Lake County Green Infrastructure Model and Strategy

Last revised 8/20/2017

Last revised 8/20/2017

Green Infrastructure Model and Strategy for Lake County, Illinois

Technical Report

Prepared by The Conservation Fund and Lake County Forest Preserve District March 2016

Project Point of Contact Jim Anderson Director of Natural Resources, Lake County Forest Preserve District janderson@lcfpd.org

Report Co-Authors Will Allen Vice President, Conservation Planning & Integrated Services 919-967-2248 wallen@conservationfund.org

Jazmin Varela Strategic Conservation Information Manager jvarela@conservationfund.org

Ted Weber Strategic Conservation Science Manager tweber@conservationfund.org

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TABLE OF CONTENTS

1. Project Summary ....................................................................................................... Page 5 2. Project Goals and Objectives ..................................................................................... Page 6 3. Planning Process ........................................................................................................ Page 7 4. Project Location ......................................................................................................... Page 9 5. Project Scope ........................................................................................................... Page 15 6. Strategic Habitat Conservation Areas ..................................................................... Page 17 a. Chain O’ Lakes ................................................................................................... Page 18 b. North Central Lake County ............................................................................... Page 20 c. Lake Michigan North ......................................................................................... Page 23 d. Lake Michigan South ......................................................................................... Page 27 e. Des Plaines River ............................................................................................... Page 31 f.

Fox River Hill and Fen ........................................................................................ Page 35

g. Lake-McHenry Central Wetlands ...................................................................... Page 38 7. Ecological Complexes .............................................................................................. Page 41 8. Ecological Enhancement Areas ............................................................................... Page 45 9. Green Infrastructure Model and Strategy ............................................................... Page 46 10. Large-scale Habitat Conservation Opportunities .................................................... Page 53 11. Ecosystem Service Valuation ................................................................................... Page 63 12.Appendices and Reference ...................................................................................... Page 79

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1.

PROJECT SUMMARY

The Lake County Green Infrastructure Model and Strategy (GIMS) builds on the previous efforts of the Chicago Wilderness regional Green Infrastructure Vision (GIV) through building a more refined green infrastructure network model with higher resolution and more up-to-date GIS data. The GIMS also builds on the efforts of The Conservation Fund’s (the Fund) support to the Chicago Metropolitan Agency for Planning (CMAP) to assess ecosystem service valuation in Lake and six other Illinois counties in its planning area.

The Lake County GIMS provides a framework for identifying land conservation and restoration opportunities for the county’s major native landscape types: woodland/forest, prairie/grassland/savanna, wetlands, and freshwater aquatic systems. The primary products of the Lake County GIMS are derived GIS datasets and models, which describe and characterize the regional green infrastructure network, restoration opportunities, and ecosystem service values of this network. The derived GIS datasets include core areas, functional connections, restoration building blocks, and composite layers that combine the science-based, data-driven ecological network with the inventory of protected and managed lands. Included in the functional connections are corridor linkages for woodland/forest, prairie/grassland/savanna, wetlands, and stream buffers, as well as functional connectivity within Lake County’s trail network.

Lake County Green Infrastructure Model and Strategy

Lake County Green Infrastructure Model and Strategy

THE

Hubs

THE

Potential Restoration

C O N S E RVAT I O N F U N D

C O N S E RVAT I O N F U N D Jerome Creek-Des Plaines River

Channel Lake

£ ¤

£ ¤

41

41

North Mill Creek

Bassett Creek-Fox River

Sterling Lake-Des Plaines River

Sequoit Creek

Nippersink Creek Nippersink Lake-Fox River

Waukegan River-Frontal Lake Michigan

Mill Creek

Pistakee Lake-Fox River

Squaw Creek

Bull Creek-Des Plaines River

Lake Michigan

£ ¤

£ ¤

45

45

£ ¤

£ ¤ 12

£ ¤

Griswold Lake-Fox River

41

41

Headwaters Squaw Creek

£ ¤ 12

§ ¦ ¨

§ ¦ ¨

94

94

Cotton Creek

£ ¤

£ ¤

45

45

Indian Creek

Cary Creek-Fox River

Upper North Branch Chicago River

£ ¤

Skokie River

£ ¤

45

45

Diversey Harbor-Frontal Lake Michigan

£ ¤

McDonald Creek-Des Plaines River

£ ¤

14

14

Flint Creek

§ ¦ ¨ 290

Wheeling Drainage Ditch

Spring Creek-Fox River

§ ¦ ¨ 294

West Fork North Branch Chicago River

§ ¦ ¨ 290

Copyright: ©2013 Esri, DeLorme, NAVTEQ

0

Date: 4/25/2016

Hubs

CW GIV v2 Composite

Figure 1. Green infrastructure hubs in Lake County

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294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

4 Miles

1:200,000

Ü

Map prepared by The Conservation Fund

Lakes

§ ¦ ¨

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

12-Digit HUC PGS Restoration

Wetland Restoration Aquatic Restoration Woodland | Forest Restoration

0

Date: 4/25/2016

4 Miles

1:200,000

Ü

Map prepared by The Conservation Fund

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Figure 2. Potential restoration opportunities in Lake County

Last revised 8/20/2017

2.

PROJECT GOALS AND OBJECTIVES

These products serve as visual and digital representation and guidance for some of the goals and objectives of the Lake County Forest Preserve District's 100-Year Vision and Strategy, including: Strategic Goals • Conserve Nature at a Landscape Scale •

Prevent Species Loss

•

Establish Data-driven Conservation

•

Eradicate Buckthorn

•

Improve Water Quality

Current 100-Year Vision and Strategy Objectives • Determine the location of three 10,000-acre complexes that provide large-scale habitats for woodland, grassland and wetland plant and animal species.

•

Develop a land classification and land use policy for the District.

•

Formalize a procedure for creating, editing and storing geospatial and demographic data, which includes information, images, maps and metadata.

Current Regional Conservation Plans In 2009, the Lake County Land Preservation Partners and the boards of all 17 participating groups established and approved the following vision: “To release a Lake County landscape where, by the year 2030, at least 20 percent of the county is preserved forever as natural areas, parks, trails, farmland and scenic views.” With the county comprising approximately 300,000 acres, this is equivalent to protecting 60,000 acres. As of April 31, 2016, 54,758 acres have been preserved, leaving 5,242 acres of land to be preserved by 2030.

The Lake County GIMS also represents several regional conservation plans. These include the following: •

US Fish and Wildlife Service—Upper Midwest and Great Lakes Landscape Conservation Cooperative

•

US Fish and Wildlife Service—Eastern Tallgrass Prairie and Big Rivers Landscape Conservation Cooperative

•

US Fish and Wildlife Service—North American Waterfowl Management Plan

•

Partners in Flight—North American Landbird Conservation Plan

•

US Shorebird Conservation Plan

•

Midwest Partners in Amphibian and Reptile Conservation—Habitat Management Guidelines for Amphibians and Reptiles of the Midwestern United States

•

The Nature Conservancy—Priority Conservation Areas

•

Illinois Wildlife Action Plan

•

Chicago Region Trees Initiative

•

Chicago Botanic Garden Plants of Concern Program

•

Chicago Wilderness—Biodiversity Recovery Plan

•

Chicago Wilderness—Oak Ecosystems Recovery Plan

•

Chicago Wilderness—12 Priority Species

•

Lake County Regional Framework Plan

•

Lake County Stormwater Management Commission—Watershed Plans (Several)

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3.

PLANNING PROCESS

The Lake County Forest Preserve District (the District) exists for the primary purpose of acquiring, developing and maintaining land in its natural state; to protect and preserve the flora, fauna, and scenic beauty; for the education, pleasure and recreation of the public; and for flood control and water management. Its mission is to preserve a dynamic and unique system of natural and cultural resources, and to develop innovative education, recreation and cultural opportunities of regional value while exercising environmental and fiscal responsibility. The District currently manages over 31,000 acres in Lake County, which constitutes a significant portion of the over 40,000 acres of protected and managed lands within the county (Figure 3).

In early 2014, the District completed its 100-year Vision and Strategic Plan, which identifies strategic directions for ecological conservation to be implemented over the next 25 years (Figure 4). This plan identifies the use of science-based, data-driven conservation to guide the District’s efforts to make the 100-year vision and strategic plan a reality.

In 2015, the District selected The Conservation Fund to lead the development of a geographic information system (GIS) based Green Infrastructure Model and Strategy (GIMS) to guide regional, local and site green infrastructure planning by agencies, organizations, corporations and citizens of Lake County, Illinois. This Strategy will greatly aid the District’s and other agencies’ planning and implementation efforts by providing a consistent modeling framework throughout the county as well as a common vision for conservation across the entire county.

The Lake County GIMS supports the goal to delineate large ecological complexes within and adjacent to Lake County, and advances the 2010 open space goals articulated by the Land Conservation Partners of Lake County:

Figure 3. Lake County, IL protected and managed lands

Figure 4. 100-year Vision for Lake County, Illinois

“Land preserved as open space is critical to a healthy region. In Lake County, Illinois, a number of public and private partners have been working hard to preserve these critical lands and, to date, 39,344 acres, or 13.4 percent, have been protected. Great progress has been made but there has never been an effort to articulate a collective countywide vision for land preservation that encompasses private lands as well as lands under state, county and municipal management. With this vision land conservationists within Lake County will know exactly what our target is and how far we have to go to get there. The window of opportunity to preserve land is quickly closing, adding urgency to the need for creating this vision.”

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The Lake County GIMS officially kicked off with the first Advisory Committee meeting on July 2, 2015. Led by The Conservation Fund, the objectives of the initial webinar were to ensure that we had a comprehensive list of all data needed to complete the project and that we could obtain all of the best available data in a timely manner. We also reviewed a list of the relevant planning documents that needed to be analyzed, and provided an overview of the conceptual approach for the GIV network models and functional connectivity.

Following a GIS data discovery and quality assessment process, the Advisory Committee reconvened on August 25, 2015 to revise the proposed strategy for updating the green infrastructure GIS models (known as a network design protocol) with the refined data that was available for Lake County, including high-resolution land cover that was far superior to that used for the second version of the Chicago Wilderness Green Infrastructure Vision.

On October 1, 2015, the District convened a conference call with a select group of Lake County biologists to review focal species options for each landscape type. This call provided critical guidance on selecting parameters for the functional connectivity models to connect core areas, including identification of surrogate species for core areas and corridors.

On November 16, 2015, the District reconvened the Advisory Committee to review the green infrastructure core data and provide input on the next steps needed to complete final versions of all of the GIS products, including the restoration building blocks. We also obtained feedback on how to structure the opportunity assessments and how to begin to delineate large ecological complexes.

On January 29, 2016, the District reconvened the Advisory Committee for a final time to review all of the available deliverables and to provide guidance for the in-person workshop that was convened on February 4, 2016, for the Lake County “Committee of the Whole.” The in-person meeting provided final guidance on strategies for delineating large ecological complexes within the County.

The final products were completed in November 2016. The project team thanks everyone who supported this ambitious effort (Figure 5).

Advisory Committee Jim Anderson, Lake County FPD Leslie Berns, Lake County FPD Steve Byers, Illinois NPC Keith Caldwell, Lake County GIS Kathryn Doyle, Lake County Ken Jones, Lake County FPD Richard Knodel, Lake County GIS Ryan London, Lake Forest Open Lands Association Rebeccah Sanders, Audubon Chicago Lydia Scott, Morton Arboretum John Sentell, Lake Forest Open Lands Association Stephen Smith, Citizens for Conservation Sarah Surroz, Conserve Lake County Thomas Vanderpoel, Citizens for Conservation Nancy Williamson, Illinois DNR Additional Project Support Mark Bramstedt, USDA NRCS Lindsay Darling, Morton Arboretum Allison Frederick, Lake County FPD Gary Glowacki, Lake County FPD Catherine Hesser, Lake County Partners Kathy Luther, NIRPC Kent Messer, University of Delaware Christine Miller, Lake County FPD Bethany Olmstead, The Conservation Fund Jarlath O’Neil-Dunne, University of Vermont – Spatial Analysis Lab Tim Preuss, Lake County FPD (IDNR, 2016) Michael Schwartz, The Conservation Fund Scott Tison, The Conservation Fund Louise Yeung, CMAP Figure 5. Green infrastructure Strategy project support

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4.

PROJECT LOCATION (WITHIN THE ECOLOGICAL DIVISIONS OF ILLINOIS)

Lake County is located in the very northeast corner of Illinois bordered by Lake Michigan to the east, Wisconsin to the north, McHenry County and the Fox River to the west and Cook County to the south. The county is the youngest geological area in the State of Illinois with north to south running glacial moraines, starting with the Valparaiso Moraine in the west, moving east to the Tinley Moraine, Park Moraine, Deerfield Moraine, Blodgett Moraine, and farthest east, Highland Park Moraine. The project location is located within the Northeastern Morainal Natural Division of Illinois, which is described below and provides an ecological, geological and physical description of the landscape of Lake County and adjoining lands. Since the draft of this report, the Illinois Department of Natural Resources has revised the Wildlife Action Plan and identified a Natural Division for Lake Michigan, a draft description of the division is available here: http://www.dnr.illinois.gov/conservation/IWAP/Documents/NaturalDivisions/LakeMichigan.pdf

Figures 6 & 7. (Above)The Illinois Natural History Survey classified natural communities within the State of Illinois according to the geological history of the different regions. (Below) Lake County is located in the Northeastern Morainal Natural Division, area #3, and the natural communities that have developed after the glaciers retreated are described below.

Northeastern Morainal Natural Division Characteristics The Northeastern Morainal Natural Division (a Natural Division is an area of similar ecological communities) contains a landscape of the most recently glaciated portion of Illinois within the counties of Boone DeKalb, DuPage, Kane, Lake, McHenry, Will, and Winnebago. Four distinct Sections within the Division are recognized due to variations in topography, soil, glacial activity, flora, and fauna. Drainage is poorly developed in some areas, thus abundant marshes, natural lakes, and bogs are distinctive features. Other areas have well-drained glacial outwash soils with seeps, fens, and springs. The Chicago lake plain and ancient beach ridge, bluff and panne communities provide unique critical habitat found only in the Northeastern Morainal Natural Division in Illinois. Higher gradient streams flow over gravel, cobble, and bedrock, providing good substrate for habitat and more stable streambed characteristics compared to many older regions of Illinois with loess-dominated soils. Stable rocky substrate, combined with significant ground water flow in some areas provides unique cool water conditions for excellent populations of diverse non-game communities.

With such diverse wetlands, prairie, forest, savanna, lakes, and streams, the Northeastern Morainal Natural Division hosts the greatest biodiversity in Illinois. Along with the largest human population, northeastern Illinois also has the most extensive acreage of protected natural areas, which offer excellent active and passive recreational opportunities.

Like most areas of the state, natural land cover has been extensively altered, although urbanization is considerably more extensive than elsewhere in the state, and expansion of development continues to be a major threat.

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Major Habitats & Challenges within Northeastern Morainal Natural Division Forest Including open woodlands and savannas, there are currently less than 270,000 acres of forest in the natural division, from a historical 765,000 acres.

• Buckthorn and other woody exotic invasion • Lack of timber management improvements • Drainage diversion and floodwater • Nuisance animals, such as feral cats, raccoons, and brown-headed cowbirds • Excessive deer browse • Sugar maple infestation • Exotic insect pests, such as emerald ash borer, gypsy moth, and Dutch elm disease • Too little oak regeneration due to lack of fire and other factors • Fragmentation/edge effect from development

Open Woodland/Savanna • • • •

Buckthorn and other woody exotic invasion Bur Oak Blight Excessive deer browse Fragmentation/edge effect from development

Grassland Less than 245,000 acres remain.

• Dominance by exotic and invasive species • Fragmentation/edge effect from development

• • • •

Lack of fire Lack of mature, cavity-producing timber No seed bank Past over-grazing

•

Nuisance animals, including feral and domesticated cats Woody species invasion or natural succession to forest

•

Wetland Historically, more than 568,000 acres occurred in the Division, but less than 72,000 acres at present.

• Drainage issues, including de-watering • Nuisance native animals, such as beaver and Canada goose • Exotic species, including reed canary grass, phragmites, purple loosestrife, Asian carp, and • Nutrient overload mute swans • Sedimentation • Filling • Urban run-off and pollutants • Impounding water too long • Increased salinity

Lakes and Ponds Lake County has 10,000 acres of large glacial lakes, including Fox, Chain, Loon, Deep, Diamond, Bangs, Lake Zurich, Timber, Turner, Little Silver, Long, and others.

• Increased turbidity from agricultural and urban • Loss of vegetative habitat due to excessive runoff and pollutants removal of submerged aquatic vegetation • Invasive exotics, such as curly-leaf pondweed, • Municipal wastewater discharge Eurasian water milfoil, and zebra mussel • Nutrient input and eutrophication • Isolation from wetland habitat by berms and • Road salt for de-icing spillways, dams, and shoreline development • Sediment and shoreline erosion from boating (i.e. Riparian vegetation removal and seawall • Stormwater discharge and impermeable construction) surfaces severely impacting water quality

Streams Urbanization may be the most critical challenge to stream communities.

• Dams • Increased point and non-point sources pollution causing exacerbated nutrient levels • Elevated water temperatures • Increased stream flow from higher impervious • Increased demand for surface water surface coverage Page 10 of 172

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Major Habitats & Challenges within Northeastern Morainal Natural Division (continued) Beach, Dune, Panne • Hydrological alterations • Ongoing battle with accelerated shoreline degradation and lack of sand nourishment • Invasive and exotic species • Nuisance native animals, such as beaver

Challenges for All Community Types Urbanization has numerous impacts, some irreversible, on all habitat types in the Northeastern Morainal Natural Division: • Altered hydrology • Light, noise, and air pollutions • Dams • Nuisance invasive plant and animal species • Filling • Runoff • Impervious surface • Siltation • Land clearing

Opportunities The Northeastern Morainal Natural Division has many sizable, potentially good quality habitats protected by public and private landowners. Seven Forest Preserve Districts, two Conservation Districts, and the Illinois Department of Natural Resources facilitate landscape-scale management. These landowners alone own over 355,000 acres of open space and fish and wildlife habitat. Two federal facilities, Fermilab and Argonne, contain an additional 8,000 acres of significant habitat.

Much of the public land is concentrated around stream corridors, wetland, and lakes. Over 20,500 acres of public and private land within the natural division are managed as Illinois Nature Preserves or Land and Water Reserves. Many partnerships with a multitude of public and private conservation organizations and institutions exist in the Northeastern Morainal Natural Division. These partners are targeting restoration and management goals for all major habitat types.

Funding used by partners for terrestrial and aquatic habitat protection, acquisition and restoration include federal (e.g., State Wildlife Grant Program, U.S. Army Corps of Engineers fines and mitigation fees, various U.S. Fish & Wildlife Service funds), state (e.g., Open Land Trust, Illinois Environmental Protection Agency 319 Nonpoint Source Pollution fund, Clean Energy Foundation) and local (Open Space Referendum) sources. Private resources come from county residents and through independent conservation land trusts and the Preservation Foundation of the Lake County Forest Preserves.

Restoration Guidelines For Natural Communities Landscapes Restoration and management of large, contiguous tracts of land will become more difficult as urbanization continues.

New landscape-scaled projects are still possible in Boone, Cook, McHenry, Lake, Kane, and DeKalb counties. Existing large areas throughout the natural division will benefit from on-going and planned restoration and management.

Forests Increase by 8,000 acres. Restore and manage 20 sites >500 acres, 4-5 sites 800-1000 acres, and 100% of all remaining Flatwoods.

Savannas Increase by 12,000 acres. Restore and manage 15-20 existing sites to >200 acres, and 10 sites to >500 acres Grasslands Increase by 20,000 acres. Restore and manage 10-12 sites with >65% grass cover and >500 acres. Grassland complexes >3,000 acres should maintain at least 65% grassland cover. Restore and manage 100% of remaining dolomite and gravel prairie types.

Wetlands Increase by 1,500 acres. Restore and manage 15 sites of >1,000-acres complexes with several 50- to 100-acre wetlands community types including fens, panne, seeps/springs, and sedge meadow.

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Restoration Guidelines For Natural Communities (continued) Glacial lakes Most glacial lakes are not protected. They are owned by an organization other than the state, nature preserve, or county. Many glacial lakes have homeowners associations making management decisions regarding lake quality according to Illinois Water Law.

Natural communities in the Natural Area Division • Beach • Fen • Sand and other savanna • Bog • Forested fen • Sand flatwoods • Calcareous floating mat • Glacial lakes • Sand prairie • Cattail marsh • Graminoid fen • Sedge meadow • Cool water streams • Gravel prairie • Seeps/springs • Dolomite prairie • Northern flatwoods • Swale • Dune • Panne • Vernal ponds

Critical Species in the Natural Area Division Amphibians • Blanchard's cricket frog • Plains leopard frog • Wood frog • Blue-spotted salamander • Smooth green snake

Birds • American bittern • Forster's tern • Red-headed woodpecker • Black rail • Greater yellowlegs • Sandhill crane • Black tern • Henslow's sparrow • Swainson's hawk • Black-billed cuckoo • Least bittern • Upland sandpiper • Black-crowned night • Loggerhead shrike • Wilson's phalarope heron • Northern flicker • Yellow rail • Bobolink • Northern harrier • Yellow-headed blackbird • Common moorhen • Piping plover • Common tern

Fish • Banded killifish • Brook trout (extirpated) • Longnose sucker • Blackchin shiner • Iowa darter • Pugnose shiner • Blacknose shiner • Lake chubsucker (indicator • Starhead topminnow species) • Bowfin • Lake sturgeon Insects • Elfin skimmer dragonfly • Karner blue • Swamp metalmark • Hine's emerald dragonfly • Silver-bordered fritillary • Hoary elfin • Silvery checkerspot

Mammals • Bobcat • Indiana bat • Meadow jumping mouse • Franklin's ground squirrel • Least weasel

Mussels • Black sandshell • Purple wartyback • Slippershell • Creek heel splitter • Rainbow • Spike • Ellipse • Salamander mussel Page 12 of 172

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Critical Species in the Natural Area Division (continued) Reptiles • Blanding's turtle • Graham's crayfish snake • Bull snake • Kirtland's snake • Eastern massasauga • Spotted turtle

Non-game Indicator Species in the Natural Area Division Forest • Barred owl • Little brown bat • Eastern gray squirrel • Spotted salamander • Hairy woodpecker • Spring peeper

Open Woodland/Savanna • Baltimore oriole • Fox squirrel • Cooper's hawk • Red bat • Eastern bluebird • Red-headed woodpecker • Eastern kingbird • Six-lined racerunner

Grasslands • Bobolink • Henslow's sparrow • Eastern meadowlark • Meadow vole

Wetlands • Common snapping turtle • Marsh wren • Great blue heron • Meadow jumping mouse • Great egret • Muskrat • King rail • Northern leopard frog

• Pied-billed grebe Glacial Lakes • Blackstripe topminnow • Grass pickerel • Bowfin • Lake chubsucker

Streams • American brook lamprey • Lake chubsucker • American eel • Least darter • Bluntnose darter • Mottled sculpin • Brassy minnow • Pugnose minnow • Creek chubsucker • Rainbow darter • Freckled madtom • Slender madtom

Non-game Indicator Species in the Natural Area Division (continued) Beach & Panne/Dune • Blanchard's cricket frog • Plant-host insect specie • Eastern tiger salamander • Least weasel • Meadow jumping mouse • Meadow vole • Migratory shorebirds and raptors • Olympia marble wing Page 13 of 172

•

Western ribbon snake

• • •

Eastern tiger salamander Wood frog Wood thrush

• • •

Southern flying squirrel White-footed mouse Wood frog

• •

Plains garter snake Smooth green snake

• • • •

Sandhill crane Sora Virginia rail Yellow-headed blackbird

•

Warmouth

• • • • • •

Southern redbelly dace Speckled chub Starhead topminnow Stoneroller Suckermouth minnow Trout-perch

Last revised 8/20/2017

Illinois Department of Natural Resources’ Conservation Opportunity Areas in Lake County Illinois Department of Natural Resources’ Wildlife Action Plan identifies areas that provide significant wildlife habitat.

These areas are designated as “Conservation Opportunity Areas” (COA). Below are the three COA in Lake County.

Illinois Beach—Chiwaukee Prairie COA The Chiwaukee Prairie Preservation Fund established a 40-year partnership to preserve and restore Chiwaukee Prairie in southeast Wisconsin. Partners include the Village of Pleasant Prairie, University of Wisconsin-Parkside, The Nature Conservancy-Wisconsin and the Wisconsin Department of Natural Resources. Potential exists for a larger agreement to manage critical beach, dune, and swale habitat across state lines with Wisconsin and Illinois Department of Natural Resources at Illinois Beach State Park and the LCFPD at Spring Bluff and Lyons Woods Nature Preserves. Lake County Forest Preserve District restoration ecologists have initiated contact with the Wisconsin partners. Opportunities for reintroductions of rare insects and management of federally endangered species exist. This COA was recently recognized as a Ramsar Wetland of International Importance.

Lake-McHenry County Wetland Complex COA •

•

Protected lands o Airstrip Marsh o Bangs Lake o Black Crown Marsh o Broberg Marsh o Chain O' Lakes o Fairfield Road South Marsh

o o o o o o o

Fourth Lake Nature Preserve Gavin Bog & Prairie Grant Woods Marl Flat McDonald Woods Moraine Hills Nippersink

o o o o o o

Redwing Slough Rollins Savanna Schreiber Lake Bog Sun Lake Volo Bog Wauconda Bog Nature Preserve

Priority resources o

Several rare wetland types, including fens and pannes

o

Rare wetland and grassland species, some not found elsewhere in Illinois

o

Several hundred recently protected acres slated for wetland, prairie, and savanna restoration

Upper Des Plaines River Corridor COA Protected lands o Van Patten Woods o Wadsworth Savanna Nature Preserve o Sedge Meadow o Oak-Hickory • Priority resources o Des Plaines River o Wetland, sedge meadow, and savanna habitat o Several threatened/endangered species o Migratory birds • Conservation opportunities o Large areas are available for wetland, savanna, sedge meadow, and floodplain forest restoration within this complex.

•

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5.

PROJECT SCOPE

The Lake County Green Infrastructure Model and Strategy (GIMS) was undertaken to provide a geographic information system (GIS) based model that could provide information to make data-driven decisions about five special projects: •

Identification of three 10,000 acre ecological complexes in and around Lake County

•

Assessment of water resource capabilities and groundwater recharge areas

•

Assessment of potential large-scale woodland, wetland and prairie opportunity areas

•

Assessment of Lake Michigan ravine and lake plain opportunities

•

Assessment of ecosystem valuation in Lake County

In response to these projects, The Conservation Fund has developed GIS information that provides data to make determinations about the special projects.

Based on the data provided by the GIMS, meetings with the Advisory Committee and the workshop, we have selected three ways to illustrate the boundaries of resources within the study area. These are based on landscape processes, watersheds and the desire to provide habitat for the native species of Lake County to ensure that no species are lost and that populations of plants and animals can expand and increase.

Strategic Habitat Conservation Areas The first method is "Strategic Habitat Conservation Areas" (SHCA). As defined by the United States Fish and Wildlife Service, these are large landscape scale conservation areas to address conservation challenges that cross jurisdictional boundaries, such as habitat fragmentation, disease, and climate change, requiring conservation planning at an ecologically appropriate scale (e.g. watershed, ecoregions, etc.) rather than smaller scales (e.g. single land management units) that coincide with jurisdictional boundaries. By starting at larger versus smaller scales, we are better able to address conservation challenges that cross arbitrary boundaries (e.g., fragmentation, dispersal barriers, climate change).

Ecological Complexes The second method, which is a working objective of this project, is to identify 10,000-acre "Ecological Complexes" within and around Lake County. An Ecological Complex is a collection of core preserves (2,000–5,000 acres) and connecting corridors within an SHCA that provides habitat or potential habitat for a diverse collection of natural communities. The connecting corridors are critical in that they provide a buffer to the core preserves, wildlife corridors, and buffers along aquatic systems connecting the core preserves. Ecological Complexes are seen as priority areas within and adjacent to Lake County where the District and its partners should be focusing protection and restoration efforts. This is not to say other areas are not important, but this allows the District and partners to apply "Precision Conservation," implementing conservation where it will have the most measurable effect.

Enhancement Areas The third method is "Enhancement Areas." These are areas of the infrastructure that provide protection and habitat for species and communities, but further expansion and/or acquisition are limited by current land uses. These Enhancement Areas still contain important ecological resources that should be protected and enhanced through "Community Conservation." This process involves the District and other entities working with local communities in the Enhancement Areas to establish backyard buffers and local site-based green infrastructure practices that increase infiltration, protect important hydrological connections and provide potential habitat for native species.

The District and the GIMS Working Group held a planning workshop to identify important conservation areas adjacent to and within Lake County. From this effort and follow-up conversations, we have identified seven SHCA and four Enhancement Areas. The selection of the SHCA was built upon the fact that these conservation areas are based upon habitat types and their ability to sustain species and ecological functions.

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Strategic Habitat Conservation (SHC) planning is based on a system established by the United States Fish and Wildlife Service and the United States Geological Service. SHC provides a framework for developing, setting, and achieving conservation targets at multiple scales, based on the best information, data, and ecological models. By utilizing this framework, we move away from opportunistic, program-specific actions to an approach that features a strategic focus.

Full implementation of SHC entails four elements that occur in an adaptive management circular continuum: • • • •

Biological Planning Conservation Design Conservation Delivery Monitoring and Research

This framework requires answers to vital questions about our conservation efforts: How? Where? When? How much?

None of the theory, planning or design becomes worthwhile until the efforts have been implemented. However, the SCH framework becomes strategic, because the on-the-ground implementation is established on sound planning and designs and can be documented through monitoring and research. SHC is a form of adaptive management specifically tailored to habitat conservation that can measurably benefit species populations.

Figure 8. A schematic including many of the important elements in the iterative SHC approach to conservation. Diagram courtesy of the United States Fish and Wildlife Service.

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6.

STRATEGIC HABITAT CONSERVATION AREAS

Figure 9. Strategic Habitat Conservation Areas were based upon both the watersheds and the habitats found within and around them.

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The seven Strategic Habitat Conservation Areas (SCHA), visible in the map on the previous page, that were identified by the District, the workgroup, and partners include:

• Chain O’Lakes • Lake-McHenry Wetlands • Fox River Hill and Fen • Des Plaines River • Lake Michigan South • North Central • Lake Michigan North

Chain O’ Lakes Strategic Habitat Conservation Area The Chain O’Lakes SHCA consists of 62,996 acres in Lake and McHenry Counties in Illinois and Kenosha County in Wisconsin. This SHCA is associated with the Fox River and the glacial lake/wetlands around the Fox River, Nippersink Creek and Squaw Creek watersheds in Illinois and the Fox River, Bassett Creek, and Peterson Creek watersheds in Wisconsin.

Total Acres Total LCFPD Protected Wetlands (LCWI) ADID Wetlands Hydric Soils Hydric Inclusion Soils Other Soils FEMA 100-Year Floodplain Illinois Natural Area Inventory Nature Preserves Lakes

62,996 1,585 12,829 5,134 11,368 1,267 9,160 11,604 3,483 212 5,983

2.5% 20.4% 8.2% 18.0% 2.0% 14.5% 18.4% 5.5% 0.3% 9.5%

Figure 10. Chain O’ Lakes SHCA environmental data

This SHCA is anchored by the Illinois Department of Natural Resources’ 6,500-acre Chain O’ Lakes State Park. The park borders three natural lakes—Grass, Marie and Nippersink—and the Fox River that connects the other seven lakes— Bluff, Fox, Pistakee, Channel, Petite, Catherine, and Redhead—that make up the Chain. In addition, the park contains the 44-acre Turner Lake Nature Preserve within its boundaries. With nearly 6,500 acres of water and 488 miles of shoreline, the park is a very large wetland—open water habitat that is crucially important for waterfowl and wetland birds. The upland areas provide habitat for grassland and woodland birds.

Surrounding the State Park are seven Forest Preserves or Conservation District preserves, including Lake Marie Forest Preserve, Blue Bird Meadow Forest Preserve, Grant Woods Forest Preserve, Gander Mountain Forest Preserve, Nippersink Canoe Base, Pioneer Fen Conservation Site, and Weingart Sedge Meadow Conservation Site. Within these preserves are eight Illinois Natural Area Inventory sites and two dedicated Illinois Nature Preserves:

Illinois Natural Area Inventory Sites: • Channel Lake • Grass Lake Wetlands • Cross Lake • Turner Lake • Gander Mountain Geological Area • Wadley Marsh • Gavin Bog and Prairie • Weingart Sedge Meadow

Illinois Nature Preserves:

• •

Gavin Bog and Prairie Nature Preserve Turner Lake Fen Nature Preserve

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Within Kenosha County, the Southeastern Wisconsin Regional Planning Commission identified 16 natural area sites: • • • • • • • •

B/AH Sedge Meadow Camp Lake Marsh Center Lake Woods and Wetlands Fox River Park Woods Hooker Lake Marsh Montgomery Lake Marsh NN Sedge Meadow Peat Lake State Park

• • • • • • • •

Peterson Creek Sedge Meadow Rock Lake Woods Silver Lake Bog Silver Lake Wetlands Stopa Fen Trevor Creek Wet Prairie Wilmot Ski Hill Prairie Wilmot Stream Wetland

The Chain O’ Lakes SHCA provides critical protection for waterfowl and wetland birds. It is the largest collection of aquatic habitats in the Midwest. Within the SHCA there are 20 lakes that, for the most part, are associated with adjacent wetlands. This large collection of open water habitats provides excellent breeding habitat for wetland birds and provides critical habitat for migratory waterfowl species.

Gander Mountain is a 300-acre complex of oak woodlands, streamside fen, and dry hill prairie. The area has been documented as an important geological preserve. Habitat for grassland birds is planned for Bluebird Meadow Forest Preserve (235 acres). Grant Woods Forest Preserve is a 1,226-acre collection of native forested fen, wetlands, woodlands, and shrublands. A 400-acre block of shrubland bird habitat is located in the northern portion of this parcel.

Lake Marie Forest Preserve (227 acres) is a former woodland and wetland complex adjacent to the Chain O’ Lakes, which would provide critical nesting habitat for several species.

In the Wisconsin portion of the SHCA exists wetlands associated with the Fox River corridor, along with large parcels of agricultural lands that could be restored to wetlands and wet prairies. Farming practices that decrease sediment loss should be practiced to reduce the amount of sediment impacting the Chain O’ Lakes. Stopa Fen just north of the Illinois State line along the western banks of the Fox River needs protection and restoration.

Habitat Types within SHCA Community Assessment from Chicago Wilderness Biodiversity Recovery Plan and The Nature Conservancy Ranking • Graminoid Fen* – Very High Risk of Loss – Poor Condition • Gravel Prairie* – Very High Risk of Loss – Poor Condition • Streamside Marsh – Very High Risk of Loss – Poor Condition • Forested Fen* – Very High Risk of Loss – Poor Condition • Dry-mesic Woodland* – Moderate Risk of Loss – Poor Condition • Mesic Woodland* – Moderate Risk of Loss – Poor Condition • Basin Marsh* – Moderate Risk of loss – Fair Condition • Sedge Meadow* – High Risk of Loss – Fair Condition

(*) These assessments are based on habitat significance, floristic quality, species richness, numbers of endangered and threatened species, levels of species conservatism, and ecological functions have been determined to be of high biological importance in the SHCA.

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North Central Strategic Habitat Conservation Area The North Central SHCA consists of 62,635 acres in Lake County, Illinois and Kenosha County, Wisconsin. This SHCA is associated with the Upper Des Plaines River and North Mill Creek watersheds, both of which extend into Wisconsin.

Total Acres Total LCFPD Protected Wetlands (LCWI) ADID Wetlands Hydric Soils Hydric Inclusion Soils Other Soils FEMA 100-Year Floodplain Illinois Natural Area Inventory Nature Preserves Lakes

62,635 6,598 6,875 2,092 8,553 1,799 20,306 4,295 1,444 1,798 918

10.5% 11% 33.4% 13.6% 2.9% 32.4% 6.9% 2.3% 2.9% 1.4%

Figure 11. North Central SHCA environmental data This SHCA is anchored by the extensive holdings of the District (6,600-acres) and the Illinois Department of Natural Resource's Red Wing Slough/Deer Lake Management Area (600 acres). The District's preserves are located along the Des Plaines River and east of the Red Wing Slough Land and Water Reserve in the north Mill Creek watershed. The Des Plaines River and north Mill Creek watershed in Wisconsin is also part of the SHCA and includes Prairie Springs Park, Gateway Center Park, Des Plaines River Lowlands and Mud Lake sedge meadow.

Located within this SHCA there are 11 forest preserves, including Van Patten Woods, Wadsworth Savanna, Pine Dunes, Prairie Stream, Dutch Gap, Hastings Lake, McDonald Woods, Mill Creek, Ethel's Woods, Raven Glen Sedge Meadow and Oak Hickory Forest Preserves. Within these preserves are five Illinois Natural Area Inventory sites, a dedicated Illinois Nature Preserve, and a Land and Water Reserve: Within Kenosha County, the Southeastern Wisconsin Regional Planning Commission identified 14 natural area sites: • • • • • • •

Bain Station Low Prairie Bain Station Railroad Prairie Benedict Prairies Bristol Woods Des Plaines River Lowlands Des Plaines River Wetlands Highway C Low Prairie Wetland

Illinois Natural Area Inventory Sites: • Antioch Bog • Little Silver Lake • McDonald Woods Marsh Land and Water Reserve • Redwing Slough

• • • • • • •

Lake Russo Prairie Remnant Louvain Old Field Merkt Woods Mud Lake Sedge Meadow Piela Wetlands Pleasant Railroad Prairie Salem Lake Road Marsh

• •

Redwing Slough Wadsworth Prairie and Savanna

Nature Preserves • Wadsworth Prairie and Savanna

The North Central SHCA provides critical protection for shorebirds, waterfowl and wetland birds, forest interior bird species at Ethel's Woods Forest Preserve, Bristol and Merkt Woods, aquatic species in the Des Plaines River, streamside sedge meadows along the Des Plaines River valley, and large areas of oak savannas scattered across the SHCA. Within the SHCA there are 20 lakes that, for the most part, are associated with the Des Plaines River and North Mill Creek watersheds. The aquatic quality of the Des Plaines River has greatly increased in the northern reaches of the watershed.

Aquatic plant and fish species are indicating improved aquatic conditions. The stretch of the Des Plaines River in the SHCA has no dams or impediments that restrict movement of aquatic species.

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While a significant portion of the river’s banks are lined with a narrow system of forest preserve holdings along its course in Illinois, suburban development within the watershed has created a river system that has lost some of its ecological and hydrological integrity. In Wisconsin, an estimated 10,000 acres of wetlands have been drained along the Upper Des Plaines and its tributaries and an additional several thousand acres have been drained in Illinois. Remaining natural areas are isolated and/or being degraded to be ecologically viable for the increase of biodiversity of fauna that would normally inhabit riparian corridors. Nevertheless, a number of top-quality natural community remnants remain in the SHCA and opportunities for restoration and connection of these preserves are present.

The U.S. Army Corps of Engineers completed the Upper Des Plaines River and Tributaries, IL & WI Integrated Feasibility Report & Environmental Assessment that focused on reducing flood potential in the Des Plaines River watershed. The feasibility report has two primary purposes: further reduction of flooding along the main stem and tributaries, and environmental restoration of degraded ecosystems within the basin. Secondary purposes are improving water quality and enhancing recreational opportunities throughout the basin. The report identified six ecological restoration projects within the SHCA, totaling 3,500 acres of wetland and prairie restoration efforts including: Proposed Projects

Acres

Bristol Marsh (WI)

1,619

Dutch Gap Forested Floodplain (WI)

689

Dutch Gap Aquatic Complex (IL)

680

Red Wing Slough and Deer Lake Complex (IL)

1,578

Pollack Lake and Hastings Creek Riparian Wetlands (IL)

429

Mill Creek Riparian Woodlands (IL)

276

In addition to these proposed projects, there are extensive agricultural areas that could be restored to native prairies, savannas, and riparian wetlands. Within the SHCA the following forest preserves provide unique habitats: Van Patten Woods This preserve is a collection of oak woodlands and riparian wetlands along the Des Plaines River. The Des Plaines River at this preserve provides habitat for native aquatic plants and fish species. The oak woodlands contain rare plant species, and prairies along the river corridor are prime habitat for reptiles and amphibians.

Oak Hickory Forest Preserve To the east of Van Patten Woods, this preserve is a mix of good quality oak woodlands and agricultural lands that could be reforested to increase woodland habitat along the eastern border of the Des Plaines River.

Wadsworth Savanna This preserve is a 1,200-acre Illinois Nature Preserve that provides habitat for high-quality marshes, sedge meadows, fens, mesic prairies, oak savanna, and woodlands. Several state-listed endangered and threatened species are known within Wadsworth Savanna, as well as a federally listed plant species that is unique to the Midwest. It is a large preserve that provides flood protection and improved water quality.

Pine Dunes, Prairie Stream, and Dutch Gap These forest preserves are located further west along the North Mill Creek watershed and consist of agricultural lands, wetlands, and prairie buffer. Red Wing Slough and Deer Lake Management Area form a large complex of wetland habitat. Restoration of these three preserves will provide a large habitat landscape that will enhance the ecological complex of wetlands and prairies associated with Red Wing Slough.

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Raven Glen and Hastings Lake These two preserves are located in the Hastings Creek watershed. Both support good quality lakes that provide habitat for rare fish and plant species. The preserves also have groves of oak trees, and Raven Glen has prairie habitat along the creek corridor.

Ethel's Woods and McDonald Woods Both are located within the North Mill Creek watershed. McDonald Woods has marsh communities that are used by waterfowl and wetland birds and oak savanna areas. Ethel's Woods has a large block of forest habitat along the eastern border of North Mill Creek. Currently, the riparian corridor is dammed and the District is draining the artificial lake and restoring the natural riparian stream and wetlands. This large block of oak forest has the potential to provide habitat for Forest Interior bird species.

Mill Creek This forest preserve is a mixture of oak woodlands and streamside wet prairie and marsh communities. North Mill Creek runs north-south through the preserve, sustains good sinuosity, and has excellent potential for stream restoration and re-introduction of native aquatic species.

Sedge Meadow This is a former experimental area with wetlands that are controlled by water control structures to conduct research.

North Mill Creek Watershed The Lake County Stormwater Management Commission has a draft plan for the North Mill Creek Watershed and has identified the following goals for the watershed and partners working within the SHCA: •

Improve and protect water quality (physical, biological, and chemical health), eliminate impairments and nonpoint source pollution, and implement land development and management practices to prevent pollution.

•

Protect, enhance & restore natural resources (soil, water, plant communities, and fish and wildlife) through the expansion of green infrastructure reserves and environmental corridors, maintaining hydrology and buffers for high-quality areas, and employing good natural resource management practices.

•

Prevent flood damage from worsening in the watershed; and reduce existing flood damage to structures, infrastructure and the increasing crop loss due to flooding.

•

Use a system of both site and watershed level stormwater green infrastructure practices, as well as regional greenways and trails to protect and connect natural resource areas and to provide recreational opportunities.

•

Guide new development design and practices to protect or enhance existing water resources, natural resources and open space (working and natural lands).

•

Provide watershed stakeholders with knowledge, skills and motivation needed to implement the watershed plan. Watershed stakeholders include (but are not limited to) residents, property owners, property owner associations, government agencies and jurisdictions, and developers.

•

Watershed stakeholder participation in farmland preservation programs, and implementation of sustainable agricultural practices that meet the watershed goals.

Wisconsin Complexes In the Wisconsin portion of the North Central SHCA, there are several large wetland complexes associated with the Des Plaines River corridor. The Des Plaines River wetlands and lowlands (480 acres) contain an extensive wetland and upland complex that are significant because of their open space and wildlife habitat. Xeric oak woods, mesic and wet-mesic prairie, sedge meadow and riverine forest provides habitat for a wide variety of species, including a federally endangered plant species. Merkt Woods (83 acres) and Bristol Woods (181 acres) are the largest blocks of oak woodlands remaining in the Wisconsin portion of the SHCA. These woods are a rich and diverse grove of xeric and drymesic woods dominated by oaks but other species like basswood and yellow bud hickories provides habitat for forest interior species.

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There are significant opportunities in the North Central SHCA to achieve these goals and provide for large restoration areas of wetland, prairie, savanna, forest and riparian habitats to benefit a very diverse collection of species including, stream fish and mussel species, grassland birds, wetland birds, forest interior species and high quality plant communities.

Within the North Central SHCA, there is significant habitat for the eastern prairie fringed orchid (Platanthera leucophaea), which is a federally threatened species. The eastern prairie fringed orchid occurs mostly east of the Mississippi River in fewer than 60 sites in Illinois, Iowa, Maine, Michigan, Ohio, Virginia, Wisconsin, and in Ontario, Canada. The eastern prairie fringed orchid occurs most often in mesic to wet unplowed tallgrass prairies and meadows but has been found in old fields and roadside ditches. The eastern prairie fringed orchid also occurs in bogs, fens, and sedge meadows. The nocturnally fragrant flowers of these perennial orchids attract hawkmoths that feed on nectar and transfer pollen from flower to flower and plant to plant. Seed germination and proper plant growth depend on a symbiotic relationship between the plants' reduced root systems and a soil-inhabiting fungus for proper water uptake and nutrition. There is a very large population within the SHCA that is being protected, managed and monitored by the Forest Preserve as part of the US Fish and Wildlife Service’s recovery program efforts for this species.

Habitat Types Within SHCA Community Assessment from the Chicago Wilderness Biodiversity Recovery Plan and The Nature Conservancy Ranking • • • • • • • • • •

Fine Texture-Soil Prairie* – Very High Risk of Loss – Poor Condition Streamside Marsh – Very High Risk of Loss – Poor Condition Graminoid Fen* – Very High Risk of Loss – Poor Condition Mesic Fine-Textured-Soil Savanna* – High Risk of Loss- Poor Condition Sedge Meadow* – High Risk of Loss – Fair Condition Dry-Mesic Woodland* – Moderate Risk of Loss – Poor Condition Mesic Woodland* – Moderate Risk of Loss – Poor Condition Wet-Mesic Woodland* – Moderate Risk of Loss – Poor Condition Basin Marsh* – Moderate Risk of Loss – Fair Condition Bog – Moderate Risk of Loss – Fair Condition

(*) These communities base on habitat significance, floristic quality, species richness, numbers of endangered and threatened species, levels of species conservatism and ecological functions have been determined to be of high biological importance in the SHCA. Lake Michigan North Strategic Habitat Conservation Area The Lake Michigan North SHCA consists of 32,959 acres in the Lake Michigan Watershed in Lake County, Illinois and Kenosha County, Wisconsin. The Lake Michigan Watershed is an area of land where water that falls as rain or snow, flows across the landscape, enters streams, ravines, and wetlands, and ultimately drains into Lake Michigan. The 48square mile (31,266-acre) watershed is bounded by Green Bay Road on the west, Lake Michigan on the east, Waukegan Harbor on the south, and 116th Street in Pleasant Prairie, Wisconsin on the north.

Total Acres Total LCFPD Protected Wetlands (LCWI) ADID Wetlands Hydric Soils Hydric Inclusion Soils Other Soils FEMA 100-Year Floodplain Illinois Natural Area Inventory Nature Preserves Lakes

32,959 1,127 6,425 4,207 5,696 3,181 17,763 3,530 3,721 1,556 112

3.4% 19.5% 12.8% 17.3% 9.6% 53.9% 10.7% 11.3% 4.7% 0.3%

Figure 12. (Left) Lake Michigan North SHCA environmental data

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The Lake Michigan North SHCA is part of the Lake Michigan Watershed, which includes portions of the Root and Pike River system in southeastern Wisconsin, Kellogg Creek in Wisconsin and Illinois, the Dead River, Waukegan River and Pettibone Creek in Illinois. These are some of the few remaining Illinois tributaries that drain to Lake Michigan and contribute to the overall quality and health of Lake Michigan and the Great Lakes system. The watershed includes over 21 miles of stream and more than 2,900 acres of wetlands. From north to south, the major stream channels include an unnamed tributary, Dead Dog Creek, Kellogg Creek, Bull Creek, and the Glen Flora Tributary. Bull Creek is made up of four tributaries, which together become the Dead River in Illinois Beach State Park. The Glen Flora Tributary, formerly known as the Little Dead River, currently flows through the Johns Manville lagoons and discharges through a pipe to Lake Michigan. The Waukegan River and Pettibone Creek watershed flow through ravines to Lake Michigan and are primarily transverse through residential areas, downtown Waukegan and the Great Lakes Naval Station.

The watershed includes Illinois Beach State Park, a National Natural Landmark visited by 2.8 million people annually, which contains 2,000 acres of Illinois Nature Preserve, a high concentration of threatened and endangered species, and unique ecosystems found nowhere else on Earth. The park also contains the last remaining undeveloped Lake Michigan shoreline and sand dune complex in Illinois. North in Wisconsin the watershed includes Chiwaukee Prairie, which is an extremely rich prairie and marsh. Further north is Carol Beach, which consists of scattered wet and dry prairie amongst private homes. In 2015, together these areas were designated as a Ramsar Wetland of International Importance. recognized internationally for the quality and significance of the biodiversity.

The watershed includes areas of the Kenosha, and Pleasant Prairie, WI, Village of Winthrop Harbor, City of Zion, Village of Beach Park, and City of Waukegan, as well as lands owned and managed by Lake County, the Lake County Forest Preserve District, the State of Illinois, and a number of other public and private entities.

Located within the Lake Michigan North SHCA there are four Forest Preserves including Spring Bluff, Thunderhawk, Lyons Woods and Greenbelt Forest Preserves. There are four Waukegan Park District properties, including Bowen Park, Beulah Park, Carmel Park and Waukegan Beach. Zion Park District owns the Hosah Prairie along the Lake Michigan coast.

In addition, there are four Illinois Natural Area Inventory Sites, four Illinois Dedicated Nature Preserves, and 12 ravine systems owned by various agencies and private landowners.

Illinois Natural Area Inventory Sites • •

Illinois Dunes North Illinois Beach

• •

Lyons Woods Waukegan Beach

• •

North Dunes Spring Bluff

• • • • •

Lyons Woods Ravine North Spring Bluff Ravine Pettibone Creek Ravine Waukegan Ravine No Name Ravines 1, 8, and 9

Nature Preserves • •

Illinois Beach Lyons Woods and Prairie

Ravines • • • • •

Bull Creek Ravine Dead Dog Creek Ravine Dead River Ravine Glen Flora Ravine Kellogg Creek Ravine

Within Kenosha County the Southeastern Wisconsin Regional Planning Commission has identified 14 natural area sites: • • • • •

104th St. Mesic Prairie Barnes Creek Dunes and Panne Bender Park Carol Beach Estates Prairie, Panne, and Prairie Chiwaukee Prairie

• • • • •

Kenosha Sand Dunes and Prairie Martian Band Parcel Nedwaki Prairie Oak Creek Power Plant Woods Tobin Road Prairie

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The foundation of the Lake Michigan North SHCA is the Wisconsin-Illinois Lake Michigan Lake Plain, which is largely protected as the Illinois Beach State Park. Long recognized for its complex geological structure, unique flora and spectacular beauty, the Lake Michigan dunes area originally stretched 6.5 miles along the sandy shore of Lake Michigan.

Illinois Beach is the only remaining beach ridge shoreline left in Illinois, with dunes, swales, sprawling marshes, black oak savannas and vast arrays of animal life and vegetation.

More than 650 species of plants have been recorded in the dunes area alone, several which are listed as threatened or endangered. Black oak woodlands with an open, savanna-like appearance crown the sandy ridges. The 4,160-acre park consists of two areas, the southern portion, which is an Illinois Dedicated Nature Preserve, and the northern portion, which is open to the public for access.

To the north of Illinois state line is Chiwaukee Prairie (310 acres), which is an excellent example of the swell and swale topography found in the Lake Michigan Lake Plain that was created when the level of glacial Lake Michigan lowered in stages. It is one of the largest prairie complexes and the most intact coastal wetlands in the region. The prairie contains an exceptional diversity of plants and animals—more than 400 species of vascular plants have been found here. The natural area features a mosaic of plant communities, ranging from southern sedge meadow, wet prairie, and wet-mesic prairie in the low areas, to dry-mesic prairie on the slightly elevated sandy ridges. Portions of the site are classified as calcareous fen, inhabited by calcium-loving plants. An oak opening dominated by bur and black oaks occupies higher, drier ground along the southern and western parts of the preserve. The northernmost portion, Kenosha Dunes, contains open and stabilized sand dunes. This variety of habitats, coupled with their location in the extreme southeastern corner of the state, allows several rare and geographically restricted plants, amphibians, reptiles, birds, invertebrates, and mammals to thrive here.

In between Chiwaukee Prairie and the Illinois Beach State Park, the 250-acre Spring Bluff Forest Preserve connects these two complexes and contains more swell and swale topography with wet, wet-mesic, mesic, dry-mesic and dry sand prairies, and black oak sand savannas. This unique preserve, along with Chiwaukee Prairie, provides critical habitat for many species, including one of the largest populations of a reptile species of greatest conservation need.

The Wisconsin and Illinois Departments of Natural Resources and the Lake County Forest Preserve District are primary owners of the Lake Plain portion within this SHCA. Waukegan Park District, the U.S. Navy, and private residents own many of the ravine communities in the SHCA. All of the ravine systems have been assessed as part of the Lake Michigan Watershed Ecosystem Partnership: Strategic Sub-Watershed Identification Process. The Lake County Stormwater Management Commission has received funding to implement ravine stabilization and restoration in the ravine systems in this SHCA. Through the Illinois Coastal Management Program (ICMP) stakeholder engagement process, coastal stakeholders have identified priority objectives that will help focus protection and management efforts. Throughout the Coastal Program area, ICMP will focus on projects that: •

Improve hydrologic regimes to more natural conditions.

•

Protect and increase interconnected open space, especially along priority waterways.

•

Support rehabilitation and redevelopment of brownfield and old industrial sites.

•

Restore and improve riparian areas, lakes and streams as habitat for birds, fish, and wildlife, including expanding protection and restoration of nearshore aquatic habitat.

•

Use green infrastructure and other strategies to manage stormwater and reduce runoff.

•

Improve and coordinate regional collaboration on invasive species management to control terrestrial and aquatic invasive species and improve ecological conditions. In addition to the big-picture priorities for the whole region, stakeholders identified objectives for each section of the Illinois coast, which reflect the environmental diversity of our shoreline.

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The watershed also includes Illinois’ only Great Lakes Area of Concern (AOC) at Waukegan Harbor. The Waukegan Harbor Citizens Advisory Group (CAG) is an organization comprised of members from area businesses, government, nongovernmental organizations and the local community. Members work together to identify and overcome obstacles to restoring the beneficial uses of the Waukegan Harbor AOC. The vision of the Waukegan Harbor CAG is: •

To ensure the expedient development and implementation of a Remedial Action Plan for the Waukegan AOC that fulfills the terms of the Great Lakes Water Quality Agreement and the Critical Programs Act.

•

To foster among the public a sense of responsibility for restoring and maintaining the ecological integrity of the Waukegan Harbor AOC.

•

To promote a lake environment for the public to use and enjoy in recognition that public access to the lakeshore will significantly benefit both the economy and the citizens of Waukegan.

Ramsar Wetland of International Importance Of significance in this SHCA is the designation of the Wisconsin-Illinois Lake Plain as a Ramsar Wetland of International Importance. The Ramsar Convention designated 3,914 acres of land owned by eight public landowners along Lake Michigan in southeast Wisconsin and northeast Illinois as a Wetland of International Importance. The designated area starts north of the Village of Pleasant Prairie and continues south to the City of Waukegan, including (north to south): • • • • •

Kenosha Sand Dunes Chiwaukee Prairie State Natural Area Carol Beach Parks and Open Space Spring Bluff Nature Preserve Fossland/Novotny Park

• • • • •

Dead Dog Creek Illinois Beach State Park and Nature Preserve Hosah Prairie Bowen Park Glen Flora Tributary

This coastal landscape, covering approximately 15 miles of coastline, contains the highest quality coastal dune and swale ecosystem in the region. The Lake Plain supports six globally rare representatives of fen, sedge meadow, freshwater marsh and seep wetland communities, as well as critical sand savanna and dry prairie upland habitat. The publicly and privately protected ecosystem connects 14 different community types, seven of which are wetland communities: •

The Lake Plain contains six representative community types of exemplary high quality, which are designated with a global conservation status ranking of imperiled or vulnerable.

•

The Lake Plain supports two federally protected wetland dependent species, including a population of eastern prairie fringed orchid (Platanthera leucophaea), as well as 1,236 acres designated as critical habitat area for the federally endangered piping plover (Charadrius melodus).

•

The Lake Plain serves as important breeding habitat for many wetland-dependent bird species and provides critical migratory stopover habitat for at least 310 migratory bird species. A portion of the Lake Plain (2,039 acres) is designated an Important Bird Conservation Area by the National Audubon Society.

Further, the Lake Plain provides additional noteworthy ecological and socioeconomic services: •

The Lake Plain wetlands and associated upland prairie and savanna complex provide habitat for over 930 native plant species and 300 animal species, including 63 state protected species.

•

The Lake Plain provides critical ecosystem services, including protection of water quality. Five major tributaries and several minor tributaries flow through the Lake Plain prior to reaching Lake Michigan.

•

The Lake Plain provides significant tourism opportunities for local communities, supporting over two million visitors a year, engaging community members in volunteer conservation stewardship, and providing high-quality examples of coastal wetland communities for education and scientific research.

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The Lake Michigan North SHCA resides within a band of important state natural areas and parks that span Lake County, Illinois. These natural areas serve as a crucial foraging and breeding grounds along the Lake Michigan flyway, which is an important migration route for many songbirds. The flyway provides a visual north-south sight line, the coast of Lake Michigan, which the birds have evolved to follow as they undergo migration. During the migration periods, March to May and September to mid-October, more than five million songbirds are believed to traverse this flyway. Audubon Society has designated Lake Michigan, Illinois Beach State Park and the Great Lakes Naval Station as Important Bird Areas in the Lake Michigan SHCA. Habitat Types Within SHCA Community Assessment from the Chicago Wilderness Biodiversity Recovery Plan and The Nature Conservancy Ranking • • • • • • • • • •

Sand Prairie* – Very High Risk of Loss – Poor Condition Graminoid Fen* – Very High Risk of Loss – Poor Condition Sand Seep – Very High Risk of Loss – Poor Condition Mesic Sand Savanna* – Very High Risk of Loss – Fair Condition Dry Sand Savanna* – High Risk of Loss – Fair Condition Sedge Meadow* – High Risk of Loss – Fair Condition Panne* – High Risk of Loss – Good Condition (this is under dispute with changing lake levels) Dry Mesic Woodland* – Moderate Risk of Loss – Poor Condition Basin Marsh* – Moderate Risk of Loss – Fair Condition Dry-Mesic Sand Savanna* – Moderate Risk of Loss – Good Condition

(*) These communities based on habitat significance, floristic quality, species richness, numbers of endangered and threatened species, levels of species conservatism and ecological functions have been determined to be of high biological importance in the SHCA. Within the Lake Michigan North SHCA, the Lake Plain habitat provides critical habitat for the piping plover (Charadrius melodus) a shorebird of the Great Lakes Region. Generally, piping plovers favor open sand, gravel, or cobble beaches for breeding. Breeding sites are generally found on islands, lakeshores, coastal shorelines, and river margins. The U.S. Fish and Wildlife Service designated critical habitat within the Lake Michigan North SHCA for the piping plover. Critical habitat is a term used in the Endangered Species Act that refers to specific geographic areas that contain habitat features essential for the conservation of a threatened or endangered species. These areas may require special management considerations or protection for the species.

The dunes and lakeshore within the SHCA also provide habitat for the federally threatened pitcher’s thistle (Cirsium pitcher). The Pitcher’s thistle is a native thistle that grows on the beaches and grassland dunes along the shorelines of Lakes Michigan, Superior, and Huron. It is now found in Indiana, Michigan, and Wisconsin and in Ontario Canada.

Pitcher’s thistle was extirpated from Illinois but has been reintroduced in Lake County lake plain. The Pitcher’s thistle (is one of many rare or declining species inhabiting dunes of the Great Lakes region. The number of dune species across different trophic levels exhibiting similar downward trends is a signal that our management or lack of it is affecting the dune ecosystem. Knowledge of the larger dune ecosystem, which influences the species’ habitat and survival, must be incorporated in recovery planning and implementation for the Pitcher’s thistle.

Lake Michigan South Strategic Habitat Conservation Area The Lake Michigan South SHCA consists of 45,343 acres in the Lake Michigan and Chicago River Watersheds in Lake County, Illinois. The Lake Michigan Watershed in this SHCA is 7,873 acres and consists of the Lake Michigan bluffs sitting atop the Highland Park Moraine of the Lake Border Morainal System and several ravine communities that are down cutting into the bluffs. The bluff area was dominated by oak ecosystems, many of which still are present today in the form of large estate homes with an intact oak canopy. The Lake Michigan portion of the SHCA stretches from just south of the Great Lakes Naval Station and extends south to Kenilworth.

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Total Acres

45,343

Total LCFPD Protected

2,162

4.8%

Wetlands (LCWI)

5,425

11.9%

ADID Wetlands

742

1.6%

Hydric Soils

7,719

17.0%

Hydric Inclusion Soils

8,554

18.9%

Other Soils

16,907

37.3%

FEMA 100-Year Floodplain

5,629

12.4%

Illinois Natural Area Inventory

1,552

3.4%

Nature Preserves

1,026

2.3%

Lakes

165

0.3%

Figures 13 & 14. (Above) Lake Michigan South SHCA environmental data.

(Right) North Branch Chicago River Watershed.

The wooded bluffs of Lake Michigan dominate the Lake Michigan Watershed portion of this SHCA. The ravines, which have down cut into the bluff as Lake Michigan, receded after the glaciers and the Lake Michigan coastline. Along the coast between North Chicago and Winnetka, the Zion City and Highland Park Moraines dead-end into Lake Michigan.

These end moraines formed about 14,000 years ago just prior to glacial ice permanently receding into the Lake Michigan basin. These are thus the youngest end moraines in Illinois. The Highland Park Moraine encompasses the entire SHCA. Long-term wave erosion along this morainal unit has resulted in bluffs that form the highest and steepest landscape along the Illinois coast. Maximum bluff heights of about 90 feet occur along the southern Highland Park lakeshore. The bluff slopes range from nearly vertical to about 45 degrees. There is considerable local variability in slope, and many segments of the bluff slope have been graded or terraced for erosion control along private lakeshore property as well as public lakeshore. A discontinuous bluff face results from a series of steep-sided, V-shaped ravines that open to the lakeshore. These ravines are cut into the morainal upland and originate as much as one mile inland from the shore. The ravines typically have intermittent streams that discharge to Lake Michigan.

The lakeshore communities that are found in the SHCA include the following starting with the tabletop bluff and extending out into Lake Michigan: Bluff The unique climate and erosive-prone clay bluff within the SHCA have an interesting suite of native plants that have evolved to withstand its harsh conditions including eroded bluff areas. These are primarily oak dominated woodland communities with scattered wet pockets.

Ravine The evolution of these SHCA ravines has shaped a unique environment with impressive flora. A multitude of factors contributes to the high diversity of plant species and micro climates found in the ravines of which include the underlying glacial substrate, close proximity to Lake Michigan, varying slope, inclinations and natural instabilities (slumps), and the presence of groundwater seeps.

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Stream Currently, all of the ravines are fragmented from Lake Michigan. In-stream habitat and fluvial geomorphology of the ravines have been adversely impacted over the last 100-years due to watershed development associated effects.

Lakeshore Much of the SHCA has little space between the shore of Lake Michigan and the bluff’s toe, but in places where enough sand accumulates, small formations of beach communities can be found.

Littoral Zone Currently, habitat consists of extensive sand flats and minor non-conformities provided by small manmade groins.

Deep Water Deepwater structures exist offshore from the SHCA and include Highland Park and Julian’s reefs. Julian’s reef is 14 miles directly east of Fort Sheridan and the Highland Park reef is three miles east. Julian’s Reef substrates include primarily bedrock with rubble, sand and small amounts of silt (Horns 1991), whereas the Highland Park reef consists of bedrock and cobble with its interstitial spaces filled in with sand and silt (Chotkowski & Mardsen 1995). The remaining deepwater areas off the coast of Ft. Sheridan are primarily sand flats.

The Lake Michigan South SHCA resides within a band of important state natural areas and parks that span Lake County, Illinois. These natural areas serve as a crucial foraging and breeding grounds along the Lake Michigan flyway, which is an important migration route for many songbirds. The flyway provides a visual north-south sight line, the coast of Lake Michigan, which the birds have evolved to follow as they undergo migration. During the migration periods, March to May and September to mid-October, more than five million songbirds are believed to traverse this flyway. The National Audubon Society has designated Lake Michigan as an Important Bird Area and within the Lake Michigan South SHCA. Located within the Lake Michigan South SHCA there are six Forest Preserves including Berkeley Prairie, Oriole Grove, Prairie wolf, Middlefork Savanna, Fort Sheridan Forest Preserves and a portion of Greenbelt Forest Preserve. The Lake Forest Open Lands Association currently has six preserves in the SHCA, including Everett Farm, Middlefork Farm, West Skokie, Derwen Mawr, Melody Farm Nature Preserve and Skokie River. Lake Bluff Open Lands Association also owns a preserve called Skokie River. There are six Highland Park District parks including Skokie River Woods, Heller Park, Rosewood Park, Mallard Park, Central Park, and Moraine Park. There are several Forest Preserve District of Cook County preserves including Skokie Lagoons, Mary Mix McDonald Woods, Turnbull Woods, Somme Woods and Prairie, Watersmeet Woods, Chiplly Woods and Sunset Ridge Woods within the SHCA in Cook County, Illinois. As part of the old Fort Sheridan Army base and the ravine to the north, there is a collection of three areas along two miles of the Lake Michigan lakefront. They include the Lake Forest Open Lands Association’s McCormack Ravine and Woods, Fort Sheridan Forest Preserve, and the Openlands Lakeshore Preserve.

Within the Lake Michigan South SHCA, there are 10 Illinois Natural Area Inventory Sites, seven Illinois Dedicated Nature Preserves, and 35 ravine systems owned by various agencies and private landowners.

Illinois Natural Area Inventory Sites • Blair Woods • Blodgett Ravine • Crabtree Farm Woods • Fort Sheridan Bluff

Illinois Dedicated Nature Preserves • Berkeley Prairie • Dokum Mskoda • Hybernia

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• • •

Fort Sheridan Site Highmoor Prairie Lake Bluff Woods

• • •

McCormick Ravine and Woods Oak Grove Botanical Area Skokie River

• •

Middlefork Savanna Openlands Lakeshore Bluff and Ravine

• •

Skokie River Skokie River Prairie

Last revised 8/20/2017

Ravine Systems • • • • • • • • • • • •

Bartlett Ravine Cemetery Ravine Clark’s Ravine Crabtree Ravine Hutchinson Ravine Janes Ravine Lillian Dells Ravine Mayflower Ravine McCormick Ravine No Name 11 No Name 3 No Name 4

• • • • • • • • • • • •

No Name 5 No Name 6 No Name 7 Ravine 1 Lake Ravine 10 Lake Ravine 2 Lake Ravine 3 Lake Ravine 4 Cook Ravine 4 Lake Ravine 5 Cook Ravine 5 Lake Ravine 6 Cook

• • • • • • • • • • •

Ravine 6 Lake Ravine 7 Cook Ravine 7 Lake Ravine 8 Lake Ravine 9 Lake Schenck Ravine Scotts Ravine South Ravine Van Horne Ravine Walden Ravine Witchhazel/Seminary Ravine

Through the Illinois Coastal Management Program (ICMP) stakeholder engagement process, coastal stakeholders have identified priority objectives that will help focus protection and management efforts. Throughout the Coastal Program area, ICMP will focus on projects that: •

Improve hydrologic regimes to more natural conditions

•

Protect and increase interconnected open space, especially along priority waterways

•

Support rehabilitation and redevelopment of brownfield and old industrial sites

•

Restore and improve riparian areas, lakes and streams as habitat for birds, fish, and wildlife, including expanding protection and restoration of nearshore aquatic habitat.

•

Use green infrastructure and other strategies to manage stormwater and reduce runoff.

•

Improve and coordinate regional collaboration on invasive species management to control terrestrial and aquatic invasive species and improve ecological conditions. In addition to the big-picture priorities for the whole region, stakeholders identified objectives for each section of the Illinois coast, which reflect the environmental diversity of our shoreline.

The Lake Michigan South SHCA also includes two portions of the North Branch of the Chicago River. These include the Skokie River Branch (17 miles), which is 19,335 acres and includes the Skokie Lagoons, Chicago Botanic Garden, and terminates at Lake Avenue in Cook County, Illinois. The second branch is generally referred to as the Middlefork of the Chicago River (24 miles), which is 15,319 acres and begins on the south side of Illinois Route 120 and stretches south to Cook County’s Watersmeet Forest Preserve just south of Winnetka Road.

Prior to 1898, the Chicago River flowed into Lake Michigan. However, due to pollution and health problems that arose from the city's sewage discharge from the river into the Lake, which was Chicago's drinking water supply, the flow of the Chicago River was reversed and diverted from Lake Michigan into the Mississippi River basin through the Chicago Sanitary and Ship Canal that was opened on January 2, 1900.

As with the watershed, the river has undergone significant change since the time of European settlement in the early/mid-1800s. Two hundred years ago, the river would have been described as a marshy slough, meandering slowly and falling imperceptibly as it flowed southward.

The clear waters of the river channels supported marsh plants, such as bulrushes and water lilies. Extending from the river were wet prairies and meadows interspersed and bordered by oak savannas that were situated on the higher ground in the watershed.

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The Middlefork and Skokie rivers are located in the lake border ground moraines and, as noted above, once flowed gently through wide marshes and sedge meadows. Today many of these waterways have been confined to excavated channels that transmit stormwater from the surrounding landscape to the main stem of the Chicago River. There are good remnant natural areas found along the river corridors, including savannas, woodlands, prairie, and wetlands.

The Lake County Stormwater Management Commission’s North Branch Chicago River Watershed-Based Plan identified goals for the Chicago River in the SHCA: •

Improve water quality in the North Branch Chicago River.

•

Reduce flood damage in the North Branch Chicago River.

•

Protect and enhance natural resources and provide associated recreational opportunities.

•

Develop a public information and education program within the watershed communities.

•

Improve participation and coordination in the watershed improvement activities.

Habitat Types Within SHCA Community Assessment from the Chicago Wilderness Biodiversity Recovery Plan and The Nature Conservancy Ranking • • • • • • • • • • • •

Fine-Textured-Soil Prairie* – Very High Risk of Loss – Poor Condition Streamside Marsh – Very High Risk of Loss – Poor Condition Wet-Mesic Fine-Textured-Soil Savanna* – Very High Risk of Loss – Poor Condition Wet-Mesic Upland Forest – High Risk of Loss – Poor Condition Mesic Fine-Textured-Soil Savanna* – High Risk of Loss – Poor Condition Sedge Meadow* – High Risk of Loss – Fair Condition Northern Flatwood* – High Risk of Loss – Fair Condition Dry-Mesic Upland Forest – Moderate Risk of Loss – Fair Condition Mesic Upland Forest – Moderate Risk of Loss – Poor Condition Wet-Mesic Woodland* – Moderate Risk of Loss – Poor Condition Dry-Mesic Fine-Textured-Soil Savanna* – Moderate Risk of Loss – Poor Condition Basin Marsh* – Moderate Risk of Loss – Fair Condition

(*) These communities base on habitat significance, floristic quality, species richness, numbers of E/T species, levels of species conservatism and ecological functions have been determined to be of high biological importance in the SHCA. Des Plaines River Strategic Habitat Conservation Area The Des Plaines River SHCA consists of 61,569 acres and includes most of the Des Plaines River watershed in Lake County from the confluence of Mill Creek and the Des Plaines River south to the confluence of McDonald Creek and the Des Plaines River at Big Bend Forest Preserve in Cook County.

Total Acres Total LCFPD Protected Wetlands (LCWI) ADID Wetlands Hydric Soils Hydric Inclusion Soils Other Soils FEMA 100-Year Floodplain Illinois Natural Area Inventory Nature Preserves Lakes

61,569 6,442 9,817 961 12,352 7,398 28,086 9,922 1,998 1,445 921

10.5% 16.0% 1.6% 20.0% 12.0% 43.5% 16.1% 3.3% 2.4% 1.5%

Figure 15. Des Plaines River SHCA environmental data

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The Des Plaines River originates in Wisconsin and flows south to the confluence with the Illinois River at Lyons, Illinois.

As the river moves through Lake and Cook Counties, farms give way to suburbs, then to edge cities of metropolitan Chicago.

Along the southern portion of the Des Plaines River in southern Lake County and northern Cook County, urban uses dominate the landscape, where urban development is 10 times more concentrated than other parts of Illinois, including northern Lake County.

This SHCA represents 96 square miles of the 346-square mile watershed of the Des Plaines River. Historically, the watershed was 40% prairie and 60% forest and savanna. Much of the SHCA landscape west of the river in Lake and Cook counties was covered with savanna and pockets of prairie, including wet prairie, and wetland marshes. East of the river, with reduced fire intensity, dense growths of woodlands and forests survived, providing habitat for migrating bird species, including a wide variety of rare warblers. Today only about 18% of the woodlands and forests remain. The nonforested areas represented by marshes, wetland meadows, and ponds only cover 3.5% of the landscape.

The backbone of the Des Plaines River SHCA is a chain of Forest Preserves that follows the river north from Lyons to just north of Libertyville. Starting south in Cook County, the Forest Preserve District of Cook County maintains a corridor of Forest Preserves along the Des Plaines River, totaling 2,679 acres and including Dam #2 Woods, Camp Pine Woods, Lake Avenue Woods, Allison Woods, Dam #1 Woods, and Potawatomi Woods Forest Preserves. In Lake County, Cahokia Flatwoods (221 acres), Edward L. Ryerson Conservation Area (564 acres), Half Day (236 acres), Captain Daniel Wright Woods (750 acres), Grainger Woods Conservation Preserve (329 acres), MacArthur Woods (505 acres), Old School (543 acres), Wilmot Woods (245 acres) Independence Grove (1,150 acres), Lake Carina (481 acres) and Sedge Meadow (607 acres) Forest Preserves.

In other parts of the Des Plaines River SHCA, there are additional Forest Preserve holdings along tributaries of the Des Plaines River, including all of Almond Marsh Forest Preserve (503 acres) and the eastern portion (187 acres) of Waukegan Savanna Forest Preserve. The Libertyville Township Open Space District has holdings scattered throughout the SHCA but is primarily located within the Liberty Prairie Reserve, which stretches from the Des Plaines River at Independence Grove Forest Preserve west to the vicinity of the intersection of Illinois Routes 137 and 120. The other preserves, totaling 561 acres include St. Mary’s, O’Plaine and Butterfield Road Preserves.

The Liberty Prairie Reserve (the Reserve) consists of approximately 5,000 acres in the heart of Lake County, Illinois, where, since 1991, over half of the land has been protected by the active leadership and cooperation of public and private landowners (i.e. Community Conservation). The Reserve’s purpose is to preserve and restore the health of natural areas to encourage the appropriate use and appreciation by the public. The goal of the Reserve is to create a model of exceptional land, water, and biodiversity health where public and private landowners manage their land in ways that sustain people, plants, and wildlife.

The Reserve is an excellent example of Community Conservation, which is an alternative response to the traditional conservation of setting preserves aside and protecting them. Community Conservation seeks to protect larger areas of land by encouraging local stewardship and integrating social and environmental priorities. The concept envisions people restoring, enhancing and enjoying a site’s rich array of natural areas in ways that support clean water and healthy soils.

This is an excellent example of the collaborative efforts the GIMS could foster in other SHCA.

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Figure 16. Map of the Liberty Prairie Reserve in the heart of Lake County, Illinois. The Reserve’s purpose is to preserve and restore the health of natural areas to encourage the appropriate use and appreciation by the public.

Within the Des Plaines River SHCA there are 11 Illinois Natural Area Inventory Sites and 10 Illinois Dedicated Nature Preserves, including: Illinois Natural Area Inventory Sites • Almond Marsh • Ascension Sedge Meadow • Elm Road Woods • Grainger Woods Illinois Dedicated Nature Preserves • Almond Marsh • Elm Road Woods • Grainger Woods • Ryerson Conservation Area

• • • •

Hermann’s Woods Liberty Prairie Lloyd’s Woods MacArthur Woods

• • • •

Milne Brook and Prairie River Road Woods Ryerson Woods St. Francis Woods

• • •

Hermann’s Woods Liberty Prairie Reserve Lloyd’s Woods

• • •

MacArthur Woods Oak Openings Rhyan Tract

The Des Plaines River, from just north of Libertyville south into Cook County, serves as a critical flyway for migrating songbirds, especially warblers and woodland bird species. The flyway also provides habitat for many wading birds like herons, waterfowl such as wood ducks and other birds such as belted kingfishers use this corridor for migration, feeding, and nesting. Of the nearly 300 bird species regularly found in Illinois, 270 of these species are found in the Des Plaines River SHCA. Fourteen of these species are listed as threatened or endangered. The Audubon Society has designated the Upper Des Plaines River corridor and Edward L. Ryerson Conservation Area as Important Bird Areas. .

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In the early 2000s, the Illinois Department of Natural Resources began their Conservation 2000 Program that designated Ecosystem Partnerships throughout the State of Illinois. These Ecosystem Partnerships were a collection of public and private partners (i.e. Community Conservation) that worked toward the goal of restoring the landscape and the human connection to that landscape. The Upper Des Plaines Ecosystem Partnership developed these objectives: •

Increase and enhance open space and recreational opportunities.

•

Protect and restore terrestrial and aquatic habitat quality and quantity, including natural hydrology.

•

Improve institutional and public coordination and communication.

•

Encourage watershed and sub-watershed leadership, stewardship and volunteer activities.

•

Educate the public and public officials about their impact and their role in protecting natural resources.

•

Increase watershed monitoring quality and frequency.

•

Reduce flooding and flood damages.

•

Reduce nonpoint source pollution.

•

Reduce point source pollution.

Habitat Types within SHCA Community Assessment from the Chicago Wilderness Biodiversity Recovery Plan and The Nature Conservancy Ranking • • • • • • • • • • • • • • • • •

Fine-Textured-Soil Prairie* – Very High Risk of Loss – Poor Condition Streamside Marsh – Very High Risk of Loss – Poor Condition Wet-Mesic Fine-Textured-Soil Savanna* – Very High Risk of Loss – Poor Condition Wet-Mesic Upland Forest – High Risk of Loss – Poor Condition Mesic Fine-Textured-Soil Savanna* – High Risk of Loss – Poor Condition Sedge Meadow* – High Risk of Loss – Fair Condition Neutral Seep – High Risk of Loss – Fair Condition Northern Flatwoods* – High Risk of Loss – Fair Condition Dry-Mesic Upland Forest – Moderate Risk of Loss – Fair Condition Mesic Upland Forest – Moderate Risk of Loss – Poor Condition Dry-Mesic Woodland* – Moderate Risk of Loss – Fair Condition Mesic Woodland* – Moderate Risk of Loss – Poor Condition Wet-Mesic Woodland* – Moderate Risk of Loss – Poor Condition Wet-Mesic Floodplain Forest – Moderate Risk of Loss – Fair Condition Wet Floodplain Forest – Moderate Risk of Loss – Fair Condition Dry-Mesic Fine-Textured-Soil Savanna* – Moderate Risk of Loss – Poor Condition Basin Marsh* – Moderate Risk of Loss – Fair Condition

(*) These communities base on habitat significance, floristic quality, species richness, numbers of endangered and threatened species, levels of species conservatism, and ecological functions have been determined to be of high biological importance in the SHCA.

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Fox River Hill and Fen Strategic Habitat Conservation Area The Fox River Hill and Fen SHCA by its name indicates that this SHCA is located in three counties, converging in the southwestern portion of Lake County. The SHCA 65,714 acres are dominated by tributaries of the Fox River and include Silver Creek (4.7 miles), Fel-Pro Creek (2.12 miles), Fiddle Creek (1.25 miles), and the two largest sub-watersheds Spring Creek (11 miles) and Flint Creek (20 miles), which are 25.8 mi2 and 36.8 mi2 respectively.

Total Acres 65,714

Total LCFPD Protected

2,027

3.1%

Wetlands (LCWI)

6,998

10.7%

ADID Wetlands

2,218

3.4%

Hydric Soils

7,920

12.0%

Hydric Inclusion Soils

1,040

1.6%

Other Soils

16,457

25.2%

FEMA 100-Year Floodplain

8,867

13.5%

Illinois Natural Area Inventory

924

1.4%

Nature Preserves

1,160

1.8%

Lakes

792

1.2%

Figure 17. Fox River Hill and Fen SHCA environmental data

The Fox River Basin is a collection of nested watersheds and serves as a vital drinking water supply for communities large and small. The Fox River Basin is a significant recreational resource. This basin is home to 150 state-threatened and endangered species in the region.

Figure 18. Geology of the Fox River Valley

The location of this SHCA places it at the edge of the Valparaiso Moraine, and the majority of the SHCA is dominated by the geology of the Fox River Valley. Associated with the Fox River are various geological features that expose layers of outwash and deposited gravel.

The Fox Lake and Cary Drifts are located at the edge of the Valparaiso Moraine and are largely silty, sandy, or gravelly till with local areas of silty clayey till, many lenses of poorly sorted gravel, and abundant small kames. The Fox Lake Moraine is largely a belt of kames along the Fox River. Scattered across the landscape are deposits of Grayslake Peat, which is peat, muck, and local exposures of marl. These are dominantly organic deposits, mostly in glacial lake basins and floodplains of major rivers. This kettle moraine type of geology presents some unique natural communities, including dry hill prairies, seeps, fens, bogs, and calcareous seeps.

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The Fox River Hill and Fen SHCA consists of a collection of low-lying wetland areas, oak and prairie knolls, high-quality streams, and a portion of the Fox River Valley. Spring Creek is one of the few remaining streams located within an urban environment in northeastern Illinois that remains undammed and is of high quality (Grade C, Illinois Department of Natural Resources Biological Stream Characterization).

Spring Creek drains large wetland complexes at Spring Lake Forest Preserve (Cook County), of which several areas are seeps along the creek corridor. Flint Creek (Grade B) over its entire 20-mile length is divided up into three forks, each of which originates in kettle marshes, some of which are fed by calcareous seeps.

Silver Creek is a very high-quality fen stream that is fed for the most part by calcareous seeps and fens. The McHenry County Conservation District primarily owns the stream corridor. This is the same case for the smaller Fel-Pro Creek, which is also a fen stream.

The geology of the Fox River is an important factor in the development of natural communities with this SHCA. The interface of the Fox River Valley with the edge of the Valparaiso Moraine, the Valparaiso Ground Moraine, and the Cary Moraine creates several areas where the down-cutting of the Fox River and its several tributaries have exposed areas of gravel layers where ground water seepage occurs. In addition, large deposits of glacial outwash exist that have formed along the north-south flow path of the Fox River, which have been identified as the Fox Lake Moraine. The exposure of these glacial deposits created some unique natural plant communities, including dry hill prairies, seeps, fens, calcareous seeps, and fen streams (i.e. brooks).

Within the Fox River Hill and Fen SHCA, there are land holdings held by three county land management agencies, including Lake County Forest Preserve District, Forest Preserve District of Cook County, and McHenry County Conservation District (MCCD). There are three preserves in Lake County, including Fox River, Grassy Lake, and Cuba Marsh Forest Preserves. There are three in Cook County, including Baker’s Lake, Spring Lake, and Crabtree Forest Preserves. There are six preserves in McHenry County, including Fox Bluff, Hollows, Silver Creek, Fel-Pro RRR, Hickory Grove, and Lyons Marsh Conservation Preserves. In addition, the Citizens for Conservation and Barrington Area Conservation Trust have holdings within the SHCA, including Wagner Fen, Steyemark Woods, Flint Creek Savanna, Grigsby Prairie, Barrington Bog, Farm Trails North, Heron Marsh Preserves, Far Field Nature Preserve, The Brothers’ Preserve, Jack David Mondschine Wildlife Conservation Area, and Pederson Preserve.

The Fox River Hill and Fen SHCA contains 21 Illinois Natural Area Inventory Sites and 13 Illinois Dedicated Nature Preserves, including: Illinois Natural Area Inventory Sites • • • • • • •

Baker’s Lake Barrington Bog Barrington Hills Botanical Area Bates Fen Blair Fens and Wet Prairie Cary Junior High Prairie Cary Old Water Tower Prairie

• • • • • • •

Crabtree Nature Center Cuba Marsh Detrana Fen Farm Trails North Hollows Lyons Prairie and Marsh Main Street Prairie

• • • • • • •

Eastern Prairie Fringed Orchid Ski Hill Prairie Spring Creek Prairie Spring Lake Thunderbird Lake Tower Lake Fen Wagner Fen

•

Eastern Prairie Fringed Orchid Farm Trails North Fel-Pro Triple R Fen Lyons Prairie and Marsh

• • • •

Main Street Prairie Oakwood Hills Fen Spring Lake Tower Lake Fen

Illinois Dedicated Nature Preserves • • • • •

Baker’s Lake Barrington Bog Bates Fen Cary Junior High Prairie Cuba Marsh

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• • •

Last revised 8/20/2017

Flint Creek Watershed Plan The Flint Creek Watershed Partnership established six goals to address issues and opportunities within the Flint Creek watershed: • Protect surface and groundwater resources and enhance overall water quality in the lakes and streams of the watershed.

•

Identify and protect important natural areas/open space in the watershed and provide appropriate passive recreational benefits.

•

Reduce existing flood damage in the watershed and prevent flooding from worsening downstream.

•

Improve aquatic and terrestrial habitat in the watershed.

•

Increase communication and coordination among municipal decision-makers and other stakeholders in the watershed.

•

Foster appreciation and stewardship of the watershed through education.

Silver Creek Watershed Plan The Silver Creek Watershed Action Plan has six main goals: • Maintain/achieve healthy surface waters within the adjacent watersheds of Silver Creek and Sleepy Hollow Creek, two tributaries to the Fox River in northern Illinois.

•

Protect the quality of groundwater.

•

Protect the quantity of groundwater.

•

Restore natural areas and increase native species diversity.

•

Increase public awareness and knowledge to motivate needed action to implement the watershed plan.

•

Establish an ongoing community participation group to expand watershed planning and protection efforts and support project implementation.

Habitat Types Within SHCA Community Assessment from the Chicago Wilderness Biodiversity Recovery Plan and The Nature Conservancy Ranking • • • • • • • • • • • • • • • • •

Fine-Textured-Soil Prairie* – Very High Risk of Loss – Poor Condition Gravel Prairie* – Very High Risk of Loss – Poor Condition Streamside Marsh – Very High Risk of Loss – Poor Condition Graminoid Fen* – Very High Risk of Loss – Poor Condition Calcareous Seep* – Very High Risk of Loss – Poor Condition Wet-Mesic Fine-Textured-Soil Savanna* – Very High Risk of Loss – Poor Condition Calcareous Floating Mat – High Risk of Loss – Fair Condition Mesic Fine-Textured-Soil Savanna* – High Risk of Loss – Poor Condition Sedge Meadow* – High Risk of Loss – Fair Condition Neutral Seep – High Risk of Loss – Fair Condition Dry-Mesic Woodland* – Moderate Risk of Loss – Fair Condition Mesic Woodland* – Moderate Risk of Loss – Poor Condition Wet-Mesic Woodland* – Moderate Risk of Loss – Poor Condition Dry-Mesic Fine-Textured-Soil Savanna* – Moderate Risk of Loss – Poor Condition Basin Marsh* – Moderate Risk of Loss – Fair Condition Bog – Moderate Risk of Loss – Fair Condition Dry-Mesic Fine-Textured-Soil Savanna* – Moderate Risk of Loss – Poor Condition

(*) These communities base on habitat significance, floristic quality, species richness, numbers of endangered and threatened species, levels of species conservatism, and ecological functions have been determined to be of high biological importance in the SHCA.

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Within the Fox River Hill and Fen SHCA, as a result of the geology of the Fox River Valley, there are numerous seeps and fens that provide unique habitats for plants and animals. Additionally, since many of the streams in this SHCA are connected to these seeps and fens the quality of the streams has been recognized as high quality. As mentioned earlier, Spring Creek is one of the few remaining streams in northeastern Illinois that does not have a dam structure on it. This allows for the migration of aquatic organisms along the entire tributary corridor to the confluence with the Fox River.

Along the stream course, there are several calcareous seeps and fens that provide habitat for a unique set of plant and animal species. Silver Creek originates in McHenry County Conservation District’s Hollows Preserve and flows through two artificial lakes, Killarney and Silver, and then into the Oakwood Hills and Bates Fen complex where it flows freely 2.3 miles to the confluence with the Fox River. The Oakwood Hills and Bates Fen complex is a collection of numerous calcareous seeps, fens, and large sedge meadows. Fel-Pro Creek, while smaller in size, also has many of the calcareous seeps and fens along its course. Flint Creek, which is dammed at Flint Lake, is also associated with fens and seeps along the three branches of the creek. In addition, Flint Creek flows through large basin marshes, sedge meadows and two large fen complexes, Wagner and Tower Lake Fens.

Hine’s Emerald Dragonfly The calcareous seeps, fens, stream runs, and associated sedge meadows provide habitat for one of the rarest dragonflies in the United States, the Federally endangered Hine’s emerald dragonfly (Somatochlora hineana). In general, adult dragonflies are terrestrial, spending much of their brief life in flight, feeding on other flying insects. The larva is aquatic, lives substantially longer than the adult, and feeds on other smaller aquatic invertebrates, small fish, and larval amphibians. After adults emerge, male dragonflies establish breeding territories and mate with females. Females lay eggs in suitable aquatic habitat. Hine's emerald larval habitat appears to be cool shallow—usually only several centimeters deep—slow moving waters, spring-fed marshes, and seepage sedge meadows. Until 2015 this species was restricted to southern Cook and Will Counties in Illinois, until the species was documented at Spring Valley Forest Preserve in the Fox River Hill and Fen SHCA. The presence of this species in this SHCA is a critically important resource that is enhanced by the numerous occurrences of its habitat in the region.

Lake-McHenry Wetland Strategic Habitat Conservation Area The Lake-McHenry Wetland SHCA is the largest of the seven SHCA’s at 88,542 acres and is located entirely within the Fox River Watershed straddling the McHenry County and Lake County geopolitical boundary. This SHCA is part of the LakeMcHenry Wetland Conservation Opportunity Area that is identified in the Illinois Department of Natural Resources Illinois Wildlife Action Plan.

The Lake-McHenry Wetlands Complex was identified by Chicago Wilderness in the Wetland Conservation Strategy as of one of the state's largest concentrations of natural wetlands and glacial lakes. Adjoining these lakes in some locations are wetlands of varying degrees of quality.

Total Acres Total LCFPD Protected Wetlands (LCWI) ADID Wetlands Hydric Soils Hydric Inclusion Soils Other Soils FEMA 100-Year Floodplain Illinois Natural Area Inventory Nature Preserves Lakes

88,542 5,857 12,958 4,282 16,419 4,024 28,832 17,581 3,064 1,597 3,753

6.6% 14.6% 4.8% 18.5% 4.5% 32.6% 19.9% 3.5% 1.8% 4.2%

Figures 19 & 20. (Above) Lake-McHenry Wetland SHCA environmental data. (Right) Map of Lake-McHenry Wetland Complex.

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The Illinois Department of Natural Resources, McHenry County Conservation District, and Lake County Forest Preserve District preserve many of these high-quality wetlands. Significant natural features in this poorly drained area include glacial landforms, natural lakes, and wetlands. Many wetland types are found in this area, such as bogs, fens, seeps and shallow and deep marshes.

The complex supports several breeding wetland species including least bittern, black tern, pied-billed grebe, sandhill crane, common moorhen, Forster's tern and yellow-headed blackbird. Audubon Society chose this complex as an Important Bird Area because it met criteria for breeding pied-billed grebe, least bittern, sandhill crane, common moorhen, Forster's tern, willow flycatcher, and yellow-headed blackbird.

The SHCA includes several tributaries of the Fox River, including Sleepy Hollow Creek, Stickney Run, Boone Creek, Dutch Creek, Cotton Creek, and Lily Lake Drain in McHenry County, as well as Fort Hill Creek, Mutton Creek, Squaw Creek and Fish Lake Drain in Lake County.

The Lake-McHenry Wetland SHCA has a very wide variety of wetlands and aquatic habitat. Within the SHCA there are 46 lakes, most of which are glacial lakes, of which some are very high quality.

This SHCA has several Forest Preserves and Conservation Preserves in the area. In McHenry County, these include Cotton Creek Marsh, Stickney Run, Weingart Road Sedge Meadow preserves and Prairie View Education Center. In Lake County, there are seven preserves, including Singing Hills, Tanager Kames, Marl Flats, Black Crown, Nippersink, Kestrel Ridge, Kettle Grove, Lakewood and Ray Lake Forest Preserves.

The SHCA has 19 Illinois Natural Area Inventory Sites and five Illinois Dedicated Nature Preserves, which include bogs, fens, seeps, marshes, sedge meadows, natural lakes, glacial features and prairies.

Illinois Natural Area Inventory Sites • Air Strip Marsh • Bangs Lake • Black Crown Marsh • Brandenburg Bog • Broberg Marsh • Cotton Creek Marsh • Cranberry Lake

• • • • • • •

Fish Lake Marl Flats Lac Louette Lily Lake Round Lake Round Lake Marsh Sargent Marsh Schreiber Lake Bog

• • • • •

Stickney Run Thunderbird Lake Volo Bog Wauconda Bog Weingart Sedge Meadow

Illinois Dedicated Nature Preserves • McLean Woods and Wetlands

• •

Pistakee Bog Volo Bog

• •

Wauconda Bog Weingart Sedge Meadow

The Lake-McHenry Wetland SHCA has a diverse wetland savanna ecosystem, which is closely linked to the Fox River, a high quality (Grade B) stream. Many wetland types are found here, including bogs, fens, seeps, and shallow and deep marshes. There are several large complexes in this SHCA area, which are held in public ownership, including the 1,700acre Moraine Hills State Park, the 1,200-acre Silver Creek Conservation Area, and the 3,000-acre Lakewood/Broberg complex. These sites are notable for containing high quality, groundwater-maintained fen, sedge meadow, and marsh remnants bordered by globally imperiled oak savanna communities. Restored marshes at Moraine Hills State Park, Lakewood Forest Preserve, and Stickney Run Conservation Area provide important breeding habitat for many stateendangered and rare marsh bird species.

There is potential in this SHCA to acquire and/or restore glacial wetland, sedge meadow, wet/mesic/dry prairie, and oak savanna communities within Lake and McHenry counties in northeastern Illinois. An area already rich in wetland resources, northeastern Illinois provides important stopover, nesting, and brood-rearing habitat for several waterfowl species. It also provides important breeding and migratory habitat for marshland and grassland birds that are considered species of conservation concern by the IDNR. Protection of this SHCA can increase the quality and quantity of wetlands and associated uplands in a region that already has existing complexes of similar habitats, recognizing that concentrations of wetlands and associated uplands typically support greater densities of breeding birds than those in isolation. Preservation and restoration of these upland and wetland complexes will provide benefits to birds both in the water and on land, including threatened and endangered species. This project will help reach the goals of the North American Waterfowl Management Plan, Partners In Flight, Waterbird Conservation Plan, and North American Shorebird Conservation Plan.

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The Lake-McHenry Wetland SHCA falls into two Bird Conservation Regions (BCR). The majority of this SHCA falls in BCR 22, Eastern Tallgrass Prairie. A small portion of the SHCA falls in BCR 23 Prairie Hardwood Transition. Of the 29 species listed as priorities in BCR 22, this SHCA provides benefits to 21 species, including:

• Acadian flycatcher • Greater yellowlegs • Sandhill crane • American bittern • Henslow’s sparrow • Sedge wren • Black rail • Hudsonian godwit • Short-billed dowitcher • Black-billed cuckoo • King rail • Stilt sandpiper • Buff-breasted sandpiper • LeConte’s sparrow • White-rumped sandpiper • Common moorhen • Marbled godwit • Willow flycatcher • Forster’s tern • Marsh wren • Wilson’s phalarope • Grasshopper sparrow • Northern harrier The black tern, which is listed as a priority under BCR 23 and not listed under BCR 22, also occurs within the SCHA. Because this SHCA contains more palustrine emergent wetland acres than any other area of the state, it provides critical breeding and migratory habitat for a variety of marsh birds. American bittern, king rail, common moorhen, Forster’s terns, marsh wren and black tern utilize many of the shallow wetlands and marshes within the SHCA for breeding.

Northern harrier is commonly seen during migration and occasionally has been found breeding. Several shorebirds listed as priorities under BCR 22 and 23 use the SHCA during migration and breeding. Greater yellowlegs, stilt sandpiper, white-rumped sandpiper, buff-breasted sandpiper, short-billed dowitcher, and Wilson’s phalarope will benefit from shallow water wetland restoration activities.

Grassland bird populations in northeastern Illinois have been greatly reduced due to the conversion of the prairie to agriculture. The restoration of tallgrass prairie is a recommended task set forth by Partners In Flight (2000). Two BCR 22/23 priority species that are dependent on grassland communities are found breeding in the SHCA—grasshopper sparrow and Henslow’s sparrow. The protection and restoration of upland habitats in this SHCA will be beneficial to these and other grassland species.

Habitat Types within SHCA Community Assessment the Chicago Wilderness Biodiversity Recovery Plan and The Nature Conservancy Ranking • Fine-Textured-Soil Prairie*—Very High Risk of Loss - Poor Condition • Gravel Prairie* – Very High Risk of Loss – Poor Condition • Streamside Marsh – Very High Risk of Loss – Poor Condition • Graminoid Fen* – Very High Risk of Loss – Poor Condition • Calcareous Seep* – Very High Risk of Loss – Poor Condition • Wet-Mesic Fine-Textured-Soil Savanna* – Very High Risk of Loss – Poor Condition • Calcareous Floating Mat—High Risk of Loss – Fair Condition • Mesic Fine-Textured-Soil Savanna* – High Risk of Loss – Poor Condition • Sedge Meadow* – High Risk of Loss – Fair Condition • Neutral Seep – High Risk of Loss – Fair Condition • Dry-Mesic Woodland* – Moderate Risk of Loss – Fair Condition • Mesic Woodland* – Moderate Risk of Loss – Poor Condition • Wet-Mesic Woodland* – Moderate Risk of Loss – Poor Condition • Dry-Mesic Fine-Textured-Soil Savanna* – Moderate Risk of Loss – Poor Condition • Basin Marsh* – Moderate Risk of Loss – Fair Condition • Bog – Moderate Risk of Loss – Fair Condition • Dry-Mesic Fine-Textured-Soil Savanna* – Moderate Risk of Loss – Poor Condition

(*) These communities base on habitat significance, floristic quality, species richness, numbers of endangered and threatened species, levels of species conservatism and ecological functions have been determined to be of high biological importance in the SHCA. Page 40 of 172

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7.

ECOLOGICAL COMPLEXES

Figure 21. Map of the Greater Yellowstone Ecosystem Complex helps to visualize habitat and migration corridors for plants and animals.

Ecological complexes are based on the same concept as the formation of the Greater Yellowstone Ecosystem Complex, which is a collection of large-scale natural communities that provide habitat and migration corridors for plant and animal species, so that they may survive and reproduce.

Community ecology is the study of a set of species co-occurring at a given time and place. A central aim of community ecology is to understand how communities are organized by identifying, describing, and explaining general patterns that underline the structure of communities. The abundance and distribution of these plant and animal species depend on their interactions with each other and on the quality of their habitat, the size of the habitat, and the connection of core preserves to each other.

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Using a collaborative parcel data analysis and data derived for the GIMS, four ecological complexes have been identified: •

Wisconsin-Illinois Lake Michigan Lake Plain

•

North Central

•

Southern Des Plaines River

•

Lakewood-Moraine Hills

Background and ecological information about the four ecological complexes are provided below. * The parcel data analysis, combined with the other special projects provided detailed information for the selection of these four 10,000-acre ecological complexes in and around Lake County, Illinois. The complexes are located within the SHCA described previously. * Due to the District’s current planning efforts, rules, and regulations, the parcel data analysis cannot be shared publically within this document. The District will be meeting with its partners one-on-one to discuss the ecological complexes.

Wisconsin-Illinois Lake Michigan Lake Plain Ecological Complex

Figure 22. Map of the Wisconsin-Illinois Lake Michigan Lake Plain Ecological Complex.

The Wisconsin-Illinois Lake Michigan Lake Plain ecological complex is one of the most ecologically rich and unique areas in Illinois. The diversity of habitats, created because of its location on the shores of Lake Michigan, supports a wide variety of plants and animals. Significant and unusual topographic features include beaches, ridges and swales, lake bluff, ravines, and dunes. Microclimates along the lakefront range from extremely dry beaches and sand dunes to the moist swales or sloughs between the sand ridges. In this relatively small area, the flora ranges from prickly pear cactus and creeping juniper to wetland plants and wildflowers, such as orchids, wood lilies, gentians, and Indian paintbrushes. Twenty-one significant natural community types occur in this complex, several of which are primary communities—foredunes, beaches, and bluffs— specific to this part of the state. The area is an important part of the Central U.S. migratory route for birds and has been identified as an Important Bird Area by the National Audubon Society.

The complex, located from Kenosha Dunes, Wisconsin south to Waukegan Harbor, Illinois, makes a significant contribution to the notable biodiversity of the Lake Michigan watershed and Great Lakes ecosystem. The southern 986 acres of the proposed project area is within the Waukegan Harbor Area of Concern Extended Study Area. The Lake Plain is recognized for its biological, geological, and ecological significance as a conservation opportunity area by State Wildlife Action Plans (Illinois and Wisconsin), locally as a Chicago Wilderness Conservation Focus Area, as state-dedicated Nature Preserves and Natural Areas, Important Bird Conservation Areas, National Natural Heritage Landmarks and was recently designated as a Ramsar Wetland of International Importance. The more than 4,000 acres of publicly protected coastal dune and swale system connect 21 community types, including globally rare pannes and regionally significant wet prairies, fens, sand savanna, and dry prairie, and provides habitat for over 500 plant and 300 animal species, including 63 state-listed species and four Federally-listed species (eastern prairie fringed orchid, Pitcher’s thistle, Karner blue butterfly [historic record], and piping plover). Equally important, the Lake Plain provides critical stopover habitat for 160 migratory bird species and serves as important breeding habitat for many wetland-dependent bird species. In addition to the biodiversity supported by this region, the Lake Plain provides other critical ecosystem services, including protection of Lake Michigan water quality. Five major tributaries and several minor tributaries flow into and through the Lake Plain prior to reaching Lake Michigan.

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Total SHCA Acres

31,266

Ecosystem Services Value

Percentage Core Habitat

88%

Percentage Corridors/Buffer

12%

Lake Plain Habitat

64%

$ 871,525,992

Aquatic Restoration Potential

21.6%

$ 259,683,890

Prairie Restoration Potential

11.2%

$ 57,457,403

3.2%

$ 848,747,704

$ 2,037,414,989

Wetland Restoration Potential

Within this ecological complex, there is open space that could be restored with the potential for wetland and prairie communities, which dominate this large-scale habitat.

Lake-McHenry Wetland Ecological Complex This complex is a subset of the Illinois Department of Natural Resources’ Lake-McHenry County Wetland Complex Conservation Opportunity Area mentioned previously. It is a large collection of wetlands, which were identified by the Chicago Wilderness Wetland Conservation Strategy as the largest collection of wetland acres in the State of Illinois. Not only are there numerous wetlands, these areas are also diverse in character with large basin marshes, lakes, semipermanent wetlands, fens and bogs that provide habitat for a wide range of wetland and waterfowl birds. There are also large acreages of grasslands that provide habitat for grassland birds.

Within this ecological complex, there is open space that could be restored with the potential for wetland and prairie communities dominating this ecological complex.

Figure 23. Map of the Lake-McHenry Wetland ecological complex.

Total SHCA Acres

88,542

Percentage Core Habitat

82%

Percentage Corridors/Buffer

18%

Ecosystem Services Value

Wetland Restoration Potential

40.5%

$ 973,442,258

Prairie Restoration Potential

37.3%

$ 541,893,331

Aquatic Restoration Potential

12.8%

$ 435,790,973

Savanna Restoration Potential

9.4%

$ 136,562,930

$ 2,087,689,492

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North Central Ecological Complex The North Central Ecological Complex is a collection of Forest Preserves and Illinois Department of Natural Resource owned lands in the Mill Creek and Des Plaines River watershed, which is identified as a focus area in the District’s 100-Year Vision and Strategy. This complex has excellent potential for the restoration of savanna/grassland communities in an area where the Illinois Department of Natural Resources’ Red Wing Slough already provides habitat for waterfowl and savanna/grassland birds.

Restoration of aquatic habitat associated with the Des Plaines River will greatly enhance aquatic biological diversity in the river and greatly improve water quality. Protection of streamside marshes provides habitat for many wetland bird species and other wildlife.

Within this ecological complex, there is open space that could be restored with the potential for wetland, savanna, and prairie communities dominating this large-scale habitat.

Figure 24. Map of the North Central ecological complex.

Total SHCA Acres

62,635

Percentage Core Habitat

68%

Percentage Corridors/Buffer

32%

Ecosystem Services Value

Savanna Restoration Potential

40.7%

$ 418,280,037

Aquatic Restoration Potential

27.3%

$ 657,504,398

Wetland Restoration Potential

23.5%

$ 399,568,081

Prairie Restoration Potential

6.5%

$ 66,801,480

Woodland Restoration Potential

1.2%

$ 1,294,304

$ 1,543,448,300

Figure 25. Map of the Southern Des Plaines River ecological complex.

Southern Des Plaines River Ecological Complex The preservation of Forest Preserves along the Des Plaines River has provided a unique habitat for many plant and animal species. Some of the highest quality woodlands are located along the eastern border of the river valley. The woodlands transition from the floodplain forest close to the river to the mesic woodlands, which contain scattered collections of northern flatwoods. The collection of woodland forest preserves from northern Cook County into Lake County provides a critical regional flyway for forest interior, woodland, and savanna birds. Populations of warblers migrate twice annually through the region in one of the largest migration of birds in the country. Woodland/savanna species, such as red-headed woodpecker, are common in open canopy woodlands and savannas and are recovering with restoration efforts. The northern flatwoods are essential habitat for many amphibian species, which utilize the vernal pools and the surrounding uplands at these preserves for their entire life cycle. Fragmentation, hydrological changes, and mesicification of the flatwoods and woodlands have greatly reduced populations.

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The Des Plaines River is also an important migration route for aquatic organisms and the removal of low-head dams has greatly enhanced this migration of important fish, aquatic invertebrate, and mussel species.

Within this ecological complex, there is open space that could be restored with the potential for wetland and prairie communities dominating this large-scale habitat.

Total SHCA Acres

61,569

Percentage Core Habitat

45%

Percentage Corridors/Buffer

55%

Ecosystem Services Value

Woodland Restoration Potential

44.0%

$ 89,533,640

Wetland Restoration Potential

30.0%

$ 501,405,622

Prairie Restoration Potential

25.9%

$ 261,648,055

$ 852,587,317

The focus of the ecological complexes, as noted earlier, is to provide for a collection of core natural areas that are connected by functioning corridors. For each of the four ecological complexes, the percentage of core areas to corridors/buffer provides a method to determine which conservation efforts need to be applied to ensure that the corridors are functioning as appropriate connections for species populations. This ratio, along with the restoration potential of the remaining open space, provides a blueprint for acquisition, protection, and restoration of lands to form and enhance the ecological complexes.

8.

ECOLOGICAL ENHANCEMENT AREAS

The Strategic Habitat Conservation Area (SHCA) map also identifies four “Enhancement Areas� primarily within Lake County. These four areas, Glacial Lakes (7,890 acres), Central (19,333 acres), South Central (43,672 acres) and West Fork (18,335 acres) are identified as areas where the District and its partners will continue to collaborate and implement ecological management and green infrastructure best management practices.

Due to the level of available of open space in these areas, the primary focus will be to work with communities and partners to implement Community Conservation efforts, which includes providing buffers to natural areas, implementing green infrastructure to encourage infiltration of surface water, improving water quality and expanding natural plant communities into buffer areas, homesteads and stormwater management areas.

Sun Lake and Loon Lake Complex The protection of the Sun Lake and Loon Lakes complex is an action item of the Squaw Creek watershed plan in the Glacial Lake Enhancement Area.

Rollins Savanna and Fourth Lake Complex The protection of the 2,000-acre Rollins Savanna and Fourth Lake complex is critical for wildlife habitat, reduction of flood events, and improvement of water quality in the Central Enhancement Area. Mill Creek Forest Preserve provides the opportunity to restore approximately two miles of Mill Creek which flows through oak bluffs and maintains much of its sinuosity.

Indian Creek Watershed Protection and improvement of the Indian Creek watershed are important to improve water quality within that area, which feeds into the Des Plaines River. Many sections of Indian Creek flow through wetlands or private lands in the South Central Enhancement Area.

West Fork Chicago River The West Fork Enhancement Area has a small portion of Lake County and is highly developed. Green Infrastructure at the community and site level should be implemented to improve water quality.

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9.

GREEN INFRASTRUCTURE MODEL AND STRATEGY Lake County’s Green Infrastructure Model and Strategy (GIMS) uses landscapes as the primary organizing principle. Landscapes are a mosaic of ecosystems or land uses that possess common attributes that are repeated across a large area. Landscapes provide the rationale for deciding which resource attributes or features to include and connect within a green infrastructure network. Based on the 2004 Chicago Wilderness Green Infrastructure Vision (GIV) and Biodiversity Recovery Plan, along with the best available mapping data, four broad categories of landscape types were identified for the study area, as follows: woodland/forests, prairie/grassland/savanna, wetlands, and freshwater aquatic systems (streams and lakes).

Like the second version of the Chicago Wilderness (GIV), the Figure 26. Schematic representing green infrastructure network Lake County GIMS was developed using the core-hub-corridor approach (Figure 26). components

The building blocks of the network are core areas (cores) that contain well-functioning natural ecosystems and provide high-quality habitat for native plants and animals.

Corridors are relatively linear features, linking cores and hubs together and providing essential connectivity for animal, plant, and human movement.

Hubs are aggregations of cores that combine landscape types to treat areas as contiguous blocks that include an array of habitats.

Multiple benefits at multiple scales At its broadest, landscape-scale green infrastructure provides important ecosystem services, such as clean air and water, critical plant and animal species habitat, and wildlife migration corridors, along with compatible working landscapes (Figure 27).

Green infrastructure can provide key recreational areas that link people to natural lands and facilitate the use of transportation modes other than automobiles to reach key community assets.

All of these scales of activity can be linked together and can ensure sustainability in urban, suburban, and rural areas. The network provides a spatial framework for climate adaptation, planning for land conservation efforts, and supports the Chicago Wilderness Climate Action Plan for Nature.

Figure 27. (Left) Schematic representing green infrastructure approach

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The task of defining green infrastructure is not an easy one. Both nationally and regionally, the term has a range of meanings. That range is simplified into three categories: Landscape-based Green Infrastructure This is perhaps the meaning most commonly applied to green infrastructure. It is based on the idea that certain lands have an inherent value that can be made even greater when part of a network. The Conservation Fund defines it as: “Strategically planned and managed networks of natural lands, working landscapes and other open spaces that conserve ecosystem values and functions and provide associated benefits to human populations.”

Under this definition, the foundation of green infrastructure networks is the natural elements—woodlands, wetlands, rivers, and grasslands—that work together as a whole to sustain ecological values and functions. But green infrastructure also can include working lands, trails and other recreational features, and cultural and historic sites.

Biodiversity-based Green Infrastructure In its definition, the Chicago Wilderness GIV adopts another meaning for green infrastructure—one that focuses on the goal of supporting biodiversity. Chicago Wilderness defines green infrastructure as: “The interconnected network of land and water that supports biodiversity and provides habitat for diverse communities of native flora and fauna at the regional scale. It includes large complexes of remnant woodlands, savannas, prairies, wetlands, lakes, stream corridors, and related natural communities. Green infrastructure may also include areas adjacent to and connecting these remnant natural communities that provide both buffers and opportunities for ecosystem restoration.”

This definition reflects both existing green infrastructure—conservation district holdings, state parks, and designated natural areas—as well as opportunities for expansion, restoration, and connection.

Nature-based alternatives to gray infrastructure This definition of green infrastructure focuses on nature-based alternatives to conventional “gray infrastructure” technology and engineering. In this context, green infrastructure is used to describe products, technologies, and practices that use natural systems—or engineered systems that mimic natural processes—to enhance overall environmental quality and provide utility services.

The U.S. Environmental Protection Agency identifies green infrastructure technologies as those that use soils and vegetation for infiltration, evapotranspiration, and/or recycling of stormwater runoff, including techniques such as green roofs, porous pavement, rain gardens, and vegetated swales. In addition to effectively retaining and infiltrating rainfall, these techniques also can filter air pollutants, reduce energy demands, mitigate urban heat islands, and sequester carbon.

This plan integrates each of these meanings into a single comprehensive view of green infrastructure. It encourages not only sustainable land use and open space protection, but also innovative green technology to better protect water and other natural resources.

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Green infrastructure examples While this plan emphasizes large-scale, countywide maps of green infrastructure and trails, it recognizes that implementation of green infrastructure plans and policies should be undertaken at multiple spatial scales by various local governments, agencies, organizations, businesses, and private landowners in order to maximize the benefits. The following are some examples of green infrastructure planning and implementation at different geographic scales and how they relate to the Lake County Regional Framework Plan and Lake County Green Infrastructure Model and Strategy.

At the regional scale, the Chicago Wilderness Green Infrastructure Vision (GIV) provides a regional framework for green infrastructure mapping and planning. Within Lake County, the Green Infrastructure Model and Strategy (GIMS) maps, developed for this plan, exemplify regional scale green infrastructure planning. The US Fish and Wildlife Service has recommended the creation of Strategic Habitat Conservation Areas (SHCA).

Regional green infrastructure implementation can be seen in the significant open space and trail protection work of the Lake County Forest Preserve District (The District), which spans numerous municipalities and townships across the county.

Lake County Stormwater Management Commission watershed plans can be at the regional or community scale. Ultimately, the best way to protect watersheds is to have a common baseline of protections and design standards for all communities in a watershed.

At the Community Scale At the community level, municipalities, park districts, and townships can incorporate green infrastructure principles into their land use, land protection and sustainability plans. The Villages of Lincolnshire, Mettawa, and Bannockburn continue to be at the forefront of planning for green infrastructure and water protection. In 2012, these three communities developed the Green Infrastructure Across Three Communities Plan, which calls for the protection of the watershed, establishes limits on new impervious surface, encourages on-site infiltration, and promotes green infrastructure technologies. The three communities have also adopted their own GIV, which includes a detailed map (Figure 28).

Figure 28. Green infrastructure map of Lincolnshire, Bannockburn, and Mettawa in

Lake County, Illinois that highlights the range of scales for green infrastructure

planning and implementation.

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At the Neighborhood Scale The opportunity for large acquisition and preservation projects can be complicated by high land values, limited availability. Existing development and neighborhoods, both existing and new, can contribute to green infrastructure and conservation values by incorporating conservation design principles. This means the subdivision review process can include open space protection, native landscaping, and stormwater best management practices, which preserve biodiversity and natural resource functions in the design of the neighborhood. Not only does this preserve and enhance the natural environment, it also brings nature closer to families and children. A community conservation approach such as this can expand the connections between people and the environment. Once engaged at the grassroots level, individual landowners can provide enhanced critical connections for green infrastructure.

An example of community conservation is Deerpath Farm (DPF), a conservation development in Mettawa. The 200-acre Deerpath Farm development features 140 acres of protected woods and prairie. DPF is overseen by the homeowners association and is permanently preserved through natural landscape buffers and conservation easements held by the Lake Forest Open Lands Association (LFOLA), which has been involved with the site since 1987 and has managed it since 2005. LFOLA, a leader among national land trusts, pioneered the conservation development concept in the Midwest, beginning in 1988 with the 32-acre West Skokie Nature Preserve, a project that preserved 60% of a natural tract of land integrated along critical green infrastructure corridor. LFOLA has replicated this conservation development technique, preserving nearly 300 acres.

The developer of DPF has been restoring the land since 2000 under the direction of landscape architect Stephen Christy.

This work included restoring the natural hydrology, re-seeding native plants, and removing approximately 100 acres of non-native, invasive buckthorn. LFOLA continues to monitor native species, control invasive species, and conduct controlled burns, using funds provided by homeowner assessments.

Deerpath Farm recently became the first homeowners association in Lake County to be certified by the Conservation@Home program for eco-friendly landscaping and land stewardship. This program, developed and licensed by the Conservation Foundation throughout the Chicago Wilderness region, helps to extend and promote the benefits of community conservation. In Lake County, the Conservation@Home program is currently administered by the non-profit organizations Conserve Lake County and Barrington Area Conservation Trust. In Lake County alone, over 1,000 properties are enrolled in the Conservation@Home program, which features the opportunity for homeowners and property managers to receive individualized recommendations for actionable projects from sustainable landscape professionals.

This is another example of Community Conservation. There are numerous municipalities and non-governmental organizations within Lake County that have programs to encourage Community Conservation by engaging citizens in native landscaping, which also contributes to the health of green infrastructure in the region by extending and linking the function of protected lands into private property.

Results of the Lake County Green Infrastructure Model and Strategy The Lake County Green Infrastructure Model and Strategy (GIMS) was built based on a sequence of geographic information system (GIS) modeling steps to differentiate core areas from other landscape patches, along with the data sources used to implement the modeling methods.

These landscape types are not meant to be mutually exclusive. Inevitably, some important resource lands will meet the criteria and thresholds for more than one core area type. This is acceptable from a methodological standpoint, as well as desirable from a conservation standpoint.

Core areas are combined to create a more holistic network that identifies the “best of the best,� while providing a spatially explicit framework for habitat restoration and enhancement. It also provides the foundation for ecosystem services valuation.

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The Lake County GIMS identifies functional connections that can help link landscape features. The Conservation Fund (The Fund) used the Terrestrial Movement Analysis tool developed in ArcGIS ModelBuilder™ to model landscape connectivity, which is useful to identify and prioritize areas that are important to maintaining wildlife movement and gene flow within a human-modified landscape.

The Lake County GIMS also maps restoration building blocks for each landscape type. Pre-settlement vegetation and soil suitability were the primary data inputs for the woodland/forest, wetland, and prairie/grassland/savanna landscape types. Hydric soils were also used for the freshwater aquatic system landscape type.

The Fund also compiled a list of protected lands and other open space in Lake County, which was used to create composite layers that combine protected lands with a subset of ecological network layers.

Below is a summary of the lands identified in the GIMS. Core Areas

Acres

% County Land

Ecosystem Services Values

Core woodland/forest

8,056

2.7%

$ 26,625,080

Core prairies, grasslands and savannas

12,668

4.2%

$ 207,856,544

Core wetlands

21,796

7.2%

$ 591,674,216

Core lakes and streams

26,589

8.8%

$ 996,542,374

Functional connections

Woodland/forest corridors

17,387

5.8%

$ 57,464,035

Prairie/grassland/savanna corridors

22,599

7.5%

$ 987,187,320

Wetland corridors

18,514

6.1%

$ 711,900,328

Restoration building blocks

Woodland sites

32,343

10.7%

$ 106,893,615

Woodland/forest restoration

25,033

8.3%

$ 82,734,065

Prairie/grassland/savanna restoration

91,078

30.2%

$ 1,494,407,824

Wetland sites

952

0.3%

$ 25,842,992

Wetland complexes

58,745

19.5%

$ 159,551,420

Undeveloped freshwater systems

52,899

17.6%

$ 598,076,094

Figure 29. Area estimates according to the Lake County Green Infrastructure Model and Strategy

Following is a representation of this data, which identifies the potential for prairie/grassland/savanna, wetland, aquatic, and woodland/forest restoration efforts across the study area. The model will allow for finer detail and manipulation of the data to augment the selection of large-scale habitat restoration opportunities in the region. These opportunities may be driven by the District or may be driven by partners, communities, or citizen scientists.

By establishing enduring conservation partnerships that seek shared conservation outcomes, we are positioning ourselves to better leverage resources and support for ensuring landscapes capable of sustaining diverse and sustainable populations of fish, wildlife, and plants.

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Potential restoration opportunities are built upon core preserves within the county and have been identified as core hubs in the maps below.

Lake County Green Infrastructure Model and Strategy

THE

Potential Restoration

C O N S E RVAT I O N F U N D Jerome Creek-Des Plaines River

Channel Lake

£ ¤ 41

North Mill Creek

Bassett Creek-Fox River

Sterling Lake-Des Plaines River

Sequoit Creek

Nippersink Creek Nippersink Lake-Fox River

Waukegan River-Frontal Lake Michigan

Mill Creek

Pistakee Lake-Fox River

Squaw Creek

Bull Creek-Des Plaines River

Lake Michigan

£ ¤ 45

£ ¤

Griswold Lake-Fox River

41

Headwaters Squaw Creek

£ ¤ 12

§ ¦ ¨ 94

Cotton Creek

£ ¤ 45

Indian Creek

Cary Creek-Fox River

Upper North Branch Chicago River

Skokie River

£ ¤ 45

Diversey Harbor-Frontal Lake Michigan McDonald Creek-Des Plaines River

£ ¤ 14

Flint Creek

Wheeling Drainage Ditch

Spring Creek-Fox River

West Fork North Branch Chicago River

§ ¦ ¨ 290

§ ¦ ¨ 294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

12-Digit HUC PGS Restoration

Wetland Restoration Aquatic Restoration Woodland | Forest Restoration

Page 51 of 172

0

4 Miles

Date: 4/25/2016

1:200,000

Ü

Map prepared by The Conservation Fund

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Last revised 8/20/2017

Lake County Green Infrastructure Model and Strategy

THE

Hubs

C O N S E RVAT I O N F U N D

£ ¤ 41

£ ¤ 45

£ ¤ 41

£ ¤ 12

§ ¦ ¨ 94

£ ¤ 45

£ ¤ 45

£ ¤ 14

§ ¦ ¨ 290

§ ¦ ¨ 294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

0

4 Miles

Date: 4/25/2016

1:200,000

Ü

Map prepared by The Conservation Fund

Lakes

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Hubs

CW GIV v2 Composite

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Last revised 8/20/2017

10. LARGE-SCALE HABITAT OPPORTUNITIES Another objective of the GIMS is to identify large-scale wildlife habitat restoration opportunities in the study area.

Following is a depiction and discussion of these opportunities.

Lake County Illinois Green Infrastructure Strategy

THE

C O N S E RVAT I O N F U N D

41 £ ¤

41 £ ¤

45 £ ¤

§ ¦ ¨ 94

45 £ ¤

12 £ ¤

45 £ ¤

§ ¦ ¨ 94

14 £ ¤

§ ¦ ¨ 290

PRT = Potential Restoration Targets

Lakes PRT Grasslands

Page 53 of 172

PRT Wetlands

PRT Woodlands

PRT Aquatic

CW GIV v2 Composite

§ ¦ ¨ 294

0

4 Miles

Date: 1/13/2016 Map prepared by Will Allen

Ü£¤ 41

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Data & Maps.

Copyright: ©2013Fund, Esri,ESRI DeLorme, NAVTEQ

Last revised 8/20/2017

Large-scale Habitat Opportunities—Woodland

Lake County Green Infrastructure Model and Strategy

THE

Woodland | Forest

C O N S E RVAT I O N F U N D

£ ¤ 41

£ ¤ 45

£ ¤ 41

£ ¤ 12

§ ¦ ¨ 94

£ ¤ 45

£ ¤ 45

£ ¤ 14

§ ¦ ¨ 290

§ ¦ ¨ 294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

Lakes

Woodland | Forest Sites

Woodland | Forest Cores

Woodland | Forest Corridors Woodland | Forest Restoration

0

Date: 4/25/2016

4 Miles

1:200,000

Ü

Map prepared by The Conservation Fund

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Page 54 of 172

Last revised 8/23/2017

Woodland/Forest Restoration Opportunities The Lake County Green Infrastructure Model and Strategy (GIMS) documents a large collection of existing woodland communities noted as Woodland Forest Cores and Woodland Forest Sites along the southern Des Plaines River corridor.

Efforts to expand and provide buffers to these areas are critical for the long-term sustainability of these woodland communities for the unique flora and fauna associated with them.

Additionally, the GIMS identified a large area of potential woodland/forest restoration opportunities along the Des Plaines River valley and along the Lake Michigan coastal zone (as seen in the map on page 54). Both areas would likely require enhancement through Community Conservation, some of which is currently being implemented. The Chicago Wilderness Oak Ecosystems Recovery Plan in conjunction with the Chicago Regional Tree Initiative should guide restoration efforts.

Two other areas represent opportunities to provide restoration potential for large-scale woodlands. The first is located in the North Central Ecological Complex and would build on the existing 230-acre woodland/forest located in Ethel’s Woods Forest Preserve. Potential restoration to the east of the woods could expand this woodland community by 200500 acres. The second opportunity is located within the Lakewood-Moraine Hills Ecological Complex, where there exists the opportunity of compiling a 1,300-acre woodland complex associated with the southern portion of Lakewood Forest Preserve. Much of this habitat is identified as savanna and woodland community by the GIMS. Additional acreage to this large-scale woodland habitat is located north of Route 176 in Lakewood Forest Preserve and would be more open savanna than woodland. Much of the savanna restoration has been started with the restoration of the McLean Nature Preserve and Broberg Marsh.

Additional opportunities exist throughout the county and will be addressed by the District’s reforestation program and collaboration with local partners and conservation organizations to implement Community Conservation efforts.

There are an estimated 25,000 woodland/forest acres that could be restored in Lake County.

Page 55 of 172

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Large-scale Habitat Opportunities —Prairie/Grassland/Savanna

Lake County Green Infrastructure Model and Strategy

THE

Prairie | Grassland | Savanna

C O N S E RVAT I O N F U N D

£ ¤ 41

£ ¤ 45

£ ¤ 41

£ ¤ 12

§ ¦ ¨ 94

£ ¤ 45

£ ¤ 45

£ ¤ 14

§ ¦ ¨

§ ¦ ¨

290

294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

0

Lakes

Core Prairie | Grassland | Savanna

Historic Oaks

PGS Corridors

Page 56 of 172

Pre-Settlement PGS

4 Miles

Date: 4/25/2016

1:200,000

Ü

Map prepared by The Conservation Fund

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Last revised 8/20/2017

Prairie/Grassland/Savanna Restoration Opportunities The opportunity to restore large-scale prairie/grassland/savanna habitat is rather well defined by GIMS with the primary areas being associated with the North Central and Lake-McHenry Wetland Strategic Habitat Conservation Areas (SHCA).

Additional support is provided by the National Audubon’s Grassland Bird Assessment Study, which highlights these two conservation areas as having the potential to provide grassland bird habitat.

For grassland bird communities, at least 500 acres are needed to support a full community of birds. Large grassland sites of 1,000–3,000 acres are needed for area-sensitive species, such as northern harriers and upland sandpipers. These larger grasslands are needed to act as anchors for the grassland bird community regionally.

Prairie reptiles and amphibians need a meta-population structure and require a minimum of 200 acres to maintain their populations. To increase their populations, larger preserves of 500–1,000 acres should be established to encourage breeding rates that can provide for migration.

The northern portion of Lakewood Forest Preserve and a portion of Ray Lake Forest Preserve provide an excellent opportunity for a large-scale (2,300 acres) prairie/grassland habitat, which could be expanded to additional surrounding acres. The North Central SHCA can create a large-scale (5,000 acres) prairie/grassland habitat complex that would provide a diverse mix of wet, wet-mesic, and mesic prairie habitats associated with the Illinois Department of Natural Resource Red Wing Slough Land and Water Reserve, Prairie Stream and Pine Dunes Forest Preserves.

There are an estimated 23,000 prairie/savanna/grassland acres that could be restored in Lake County.

Page 57 of 172

Last revised 8/20/2017

Large-scale Habitat Opportunities—Wetlands

Lake County Green Infrastructure Model and Strategy

THE

Wetlands

C O N S E RVAT I O N F U N D

£ ¤ 41

£ ¤ 45

£ ¤ 41

£ ¤ 12

§ ¦ ¨ 94

£ ¤ 45

£ ¤ 45

£ ¤ 14

§ ¦ ¨ 290

§ ¦ ¨ 294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

0

Lakes

Core Wetlands

Wetland Corridors

Wetland Sites

Wetland Complexes

4 Miles

Date: 4/25/2016

1:200,000

Ü

Map prepared by The Conservation Fund

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Page 58 of 172

Last revised 8/23/2017

Wetland Restoration Opportunities Wetlands provide recreation, flood control, and pollution reduction as well as vital food and habitat for plants and animals. The combination of low water levels and high nutrients help provide an abundance of food for a variety of organisms. This enriched ecosystem feeds many small animals such as aquatic insects, shellfish, and small fish, some of which then are food for larger predatory fish, reptiles, amphibians, birds, and mammals. About 35% of threatened and endangered species in the nation depend on wetlands in some way. While wetlands are some of the most important resources we have, they are also some of the most endangered. Illinois has lost more than 85% of its wetlands since the time of non-native settlement. Wetlands are threatened by development, pollution, and exploitation. It is imperative that we preserve, protect and restore remaining wetlands.

In Lake County, the Illinois Natural History Survey estimates that there are 31,260 acres of wetlands, which represent the largest concentrations of wetlands in northeastern Illinois. Of those acres, there are 8,800 acres of basin marshes, 8,700 acres of sedge meadow, and 8,880 acres of shallow marsh. This diversity of wetland types is critical for a large number of plant and animal species.

The GIMS identifies four areas of excellent wetland complexes in Lake County. They are associated with the WisconsinIllinois Lake Plain Complex and the coastal wetlands of Lake Michigan, streamside marshes along the Upper Des Plaines River in the North Central Ecological Complex. Wetlands associated with the Chain O’ Lakes SHCA and the wetland complex located in the Lake-McHenry Wetland Ecological Complex. The latter was identified by the Chicago Wilderness Wetland Conservation Strategy as having the largest concentration of wetlands in the region.

Wetlands associated with the Wisconsin-Illinois Lake Michigan lake plain should be protected and enhanced through the restoration and management of watershed buffers draining into the lake plain. This is a large existing wetland complex that provides significant habitat for a diverse collection of species, and should continue to be a priority for the partners currently working on the complex.

The wetlands associated with the Upper Des Plaines River Valley total 3,450 acres mostly as streamside marshes and sedge meadows. Much of this land is currently protected but needs restoration, especially the streamside marshes.

Current planning efforts are focusing on the condition of the Des Plaines River watershed. Listed as an Illinois EPA 303d stream for poor water quality, the Des Plaines River should be a focus of community partners to increase infiltration, reduce flooding, improve water quality and restore the natural vegetation within the streamside marshes.

The Chain O’ Lakes SHCA is a large collection of glacial lakes and wetlands. Some of the lakes, Cedar, Deep, Sun, Loon lakes are high-quality lakes harboring state listed species. Other lakes in the SHCA and the Glacial Lakes Enhancement Area, especially those connected to the Fox River are negatively impacted by sediment inputs from the surrounding watershed. Efforts to reduce sediment inputs would greatly enhance these lakes and the surrounding wetlands. Most of the SHCA is highly developed with lake homes and the potential for increased wetland protection is limited.

The final area identified by the GIMS as having significant wetland resources is the Lake-McHenry Wetland SHCA. This SHCA includes Illinois Department of Natural Resources Moraine Hills State Park and Black Crown Marsh, Singing Hills, Kettle Grove, Lakewood and Ray Lake Forest Preserves. Each one of these core wetland areas is identified as an Illinois Natural Areas Inventory (INAI) site for natural communities and associated plants and animals. Most of these INAI sites are documented as wetland preserves. This complex of wetland preserves provides critical habitat for a wide variety of wetland species and serves as a core habitat for surrounding wetlands. In addition to the recently acquired northern portion of Ray Lake Forest Preserve, there are two other large blocks of land, totaling 2,500 acres that are currently undeveloped and would provide significant acres for large wetland habitat. Totaling these acres with currently preserved land could provide for a 10,000-acre wetland complex of deep marshes, shallow marshes, sedge meadows and temporary wetlands that would provide habitat for a diverse collection of waterfowl, wetland-dependent birds, and shorebirds. This would be critical wetland complex that would provide both breeding and stopover habitat. In addition, restoration of wetlands acres would reduce flooding, increase infiltration and improve water quality.

There are an estimated 59,000 acres that could be restored to wetland habitat in Lake County.

Page 59 of 172

Last revised 8/20/2017

Freshwater Restoration Opportunities

Lake County Green Infrastructure Model and Strategy

THE

Freshwater Systems

C O N S E RVAT I O N F U N D Jerome Creek-Des Plaines River

Channel Lake

£ ¤ 41

North Mill Creek

Bassett Creek-Fox River

Sterling Lake-Des Plaines River

Sequoit Creek

Nippersink Creek Nippersink Lake-Fox River

Waukegan River-Frontal Lake Michigan

Mill Creek

Pistakee Lake-Fox River

Squaw Creek

Bull Creek-Des Plaines River

Lake Michigan

£ ¤ 45

£ ¤

Griswold Lake-Fox River

41

Headwaters Squaw Creek

£ ¤ 12

§ ¦ ¨ 94

Cotton Creek

£ ¤ 45

Indian Creek

Cary Creek-Fox River

Upper North Branch Chicago River

Skokie River

£ ¤ 45

Diversey Harbor-Frontal Lake Michigan McDonald Creek-Des Plaines River

£ ¤ 14

Flint Creek

Spring Creek-Fox River

Wheeling Drainage Ditch

West Fork North Branch Chicago River

§ ¦ ¨ 290

§ ¦ ¨ 294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

12-Digit HUC Core Lakes and Streams Undeveloped Freshwater Systems

Page 60 of 172

0

4 Miles

Date: 4/25/2016

1:200,000

Ü

Map prepared by The Conservation Fund

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Last revised 8/20/2017

Freshwater Restoration Opportunities The GIMS illustrates that there are significant freshwater resources in Lake County. There are four types of freshwater systems noted in the study region. First, there are an abundance of natural and artificial lakes. There are several highquality lakes that are mostly located in the northwest part of the study area associated with the Fox River and the Chain O' Lakes. There are 176 lakes (over six acres) in Lake County, There are abundant streams in Lake County associated with four primary watersheds: Fox River, Des Plaines River, the three forks of the Chicago River, and Lake Michigan watersheds. Within these watersheds, there are 26 subwatersheds with approximately 30 named streams in and around Lake County. In 2006, the Illinois Department of Natural Resources identified the following streams as either biologically significant or having significant stream integrity: Spring Creek, Flint Creek, Nippersink Creek, Bull Creek, portions of Squaw Creek, Upper Fox above the Chain O' Lakes, and the Upper Des Plaines north of Wadsworth Savanna. While this is critical information, the GIMS identified streams as lacking data for most of the streams in Lake County. Stream monitoring is primarily done by the Illinois Department of Natural Resources and is limited to the rivers and tributaries very near the mouth. More information would be useful for an accurate assessment of stream resources.

The third freshwater system is the numerous ravines along Lake Michigan. They are scattered along the Lake Michigan coastline from where the Highland Park moraine starts in Wilmette, Illinois and north into Wisconsin. There are 47 ravines within the Lake Michigan Coastal Management Zone. All of these were assessed in 2009 by the Lake Michigan Watershed Ecosystem Partnership through a strategic sub watershed identification process to collect baseline data and prioritize where restoration actions should take place in order to achieve the greatest environmental and economic impacts. This table identifies the top qualifying ravines, although restoration of any ravine is a critical priority:

Figure 30. Habitat scores of subwatersheds.

The fourth freshwater resource is the Lake Michigan Lake Plain in northern Lake County and southern Wisconsin. A good portion of this landscape is protected as the Illinois Beach State Park. Chiwaukee Prairie, Spring Bluff Forest Preserve Complex, and Hosah Prairie provide further protection of a freshwater ecosystem that has been designated as a Ramsar Wetland of International Importance. The lake plain is dominated by the swell and swale topography that is the former floor of the Lake Michigan glacial lake, which has been flattened by wave erosion and by minor depressions in low areas.

The low depressions provide unique freshwater wetland habitats including marshes, wet prairies and pannes, which are critical habitat for Lake Michigan plant and animals.

The restoration opportunities are focused on these four types of freshwater resources. Stream priorities are important in the Fox River Hill and Fen SHCA where two good quality streams exist. Spring Creek which is just southwest of Lake County is an undammed stream that has excellent potential for restoration. The Forest Preserve District of Cook County owns a major portion of the watershed at the Spring Creek Forest Preserve. A priority for this watershed is the restoration of the stream habitat along with the fens that are scattered along the streamside. The numerous fens provide habitat for some unique plant and animal species, one of which is listed as a Federally endangered species.

Page 61 of 172

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Figure 31. A Function-Based Framework for Stream Assessments & Restoration Projects EPA 843-K-12-006, May 2012

Adjacent to the Spring Creek watershed, Flint Creek has three forks, which drain a major portion of the Fox River Hill and Fen SHCA, and contains one remaining dam structure. Protection and restoration of this watershed would provide significant benefits to the protected lands that form the core habitat areas.

Fish and mussel habitat should be a priority restoration feature for both Spring and Flint Creeks. Increasing infiltration and restoring wetland features within these watersheds should be a regional priority.

Other stream opportunities should be focused on the other streams/rivers identified by the Illinois Department of Natural Resources’ Biological Stream Characterization including Bull Creek and Bulls Brook, Nippersink Creek, Squaw Creek, the Upper Fox River and the Upper Des Plaines River.

The ownership of most of the lakes in the study area is mostly complete, with an abundance of homes surrounding the lakes. Restoration for many of the lakes in the Chain O' Lakes SHCA should focus on sediment management, controlling invasive species, and balancing recreational needs with current natural resources. The Chain O' Lakes managed by the Fox Waterway Agency expends significant dollars managing sediment within the lakes. A focus should be on managing the inputs into the lake systems by conservation practices on agricultural lands up stream, increasing infiltration and reducing flooding.

Page 62 of 172

Last revised 8/20/2017

Ravine restoration along Lake Michigan has become a priority in the last 10 years thanks to efforts by the Alliance for the Great Lakes, Illinois Department of Natural Resources Lake Michigan Watershed Ecosystem Partnership and, more recently, the Coastal Management Program. A strategic sub-watershed identification process (SSIP) was conducted, which identified the physical condition of the ravines and highlighted erosion issues and ravine stability. It ranked the 47 ravines within the Coastal Management Zone. Of great need is a biological assessment of the ravines to provide further focus to restoration efforts. Several projects have been implemented using Great Lakes Restoration Initiative funds, and further projects should focus on the priorities identified in the SSIP since funding is likely to be available until 2021.

The last freshwater resource is associated with the Lake Michigan Lake Plain and is of such critical importance that the Ramsar Convention designated it as a Wetland of International Importance. There is a coalition of agencies and citizen groups that have been very active in this SHCA and Ecological Complex, investigating Lake Michigan dynamics of coastal erosion, investigating reuse of brownfields, implementing invasive species control, restoring historical hydrology, restoring streams coming into the Lake Plain and managing rare plant and animal species. Future priorities should focus on protecting the coastline of Illinois Beach State Park, to protect the unique plant and animal communities found there.

Because of this unique resource, this is the highest priority for the study area. The biodiversity being lost on an annual basis is unsustainable and significant.

Efforts to work with the local community to implement Community Conservation is important to establish buffers to this Ecological Complex, and to investigate local and site green infrastructure processes that would greatly enhance this freshwater resource. Working with the local communities to investigate the opportunities to recycle and reuse brownfields within this area would provide significant protection to this globally important resource.

There are approximately 53,000 acres of potential freshwater systems that can be restored in Lake County.

11. ECOSYSTEM SERVICE VALUATION Ecosystem services are the collective benefits from an array of resources and processes that are supplied by nature.

Forests, wetlands, prairies, water bodies, and other natural ecosystems support human existence. Only recently has it become possible to quantify and reliably estimate the contributions that green infrastructure makes to human wellbeing and to measure the benefits that nature provides us—for free.

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The Lake County Green Infrastructure Model and Strategy (GIMS) builds on the 2014 efforts of The Conservation Fund (the Fund) to support the Chicago Metropolitan Agency for Planning (CMAP) in assessing ecosystem service valuation in Lake and six other Illinois counties in its planning area.

The Northwest Indiana Regional Planning Council (NIRPC) completed ecosystem service valuation for its three-county service area in 2014 with the support of the Fund. The Chicago Wilderness Green Infrastructure Vision (GIV) 2.3 Ecosystem Service Valuation projects for CMAP and NIRPC demonstrated that estimating the monetized social benefit of conservation in comparison with the investments required to protect land is a scientifically valid and valuable product. It leads to increased awareness by decision-makers and the public regarding the importance and contribution of green infrastructure to quality of life, as well as a greater understanding of the relationship between the built environment and ecological capital in the region.

As some ecosystem services do not have established markets, it is challenging to make estimates without providing detailed information on a variety of assumptions and caveats. The estimates developed for this project are estimates only. These estimates only reflect a portion of the economic benefits of ecological capital. We have provided aggregate estimates over larger areas since they are more reliable than parcel-level estimates. Even if the estimates change over the time, the key message is that a Lake County green infrastructure network has economic benefits, which can be measured and leveraged in land use planning and decision-making. It is also important to note that the Lake County green infrastructure network is a land-based network and does not take into account the ecosystem services provided

by Lake Michigan. The shoreline, nearshore submerged habitat, and the lake itself also have abundant ecosystem service values for recreation and ecotourism.

The final deliverables for the Lake County Ecosystem Service Valuation are based on the Chicago Wilderness GIV 2.3 projects for CMAP and NIRPC. These include an extensive literature review of ecosystem services, as well as geographic information system (GIS) layers and models that facilitate ecosystem service valuation, to be updated over time as new data and scientific literature become available. The development of the literature review and GIS layers was initially guided by feedback and input from a technical committee and participants of a half-day workshop held on August 18, 2014, during the CMAP project. The workshop attendees consisted of Chicago Wilderness members and other key stakeholders in the CMAP region, including representatives from Lake County. Below are brief summaries of why these ecosystem services are important to evaluate and measure in Lake County.

General Factors across the Chicago Region: •

Balmford et al. (2002) found that if the values of ecological services are considered, the benefits from conserving natural land gives a return on investment of at least 100 to 1.

•

Natural ecosystems contribute at least $2 billion per year in economic value to the six-county area around the City of Chicago.

•

$60 million (3% of the Chicago region total) in economic value provided by natural ecosystem is lost annually due to land use change.

Ecosystem Service

Water Flow Regulation / Flood Control Water Purification Groundwater Recharge Carbon Storage

Description Maintain water flow stability and protect areas against flooding (i.e. from storms).

Maintain water quality sufficient for human consumption, recreational use, and aquatic life.

Maintain natural rates of groundwater recharge and aquifer replenishment.

Sequester carbon in vegetation and soils, thereby reducing atmospheric CO2.

Figure 32. Ecosystem services that have been mapped for the Lake County Green Infrastructure Model and Strategy

Page 64 of 172

Last revised 8/20/2017

The technical committee also provided a literature review for additional services that were not mapped, as well as a county specific analysis for the economic values of recreation lands.

Ecosystem Service Air Purification Native Flora & Fauna Recreation and Ecotourism

Description Remove particulates and other pollutants from the air.

Maintain species diversity and biomass to ensure habitat resilience.

Provide opportunities for outdoor, nature-based experiences.

Figure 33. Ecosystem services that have been researched for the Lake County Green Infrastructure Model and Strategy

LANDSCAPE TYPE ECOSYSTEM SERVICE

ALL NUMBERS IN

WOODLANDS / PRAIRIE /

$2014/ACRE/YEAR. FOREST

WETLANDS

GRASSLAND /

NATURAL

LAKES

FLOODPLAINS

SAVANNA

Water Flow Regulation/ Flood control

Selected

$1,603

$16,000

$22,000

$6,500

$37,000

Median

$1,415

$16,000

$4,900

$3,700

$43,000

Water Purification

Selected

$1,300

$57

$4,350

$2,500

$0

Median

$1,060

$57

$3,429

$2,500

$0

Selected

$269

$269

$660

$4,806

$566

Median

$269

$269

$2,479

$4,806

$566

Selected

USED SPATIALLY EXPLICIT DATA FROM NBCD + gSSURGO

Median

$133

Groundwater Recharge Carbon Storage

$82

$136

$0

Figure 34. Ecosystem service valuation estimates used on the maps.

More detailed analysis of the ecosystem services evaluation is contained in Section 4.3 on page 92.

Page 65 of 172

Last revised 8/20/2017

Water Flow Regulation/Flood Control Natural systems are the least costly and most efficient way to control flooding. This is particularly important for local governments who have ongoing concerns about the cost to maintain infrastructure and to comply with stormwater management regulations. More frequent and intense storm events due to climate variability will result in more stormwater and higher peak discharges. This can result in increased sediment and pollutant runoff as well as increased sanitary/combined sewer back-ups that can contaminate drinking water sources and create public health hazards.

One way the Lake County green infrastructure network provides flood control and water flow regulation is through reductions in peak discharges of stormwater flows. Maintaining green infrastructure helps ensure that water can infiltrate into the soil and recharge the groundwater rather than enter the sewer and stormwater systems. This reduces flood damage to community infrastructure, and damage to natural hydrology that could result in a loss of native vegetation and loss of wildlife habitat.

Flooding has significant economic and social costs. Investment in green infrastructure helps avoid some of these costs to repair and replace gray infrastructure, and helps reduce private property losses and damages. In addition to being a cost-effective means of mitigating flooding and stormwater impacts, green infrastructure provides many other benefits, such as recreation and wildlife habitat, not provided by single-purpose engineered systems.

Fortunately, the green infrastructure network contains many of the naturally interconnected wetlands and riparian zones that provide this ecosystem service. Existing natural systems cannot manage all of the flood control needs of communities, but the protection of green infrastructure helps avoid the problem getting worse in locations where the green infrastructure network absorbs flood waters before entering engineered flood control infrastructure. Restoration can help improve it.

Summary Points •

A large tree can reduce 5,400 gallons of stormwater runoff per year.

•

A forest stand can intercept over 200,000 gallons per acre per year.

•

An acre of forest provides an annual avoided stormwater treatment cost of $21 per acre per year, and over $9,000 per acre per year in avoided gray infrastructure investment costs.

•

An acre of wetland typically stores 1–1.5 million gallons of floodwater.

•

In Wisconsin, watersheds with 30% wetland or lake area had flood peaks 60-80% lower than watersheds with no wetland or lake area.

•

Not building in floodplains in the Chicago metropolitan area could save an average of $900 per acre in flood damages each year.

Page 66 of 172

Last revised 8/20/2017

Action Steps to Maintain and Enhance Water Flow Regulation/Flood Control Programs, Policies, and Projects •

Support protection of high-quality natural systems, large-scale wetland complexes, and floodplain restoration, and restoration of hydrologic systems, particularly in these opportunity areas: o

Undeveloped headwaters

o

Des Plaines River flood-prone areas

o

Fox River flood-prone areas

o

Adjacent counties where there is more undeveloped land

•

Construct wetlands, bioswales, rain gardens, tree planting, permeable pavement, green roof, and gray water storage and reuse systems in existing and new developments to keep rainwater out of storm sewers and minimize flooding.

•

Complete buyouts of flood-prone structures and conversion of these areas to natural floodplain. This has the cumulative effect of reducing future flood losses, reduction of flooding potential upstream and downstream because of the extra storage volume for the stream to use, and increase of natural habitat for wildlife.

•

Support the Center for Neighborhood Technology’s Rain Ready Program.

•

Establish incentive programs and mandates to reduce impervious surfaces and minimize total disturbed land areas on a site.

•

Reduce lawn areas on public and private land, and replace with native plants.

•

Encourage high soil volume design for urban trees along streets, parkways, and boulevards.

•

Plant mostly native systems rather than turf grass along right-of-ways.

•

Develop incentive programs for rain harvesting, on-site infiltration, and onsite stormwater management.

•

Support Forest Preserve Districts to convert publicly owned lands currently in agriculture to restored wetlands where appropriate.

•

Limit/ban development in the floodplain. (Not all urban flooding is related to building in the floodplain, but this is still a policy that would help in certain places.)

•

Adjust regulations to go beyond compliance with stormwater detention, and focus more on hydrologic modification that protects stream channel integrity and reduces offsite runoff (like criteria in place in coastal Georgia, Virginia, and Maryland).

Page 67 of 172

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Lake County Green Infrastructure Model and Strategy

THE

Ecosystem Services - Flood Control

C O N S E RVAT I O N F U N D

£ ¤ 41

£ ¤ 45

£ ¤ 41

£ ¤ 12

§ ¦ ¨ 94

£ ¤ 45

£ ¤ 45

£ ¤ 14

§ ¦ ¨ 290

§ ¦ ¨ 294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

Flood Control US Dollars/Acre 17,000 - 22,000

Page 68 of 172

6,600 - 16,000 1,700 - 6,500 >1,600

0

4 Miles

Date: 4/25/2016

1:200,000

Ü

Map prepared by The Conservation Fund

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Last revised 8/20/2017

Water Purification Clean water is essential to public health and ecosystem health. Natural systems can be an effective way to reduce nonpoint source pollution, sediment, nutrients (i.e. nitrogen, phosphorus), bacteria, and other pollutants from water supplies that provide drinking water and opportunities for fishing and swimming. Natural systems can help avoid the need to invest in or replace expensive, energy intensive gray infrastructure systems that treat water or manage stormwater. Poor water quality has other significant economic impacts, including beach closures due to high bacteria levels, the need for dredging due to sedimentation, and limits on water-based recreational activities. The Lake County green infrastructure network contains many of the wetlands and other natural land that currently provide this ecosystem service.

•

Forested buffers remove up to 21 pounds of nitrogen and 4 pounds of phosphorus per acre per year from upland runoff.

•

Forest buffers reduce up to 98% of nitrogen, phosphorus, sediments, pesticides, pathogens, and other pollutants in surface and groundwater.

•

Wetlands filter 70-90% of nitrogen, 45% of phosphorous, and retain more than 70% of sediment.

•

In a comparison of 11 types of best management practices (BMP) for treating stormwater runoff, constructed wetlands were the most effective for improving water quality

•

Wetlands removed 100% of suspended solids, 99% of nitrate, 100% of zinc, and 100% of petroleum byproducts, and reduced peak flows by 85%. This greatly exceeded the performance of standard retention ponds, and expensive manufactured devices.

•

The average wastewater treatment costs using conventional methods are $4.36 per 1,000 gallons. Through wetlands construction, the cost is only $0.63/1,000 gallons (in 2014 dollars).

•

The cost of restoring and operating wetlands to remove nitrogen and phosphorus can be 50–70% less than the cost of constructing and operating engineered wastewater treatment systems.

•

The value of forest in preventing soil erosion is $151/acre/year.

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Last revised 8/20/2017

Action Steps to Maintain and Enhance Water Purification Programs, Policies, and Projects •

Prioritize program strategies based on whether drinking water supply is coming from groundwater, rivers, or Lake Michigan.

•

Explore dam removal on rivers for water quality improvements and fish passage (e.g. Fox River study group, Des Plaines River)

•

Implement large-scale tributary restoration and wetlands protection.

•

Develop an education program for landowners and land managers on strategies to reduce pollution from their properties.

•

Construct wetlands, bioswales, and rain gardens in urban areas.

•

Re-meander streams and restore natural stream flow in rural areas.

•

Reduce agricultural pollution. (Nutrients travel downstream to the Gulf of Mexico hypoxic zone).

•

Develop incentives for nutrient reduction on agricultural lands, to supplement existing best management practices and USDA cost-share programs.

•

Strengthen standards for nutrient reduction in agricultural and urban runoff.

•

Highlight how protection and enhancement of the GIV can serve as key elements of a compliance strategy that minimizes gray infrastructure investment costs.

•

The Clean Water Act (CWA) and Total Maximum Daily Load (TMDL) program provide the framework to protect water quality through setting specific targets to be attained.

•

Incorporate pollution reduction into municipal Comprehensive Plans

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Lake County Green Infrastructure Model and Strategy

THE

Ecosystem Services - Water Purification

C O N S E RVAT I O N F U N D

£ ¤ 41

£ ¤ 45

£ ¤ 41

£ ¤ 12

§ ¦ ¨ 94

£ ¤ 45

£ ¤ 45

£ ¤ 14

§ ¦ ¨ 290

§ ¦ ¨ 294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

0

Water Purification

1,297 - 4,334 41 - 1,296

Page 71 of 172

4 Miles

US Dollars/acre Date: 4/25/2016

1:200,000

Ü

Map prepared by The Conservation Fund

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Last revised 8/20/2017

Groundwater Recharge Groundwater recharge is a key to adequate water supplies for people and wildlife, particularly in those municipalities that rely on groundwater aquifers for drinking water. Significant costs can be incurred when there is a need to develop, treat, and maintain deeper wells and associated treatment systems. Groundwater helps maintain the natural base flow of rivers and streams. The geology of groundwater infiltration and capture is complex, but one of the keys is minimizing impervious surface, which diverts water into combined sewers and other stormwater management infrastructure before it can soak into the ground. The Lake County green infrastructure network includes the river and stream network, and land that serve as infiltration areas to underground aquifers.

Summary Points •

Groundwater is the earth’s largest accessible store of freshwater (excluding ice sheets and glaciers) and constitutes about 94% of all fresh water.

•

Groundwater serves an important function in the hydrological cycle of storing and subsequently releasing water.

Water discharged from aquifers maintains and sustains river flows, springs, and wetlands. Groundwater systems are tightly connected to surface water resources.

•

Forest soils can store 50% more water than urban land and allow 34% more groundwater recharge.

•

Forested wetlands overlying permeable soil can release up to 100,000 gallons per acre per day of groundwater.

Action Steps to Maintain and Enhance Groundwater Recharge Programs, Policies, and Projects •

Focus groundwater recharge initiatives in the adjacent counties where there are more recharge areas and where adequate water supply is needed for economic development.

•

Implement restoration projects that re-create historical groundwater flow regimes within pre-settlement wet, wet-mesic, and dry restoration areas.

•

Establish education program for landowners and land managers on strategies to infiltrate groundwater on their properties.

•

Increase infiltration in urban areas through strategic reduction of impervious surfaces and diversions of water from stormwater management infrastructure through constructed wetlands, bioswales, and rain gardens.

•

Complete buyouts of flood-prone structures and conversion of these areas to the natural floodplain.

•

Re-meander streams and restore natural stream flow in rural areas.

•

Minimize impervious surfaces within areas with shallow wells and state-designated groundwater recharge zones.

•

Adopt policies to encourage infiltration on private properties.

•

Establish incentive programs and mandates to reduce impervious surfaces and minimize total disturbed land areas on a site.

•

Implement policies to reduce salt on roads and fertilizers on lawns.

•

Reduce turf lawn areas on public and private land, and replace with native plants.

•

Promote high soil volume design for urban trees along streets, parkways, and boulevards.

• •

Create incentive programs for rain harvesting, on-site infiltration, and onsite stormwater management.

Creative incentives where unnecessary impervious surfaces can be removed cost effectively (e.g. old industrial sites, unused parking slots, etc.)

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Lake County Green Infrastructure Model and Strategy

THE

Ecosystem Services - Water Purification

C O N S E RVAT I O N F U N D

£ ¤ 41

£ ¤ 45

£ ¤ 41

£ ¤ 12

§ ¦ ¨ 94

£ ¤ 45

£ ¤ 45

£ ¤ 14

§ ¦ ¨ 290

§ ¦ ¨ 294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

Groundwater Recharge US Dollars/Acre 4,821 - 5,954

Page 73 of 172

649 - 4,820 285 - 648 243 - 284

0

4 Miles

Date: 4/25/2016

1:200,000

Ü

Map prepared by The Conservation Fund

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Last revised 8/20/2017

Carbon Storage The ability for natural systems to capture carbon helps mitigate the emission of greenhouse gasses, such as carbon dioxide (CO2), into the atmosphere and thereby helps reduce future climate change. Carbon is stored above ground in leaves and woody matter, and below ground in roots and the soil. The Lake County green infrastructure network includes natural areas and areas of pre-settlement native vegetation that, for the most part, represent areas where carbon storage is occurring and where new opportunities exist through habitat restoration. Protecting the existing Lake County green infrastructure network also supports climate action plans in the region.

Summary Points • Forests help remove large amounts of CO2 from the air. During photosynthesis, trees convert CO2 into oxygen. Carbon is also stored in the body of the tree, in the soil surrounding its roots, and in debris that falls to the ground. Larger and healthier trees sequester carbon at greater rates.

• A large tree can remove over 1,000 pounds per year of CO2 from the atmosphere.

• A mature oak-hickory forest can contain over 130 tons of carbon per acre.

• Restoring prairie vegetation rebuilds organic matter in the surface soil and sequesters carbon, taking centuries to reach maximum storage potential.

• Remnant prairie at Fermi National Accelerator Laboratory contained around 0.76 kg of carbon per square meter above ground and 13.5 kg per square meter below ground.

Action Steps to Maintain and Enhance Carbon Storage Programs, Policies, and Projects • Implement large-scale restoration of woodlands and prairies, particularly within the 400,000 acres called for in the GO TO 2040 plan • Use iTree to identify suitable locations for large investments in urban tree planting.

• Protect woodlands/forests through land acquisition and conservation easements.

• Expand tree planting programs in schools and communities.

• Convert existing agricultural land in public ownership to woodlands/prairie as appropriate.

• Require mitigation by developers when reducing tree cover and disturbing native vegetation.

• Provide incentives to restore woodlands and prairies on private property.

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Lake County Green Infrastructure Model and Strategy

THE

Ecosystem Services - Carbon Storage

C O N S E RVAT I O N F U N D

£ ¤ 41

£ ¤ 45

£ ¤ 41

£ ¤ 12

§ ¦ ¨ 94

£ ¤ 45

£ ¤ 45

£ ¤ 14

§ ¦ ¨ 290

§ ¦ ¨ 294

Copyright: ©2013 Esri, DeLorme, NAVTEQ

Carbon Sequestration

6 - 11

Tons/Hectare

12 - 34

2-5

Page 75 of 172

35 - 171

0

4 Miles

Date: 4/25/2016

1:200,000

Ü

Map prepared by The Conservation Fund

Data Sources: PADUS USA ( CBIv2), Lake County The Conservation Fund, Esri Data & Maps

Last revised 8/20/2017

Air Purification Forests and urban trees can remove sulfur dioxide (SOx), nitrogen oxide (NOx), ozone (O3), carbon monoxide (CO), and fine particles (PM10) from the air, all of which can be harmful to humans. Mechanisms for trees removing pollutants from the air include absorption through leaf stomata (i.e., pores for gaseous exchange) and interception by leaves. The forest soil is a large and important sink for many air pollutants. This ecosystem service is especially important because of the immediate human health impact.

Summary Points •

Trees provide air quality benefits by absorbing sulfur dioxide (SO2) and nitrogen oxide (NO2), two major components of acid rain. Trees also can trap ozone (O3), carbon monoxide (CO), and particles (PM10) in the air, all of which can be harmful to humans.

•

Based on 2007 data, Nowak et al. (2013) estimated trees in the seven-county Chicago region (including the city of Chicago) removed 18,080 tons of air pollution (CO, NO2, O3, PM10, SO2) per year with an associated value of $157 million (in 2007 dollars).

•

Urban trees reduce energy costs from residential buildings by an estimated $44.0 million annually in the Chicago region and an additional $1.3 million in value per year by reducing carbon emissions from fossil-fuel-based power sources.

•

Case Study o

TREE Benefits

o

An assessment of Chicago’s urban forest in 2009 found: §

Number of trees: 3,585,000

§

Pollution removal: 888 tons/year ($6.4 million/year)

§

Carbon storage: 716,000 tons ($14.8 million)

§

Carbon sequestration: 25,200 tons/year ($521,000/year)

§

Building energy savings: $360,000/year

Action Steps to Maintain and Enhance Air Purification Programs, Policies, and Projects •

Increase the canopy of trees in Lake County by 35%.

•

Increase the density of native shrubs in Lake County by 65%.

•

Increase native plantings to reducing mowing operations, reduce runoff and increase infiltration.

•

Encourage municipalities to create ordinances that increase the use of alternative energy sources.

•

Install permeable pavers to increase infiltration.

•

Expand, preserve, maintain and create natural areas.

•

Protect woodlands/forests through land acquisition and conservation easements.

•

Expand tree planting programs in schools and communities.

•

Convert existing agricultural land in public ownership to woodlands/prairie as appropriate.

•

Require mitigation by developers when reducing tree cover and disturbing native vegetation.

•

Provide incentives to restore woodlands and prairies on private properties.

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Native Flora and Fauna Natural systems provide opportunities for native vegetation and wildlife to thrive, which helps maintain ecosystem functions and processes. A functionally-connected network of natural lands and waters provides benefits that are greater than the sum of its parts.

While native flora and fauna help support other ecosystem services, including pollination, the whole network has value in preserving biodiversity. Fortunately, the Lake County green infrastructure network contains most of the high priority native vegetation and wildlife within the region, which will increase as more areas are restored.

Summary Points •

Ecosystem resistance and resilience to stresses depends on species composition and diversity. Diverse ecosystems are more likely to contain species tolerant to disturbances like flooding, drought, or pests.

•

Biological diversity and genetic information are not easy to translate into dollar terms, but several studies quantified the economic value of habitat, such as wetlands, which have a value up to $14,800 per acre each year (in 2014 dollars).

Action Steps to Maintain and Enhance Native Flora and Fauna Programs, Policies, and Projects •

Initiatives that support ecosystem services protection and enhancement: o

Highlight the Lake County Forest Preserve District commitment to protecting four 10,000-acre complexes in and around Lake County.

o

Implement the Illinois Wildlife Action Plan recommendations for a series of large, protected lands.

o

Expand, preserve, maintain, and create new high-quality natural areas.

o

Control invasive species.

o

Use utility corridors as habitat for pollinators.

o

Establish incentives for private landowners to provide habitat for pollinators and native vegetation.

o

Buffer aquatic resources and riparian corridors.

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Recreation and Ecotourism Natural areas not only provide a list of ecological services, they provide an array of recreational opportunities that contribute to quality of life, including biking, water sports, hunting, fishing, hiking, bird watching, camping, and canoeing.

Summary Points •

In 2011, Illinois residents and non-residents spent $3.8 billion on wildlife-associated recreation. They also spent 13.3 million days and $973 million fishing in Illinois (excluding Lake Michigan).

•

In a 2008 survey, over 97% of Illinois residents thought outdoor recreation areas are important for health and fitness, and almost 94% thought community recreation areas are important for quality of life and promote economic development. Over 80% thought more lands should be acquired for open space and/or for outdoor recreation.

•

Access to open space, parks, and recreation is a top factor used by businesses in choosing a new location.

•

Based on usage estimates the open space in Lake County provides $1,116,287,408/year of total recreation value, Forest Preserve land provided $811,813,622/year and other protected land provided $304,473,786/year.

•

Based on known usage of Lake County Department of Transportation numbers for the McClory, North Shore, and Skokie River Trail systems there was a total recreation value of $36,625,652/year for trail use on these trails.

Per mile estimates were generated from this with a value of $832,000/mile/year. Based on this estimate the Des Plaines River Trail would provide $26,137,391/year in total recreation value, while the Millennium Trail, when completed, will generate $29,134,035/year in total recreation value. For all these regional trails in Lake County, there is an estimate total recreational value of $91,897,078/year.

Action steps to maintain and enhance this service Programs, Policies, and Projects—All the above recommended actions steps

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12. APPENDICES 4.1

ABOUT THE CONSERVATION FUND

The Conservation Fund is a national nonprofit organization dedicated to advancing America's land and water legacy.

From its headquarters in Arlington, Virginia and field offices across the country, the Fund has protected land in all 50 states—over 7 million acres, including almost 50,000 acres in Illinois. The Fund is a nationally recognized, experienced leader in green infrastructure planning and ecosystem services valuation. In Chicago, the Fund played a leadership role in the establishment of the Midewin National Tallgrass Prairie and has supported Chicago Wilderness members over the past 20 years with land conservation financing and loans, wetland mitigation account management, and green infrastructure workshop convening. Since 2011, the Fund has supported the development of the Chicago Wilderness GIV version 2 in partnership with Chicago Wilderness, the Chicago Metropolitan Agency for Planning, and the Northwest Indiana Regional Planning Council.

William L. Allen, III. Vice President, Conservation Planning & Integrated Services Chapel Hill, NC With the Fund over 20 years, Will manages the Fund’s design and delivery of customized planning services including green infrastructure plans, strategic mitigation solutions, ecosystem service and optimization models, data-driven decision support maps and tools, and tactical conservation guidance. Will and his team have received planning and mapping awards from the American Planning Association, American Society of Landscape Architects and Esri, Inc. Will serves as co-editor-in-chief and managing editor of the Journal of Conservation Planning and was a co-founder of the Society for Conservation GIS. Will holds a Bachelor of Arts degree in urban studies from Stanford University and a Masters in Regional Planning from the University of North Carolina-Chapel Hill.

Jazmin Varela Information Manager, Strategic Conservation Planning Chapel Hill, NC Jazmin joined the Fund in 2007 and currently oversees the collection and quality assurance of spatial data. She designs and executes geospatial modeling for green infrastructure networks and ecosystem services. She is a member of Google Earth Trainer Network and a Google Trusted Tester. Jazmin has a Master of Environmental Management and a Certificate in Geospatial Analysis from Duke University and a BS in Geography from Appalachian State University, Boone. NC.

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Ted Weber Science Manager, Strategic Conservation Planning Annapolis, MD Ted is a national expert on green infrastructure science, ecosystem services, water quality maintenance and enhancement, wildlife corridor design, forest condition analysis, and field-based ecological assessments. In recent projects such as Chicago Wilderness Green Infrastructure Vision Ecosystem Service Valuation, the HoustonGalveston Green Infrastructure and Ecosystem Services Assessment and the Cecil County Maryland Green Infrastructure Plan, he helped calculate the financial value of wetlands, prairies, and forest cover for air quality, water quality, water supply, stormwater regulation, and carbon sequestration. Ted collaborates with others to ensure the best available science is used in strategic conservation projects and works on a wide variety of projects. He has worked as an ecologist for over 20 years, primarily in landscape, wetland, forest, wildlife, and systems ecology, as well as ecosystem valuation. He holds an M.S. in Environmental Science (Systems Ecology and Wetlands Ecology programs), a Graduate Certificate in Wetlands, and a B.S. in Physics from the University of Florida. He is a certified forest professional by the state of Maryland, and a member of the Society for Conservation Biology, the International Association for Landscape Ecology, the Freshwater Mollusk Conservation Society, and the Association of State Floodplain Managers.

4.2

TECHNICAL METHODOLOGY 4.2.1

Modeling Environment Settings

Ø Projection: NAD_1983_StatePlane_Illinois_East_FIPS_1201_Feet Ø Processing extent for Model Builder o Top: 647203.525527 o Left: 311010.222809 o Right: 347450.222809 o Bottom: 609183.525527 Ø Set cell size for raster models at 10 meters Ø Area units: hectares 4.2.2 Functional Connectivity Parameters Lake County’s Green Infrastructure Model and Strategy also identifies functional connections that can help link the landscape features. The Fund used the Terrestrial Movement Analysis tool developed in ArcGIS ModelBuilder™ to model landscape connectivity, which is useful to identify and prioritize areas that are important to maintaining wildlife movement and gene flow within a human-modified landscape. The tool treats the landscape as a circulatory system, identifying those pathways most likely to be followed by wildlife. This is done by generating random sets of starting locations (each location corresponding to an individual organism) and then calculating optimal (least cost) paths to all other habitat within the landscape. This process is executed iteratively, with each iteration having a different set of random start locations and corresponding least-cost paths. The tool calculates overall landscape connectivity by summing the least-cost paths from all iterations and then averaging these. This process creates a set of rasters that show pathway usage, the cost of moving through a corridor, and overall landscape movement potential. Below is the list of focal species we used to include as parameters for the analysis tools. A team of Lake County biologists and ecologists concurred with this list in October 2015.

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Patch type

Focal species

Dispersal barriers

Dispersal conduits

Not as suitable but not barriers

Maximum distance (km)

Forest

Southern flying squirrel

Major roads, buildings, open areas

Forest

Other areas with trees

5

Aquatic

Native fish, mudpuppy

Dams lacking a suitable fishway; high waterfalls; upland.

Unpolluted Other perennial natural waterways waterways

Forested wetlands

Blue-spotted salamander, wood frog

Major roads, Moist forest wide rivers, (incl. forested Lake Michigan, wetlands) developed land

Dry forest (e.g., pine) and cleared areas

2-5

Nonforested wetlands (excl. sedge wetlands)

Blanding's turtle, muskrat

Major roads, Floodplains and railroads, wetlands developed land

Undeveloped upland

4-15

Grassland (incl. sedge wetlands)

Purplish Copper, Black dash, Dion skipper, Eyed brown, Broadwinged skipper

Sedge wetlands, fields, and utility Dense forest, (and rail?) ROWs major roads, with vegetationdeveloped land friendly management

Other undeveloped open land

5

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10

Last revised 8/20/2017

4.2.3

Woodlands/Forest

Ø Define cover types: woodlands, upland forest, and floodplain forest (canopy > 50%). Ø Data Sources: landcover_2010_lakecountyil_v10.img: 1 meter canopy cover for Lake County using LIDAR data. The National Flood Hazard Layer (NFHL) published by the Federal Emergency Management Agency (FEMA). Oak Ecosystems present in 2010 in Lake County, IL. Woodlands 1. Extract Canopy Class (Value = 1) => 20 ha 2. Focal Statistics operation filled-in all 10m gaps. This was done to reduce fragmentation of patches where there may be a small canopy gap in the middle of the patch.

3. Raster Calculator operation used to mask all impervious surfaces (imper_mask_nd) 4. Removed edge (50 meters) for interior bird patches 5. Removed all canopy within floodplains 6. Add canopy designated as Oak Woodlands Ecosystems that did not meet the 20 ha threshold 7. Add woodlands below 20 ha threshold that are within Protected Lands (PADUS), IL INAI. IL NPC, FPD, IL Natural Heritage Database Element Occurrences and Audubon Important Bird Areas Uplands 8. Extract canopy cover that is not floodplain forest or woodlands 9. Remove edge 20 meters 10. Extract patches of 10 ha or larger (patches of 20ha were not found) Floodplain/Bottomland Forest 11. Extract all canopy cover inside the 100-year floodplain 12. Extract all patches => 200ha Combine 13. Merge all cores 14. Add 50-meter edge of natural cover around cores for buffer 15. Reclassify to 1 and ND Result = Woodland/Forest Layer 4: Core Woodlands/Forest àPatches > 50 acres + inside pre-settlement forest + < 50 acres with high quality locations.

Result = Woodland/Forest Layer 4a: Core Forest/Woodlands with added edge (Corre_FW)

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Restoration Building Blocks Ø Delineate potential woodlands/forest complexes using documented pre-settlement layer. These are potential restoration and enhancement opportunities for future site scale investigation. Pre-settlement data was obtained from historical land survey records, and plats of Lake County, Illinois (1938-1841) and was developed by the Lake County Forest Preserve District by Alfred Westerman and Jack Novak.

Ø Data Sources: Westerman, Al. Forest Preserve District. Presettlement Vegetation Types of Lake County, IL. Unpublished data.

16. Extract Oak Woodlands and Upland Forest vegetation categories.

17. Removed all impervious surfaces, roads, water and other impervious structures.

Result = Woodland/Forest Layer 6: Pre-settlement Woodlands/Forest (restore_fw)

Functional Connectivity Ø Develop functional woodlands/forest corridors

18. Reclassify high-resolution land cover for woodland movement impedance a. Land cover was resampled from original 1 m using majority filter b. There were erroneous values outside the county boundary. c. Reclassify values based on connectivity modeling in the Greater Baltimore Wilderness study area, comparing corridors delineated using different impedance values. No Data = impassable for focal organisms

2

Description Tree Canopy Grass/Shrub

Impedance value 10 50

3 4 5 6 7 No Data

Bare Soil Water Buildings Roads/Railroads Other Paved Surfaces Outside county

250 250 No Data 1000 1000 No Data

Code 1

19. Reclassify roads for woodland movement impedance - Need to be burned in so they are continuous, without gaps. a. Downloaded detailed road data for Lake County from Illinois Department of Transportation (http://gis.dot.illinois.gov/gist2/) b. Downloaded structure locations for Lake County from Illinois Department of Transportation (http://gis.dot.illinois.gov/gist2/) c. From structures, manually selected bridges that crossed water bodies or ravines and then selected subset within 100 m of National Bridge Inventory points (which is spatially inaccurate). Some of these might be culverts. Manually examined and corrected.

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d. There was no easy way to convert these points to lines or polygons. The land cover seemed to depict bridges as water or vegetated (i.e., not roads). e. Buffer bridge points 30 meters. Better for this exercise to be too large than too small. f. Erase bridge buffers from road lines g. Broke roads into three classes according to their Average Annual Daily Traffic (AADT) and wildlife impacts summarized by Charry and Jones (2009).

Vehicles/Day (AADT) <100 100-10,000

Impact Minor Substantial

Code 6 8

Near complete barrier for most species; 9 avoided by others h. Source: Charry, Barbara, and Jody Jones. 2009. â&#x20AC;&#x153;Traffic Volume as a Primary Road Characteristic Impacting Wildlife: A Tool for Land Use and Transportation Planningâ&#x20AC;?. In Proceedings of the 2009 International Conference on Ecology and Transportation, edited by Paul J. Wagner, Debra Nelson, and Eugene Murray. Center for Transportation and the Environment, North Carolina State University, Raleigh, NC. i. Not all roads had values (i.e., AADT = 0), but these seemed to be local roads or streets, which would not carry a lot of traffic. j. Convert to the grid with value = 6, 8, or 9.

20. Overlay roads over land cover a. Separated by class, so barrier roads will be on top, then major roads, then minor roads (save as grid lc_rd_class) b. Mosaic over land cover (save as grid for_imp_lc_rd) >10,000

Code 1 2

Impedance value 10 50

Description Tree Canopy Grass/Shrub

Bare Soil 250 3 Water 250 4 Buildings No Data 5 Local Roads/Railroads 1000 6 Other Paved Surfaces 1000 7 Roads with substantial impact 5000 8 Major roads that are barriers No Data 9 Outside county No Data No Data c. With the proximity to buildings and roads added in, local roads have an impedance of 3000, and roads with substantial impacts and impedance of 15,000.

21. Identify Interior forest a. Reclassify land cover plus roads (lc_rd_class) to forest/non-forest b. Reclassify distance from forest edge (using grid tree_patches) as follows: Distance from forest Divide edge impedance by: >100 m 3 30-100 m 2 <30 m, or non-forest c. Saved divisor grid as imp_intfor.

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1 Last revised 8/20/2017

22. In core woodland locations, divide impedance by 2 (Save as imp_corefor) 23. Increase impedance near impervious surfaces (methods based on recent modeling in Greater Baltimore Wilderness region) a. Reclassify grid lc_rd_class to buildings, roads, and other paved surfaces = 1, elsewhere = No Data b. Calculate Euclidean distance from impervious surfaces (reclassified impervious mask). c. Reclass distance as follows: Distance from nearest Multiply impervious surface impedance by: <10 m 3 10-30 m 2

24.

25.

26.

27.

28.

>30 m 1 d. Saved divisor grid as near_imp_surf.

Set impedance of offshore water (>30 m from shore) to NoData, so the program does not select woodland corridors across large rivers or lakes. Use water from land cover. Save grid as imp_offshore Add Protected lands a. We used PAD-US (CBI Edition) Version 2, omitted GAP Status 4 (unprotected) and military bases. b. Converted to a Boolean grid (lake_co_padus). The level of protection varied. c. Based on results from past projects, exclude paved surfaces and open water, using grid lc_rd_class.

Only trees, grass/shrubs, and bare earth receive a discount for being within a protected area. d. Reclassify protected undeveloped land = 2; elsewhere = 1. Saved as imp_protect.

Combine a. Divide land cover + roads impedance grid (for_imp_lc_rd) by interior forest impedance (i.e., lower impedance in forest interior), core woodland impedance (i.e., lower impedance in core woodlands), multiply by proximity to impervious surface (i.e., higher impedance <30 m from buildings, roads, and other pavement), divide by offshore water (i.e., no corridors >30 m from shore), and protected land (i.e., lower impedance in undeveloped protected land). b. Set values of 0 to 1. Save as for_imped.

After examining spread of impedance values (28 separate values which ranged between 1-15,000), vary by 15%.

This will mostly retain rank order but vary values ±15%. The greater the variability (e.g., if increased to 25% or 50%), the more often rank order will be violated.

Ran with 15% variance. Tested this value in Greater Baltimore Wilderness region and it was acceptable. Smaller values were not. (Core woodlands (core_woodland) and impedance (for_imped) have same projection, map extent, and cell size (10 m).) a. Parameters i. Maximum movement from start locations = 1,000,000 ii. Minimum pathway threshold = 1 iii. Maximum movement around pathway = 500 iv. Equivalent to 20 m of bare earth or 100 m of grass v. Analysis iterations = 100 vi. Start location % = 1

Result = Woodland/Forest Layer 7: Woodland/Forest Corridors (Corr_wf_bi) 4.2.4

Prairie/Grasslands/Savanna

Ø Define cover types: prairies and grasslands with <10% tree canopy coverage and savanna (10-50% tree canopy).

Savannas include fine-textured soil and sand savannas. Ø Data Sources: IN Natural Heritage Database, WI Natural Heritage Inventory, IL Natural Heritage Database. Grassland Bird Patches (unpublished) Caitlin Jensen (National Audubon Society). IL Natural Areas Inventory (INAI). IL Natural Preserves Conservation (INPC). Plant Communities LC FPD. Page 85 of 172

Last revised 8/20/2017

Prairies 1. Add all known prairie sites from INAI 2. Add all prairie vegetation types from LCFPD plant communities 3. Extract all patches equal or larger than 100 ha

Grasslands 4.

5.

6.

7.

Add all grassland bird patches (Audubon) Add INAI sites coded as grasslands by AES Remove 100-meter edge for grassland dependent birds Extract grassland blocks larger than 10 ha

Savannas 8.

9.

10.

11.

12.

13.

14.

15.

Add all known savanna sites from existing datasets Add all plant communities for savannas Add INAI sites coded as savannas Add IL-GAP landcover savanna classes Extract all savanna block larger than 20 ha Combine all prairies, grasslands and savannas cores Remove impervious surfaces and major roads Retain all patches larger than 10 ha

Result = Core Prairie, Grassland, and Savannas (Core_PGS) Restoration Building Blocks Ø Delineate potential prairie complexes using documented pre-settlement prairie. These are potential restoration and enhancement opportunities for future site scale investigation. Presettlement data was obtained from historical land survey records, and plats of Lake County, Illinois (1938-1841) and was developed by the Lake County Forest Preserve District by Alfred Westerman and Jack Novak.

Ø Data Sources: Westerman, Al. Forest Preserve District. Presettlement Vegetation Types of Lake County, IL. Unpublished data.

16. Extract Prairie and Savanna vegetation categories from presettlement vegetation 17. Use ‘mask’ raster dataset to remove developed land, roads, water and other human-disturbed areas to remove areas likely less suitable for restoration.

18. Removed core prairies, grasslands and savannas

Result = PGS Layer 4: Pre-Settlement Prairie/Grassland

Functional Connectivity Ø Develop functional prairie/grassland/savanna corridors Grassland movement impedance Page 86 of 172

Last revised 8/20/2017

19. Reclassify high-resolution land cover for grassland movement impedance a. Land cover was resampled from original 1 m using majority filter. There were erroneous values outside the county boundary. b. Reclassify values based on connectivity modeling in the Greater Baltimore Wilderness study area, comparing corridors delineated using different impedance values. No Data = impassable for focal organisms

2

Description Tree Canopy Grass/Shrub

Impedance value 1000 20

3 4 5 6 7 No Data

Bare Soil Water Buildings Roads/Railroads Other Paved Surfaces Outside county

250 250 No Data 1000 1000 No Data

Code 1

20. Reclassify roads for grassland movement impedance. Need to be burned in so they are continuous, without gaps. a. Downloaded detailed road data for Lake County from Illinois Department of Transportation (http://gis.dot.illinois.gov/gist2/) b. Downloaded structure locations for Lake County from Illinois Department of Transportation (http://gis.dot.illinois.gov/gist2/) c. From structures, manually selected bridges that crossed water bodies or ravines and then selected subset within 100 m of National Bridge Inventory points (which is spatially inaccurate). Some of these might be culverts. Manually examined and corrected. d. There was no easy way to convert these points to lines or polygons. The land cover seemed to depict bridges as water or vegetated (i.e., not roads). e. Buffer bridge points 30 meters. Better for this exercise to be too large than too small. f. Erase bridge buffers from road lines. g. Broke roads into three classes according to their Average Annual Daily Traffic (AADT) and wildlife impacts summarized by Charry and Jones (2009).

Vehicles/Day (AADT) <100 100-10,000

Impact Minor Substantial

Code 6 8

Near complete barrier for most species; 9 avoided by others h. Source: Charry, Barbara, and Jody Jones. 2009. â&#x20AC;&#x153;Traffic Volume as a Primary Road Characteristic Impacting Wildlife: A Tool for Land Use and Transportation Planningâ&#x20AC;?. In Proceedings of the 2009 International Conference on Ecology and Transportation, edited by Paul J. Wagner, Debra Nelson, and Eugene Murray. Center for Transportation and the Environment, North Carolina State University, Raleigh, NC. i. Not all roads had AADT numbers (i.e., = 0), but these seemed to be local roads or streets, which would not carry a lot of traffic. j. Convert to the grid with value = 6, 8, or 9.

21. Overlay roads over land cover >10,000

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a. Separated by class, so barrier roads will be on top, then major roads, then minor roads (save as grid lc_rd_class) b. Mosaic over land cover (save as grid gra_imp_lc_rd)

Code 1 2

Impedance value 1000 20

Description Tree Canopy Grass/Shrub

Bare Soil 250 3 Water 250 4 Buildings No Data 5 Local Roads/Railroads 1000 6 Other Paved Surfaces 1000 7 Roads with substantial impact 5000 8 Major roads that are barriers No Data 9 Outside county No Data No Data c. With the proximity to buildings and roads added in, local roads have an impedance of 3000, and roads with substantial impacts and impedance of 15,000.

22. GAP vegetation - Overlaid "Rural Grassland" class over aerial photos. Looking at three separate areas, classification errors appeared more common than correct classifications. In these samples, GAP incorrectly classified subdivisions, trees, and a golf course as grassland. It is possible the source imagery was outdated, or perhaps the algorithm was faulty.

23. Add interior grassland a. Reclass land cover plus roads (lc_rd_class) to grass/non-grass b. Reclass distance from grass edge as follows: Divide Distance from grass edge impedance by: >100 m 3 30-100 m 2 <30 m, or non-grassland 1 c. Saved divisor grid as imp_int_grass.

24. Add grassland bird patches a. Convert shapefile grasslands_bird_patches.shp to grid grass_bird b. Divide impedance by 2 25. Add INAI grasslands a. Grassland, savanna, and prairie were identified by AES (grasslands_AES.shp) b. Select GRASS = "yes" c. Convert to grid grass_aes. Divide impedance by 2.

26. Increase impedance near impervious surfaces a. Based on modeling in GBW region b. Reclassify grid lc_rd_class to buildings, roads, and other paved surfaces = 1, elsewhere = No Data c. Calculate Euclidean distance from impervious surfaces (reclassified impervious mask). d. Reclassify distance as follows: Distance from nearest Multiply impervious surface impedance by: <10 m 3 10-30 m 2 >30 m e. Saved divisor grid as near_imp_surf.

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27. Set impedance of offshore water (>30 m from shore) to NoData, so the program does not select grassland corridors across large rivers or lakes. a. Use water from land cover b. Save grid as imp_offshore 28. Add protected lands a. We used PAD-US (CBI Edition) Version 2, omitted GAP Status 4 (unprotected) and military bases. b. Converted to a Boolean grid (lake_co_padus). The level of protection varied. c. Based on results from past projects, exclude paved surfaces and open water, using grid lc_rd_class.

Only trees, grass/shrubs, and bare earth receive a discount for being within a protected area. d. Reclassify protected undeveloped land = 2; elsewhere = 1. Saved as imp_protect.

29. Combine a. Divide land cover + roads impedance grid (gra_imp_lc_rd) by interior grassland impedance (i.e., lower impedance in grassland interior), grassland bird impedance (i.e., lower impedance in grassland bird areas), AES-identified grassland impedance (i.e., lower impedance where AES identified grasslands), offshore water (i.e., no corridors >30 m from shore), and protected land (i.e., lower impedance in undeveloped protected land), and multiply by proximity to impervious surface (i.e., higher impedance <30 m from buildings, roads, and other pavement). b. Set values of 0 to 1. c. Save as grass_imped 30. Grassland connectivity modeling a. After examining spread of impedance values (28 separate values which ranged between 1-15,000), vary by 15%. This will mostly retain rank order but vary values Âą15%. The greater the variability (e.g., if increased to 25% or 50%), the more often rank order will be violated. b. Run with 15% variance i. Core grasslands (core_grassland) and impedance (grass_imped) have same projection, map extent, and cell size (10 m). ii. Maximum movement from start locations = 1,000,000 iii. Minimum pathway threshold = 1 iv. Maximum movement around pathway = 500 v. Analysis iterations = 100 vi. Start location % = 1

Result = PGS Layer 6: Prairie/Grassland/Savanna Corridors (pgs_corr_bi)

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4.2.5

Wetlands

Ø Define cover types: This includes all types of wetlands. Some wetlands might also fall under other categories (e.g., forested wetlands falling under forest as well). Ø Assemble wetland land cover using input from different data sources to create a comprehensive wetland layer. Ø Data Sources: Ducks Unlimited enhanced National Wetland Dataset (NWI) update (IL). Lake County - LCWI (2002) ADID wetlands. Illinois Natural History Survey's 1999-2000 1:100 000 Scale Illinois Gap Analysis Land Cover Classification, Raster Digital Data, Version 2.0, September 2003.

Forested Wetlands 1. Forested Wetlands were obtained from two NWI vector layers converted to 10-meter cell size and IL-GAP landcover down sampled to 10 m cell size 2. Remove all impervious surfaces and roads

Marshes and Emergent Wetlands 3.

4.

5.

6.

Extraction from NWI update and IL-GAP landcover Remove all impervious surfaces and roads

Add all ADID wetlands Create an all wetland composite layer

Water Drawdown 7. Subtract areas of water drawdown by identifying canals and ditches from National Hydrography Dataset (NHD+).

Data source: NHDPlus v.1.

8. From NHD, select ("FTYPE" = 'CanalDitch'). Buffer canals and ditches by 120 meters and artificial paths. Subtract these areas to estimate water drawdown effects 9. Subtract edge effect zone by identifying roads, development, and other human disturbances and land use Buffer these features by 30 m. Subtract from wetlands + adjacent natural cover. Identify those contiguous areas of natural cover that contain wetlands as follows.

10. Divide wetland patches into two datasets, one above an initial size threshold and one below. Initial size threshold for wetlands – 50 acres, which is based upon habitat requirements of wetland-dependent species such as Blanding’s Turtle.

Result = Wetland Layer 2: Wetland Patches > 50 acres (Core_Wet).

Result = Wetland Layer 3: Wetland Patches < 50 acres (wet_sites).

11. Add known high-quality locations of wetlands or occurrences of wetland-dependent species that fall below the established size threshold.

12. Extract all wetland patches from Wetland Layer 3 that are designated Illinois Natural Areas Inventory sites and state natural preserves, reserves, and landmarks.

13. Extract all wetland patches from Wetland Layer 3 that are State and federal threatened and endangered species sites. Ø Data Sources: IN Natural Heritage Database, WI Natural Heritage Inventory, and IL Natural Heritage Database.

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Ă&#x2DC; Data Sources: Westerman, Al. Forest Preserve District. Presettlement Vegetation Types of Lake County, IL. Unpublished data.

Result = Wetland Layer 7: Wetland Complexes (wet_restore)

14. Reclassify high-resolution land cover for wetland movement impedance a. Land cover was resampled from original 1 m using majority filter b. There were erroneous values outside the county boundary. c. Reclassify values based on connectivity modeling in the Greater Baltimore Wilderness study area, comparing corridors delineated using different impedance values. No Data = impassable for focal organisms Code

Description

Impedance value

1

Tree Canopy

10

2

Grass/Shrub

50

3

Bare Soil

250

4

Water

250

5

Buildings

No Data

6

Roads/Railroads

1000

7

Other Paved Surfaces

1000

No Data

Outside county

No Data

15. Reclassify roads for wetland movement impedance. Need to be burned in so they are continuous, without gaps. a. Downloaded detailed road data for Lake County from Illinois Department of Transportation (http://gis.dot.illinois.gov/gist2/) b. Downloaded structure locations for Lake County from Illinois Department of Transportation (http://gis.dot.illinois.gov/gist2/) c. From structures, manually selected bridges that crossed water bodies or ravines and then selected subset within 100 m of National Bridge Inventory points (which is spatially inaccurate). Some of these might be culverts. Manually examined and corrected. d. There was no easy way to convert these points to lines or polygons. The land cover seemed to depict bridges as water or vegetated (i.e., not roads). e. Buffer bridge points 30 meters. Better for this exercise to be too large than too small. f. Erase bridge buffers from road lines g. Broke roads into three classes according to their Average Annual Daily Traffic (AADT) and wildlife impacts summarized by Charry and Jones (2009).

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Vehicles/Day (AADT)

Impact

Code

<100

Minor

6 Last revised 8/20/2017

100-10,000

Substantial

8

>10,000

Near complete barrier for most species; avoided by others

9

a.

Source: Charry, Barbara, and Jody Jones. 2009. â&#x20AC;&#x153;Traffic Volume as a Primary Road Characteristic Impacting Wildlife: A Tool for Land Use and Transportation Planningâ&#x20AC;?. In Proceedings of the 2009 International Conference on Ecology and Transportation, edited by Paul J. Wagner, Debra Nelson, and Eugene Murray. Center for Transportation and the Environment, North Carolina State University, Raleigh, NC. b.

Not all roads had AADT numbers (i.e., = 0), but these seemed to be local roads or streets, which would not carry a lot of traffic. c.

Convert to the grid with value = 6, 8, or 9.

16. Overlay roads over land cover a. Separate by class, so barrier roads will be on top, then major roads, then minor roads (save as grid lc_rd_class) b. Mosaic over land cover (save as grid wet_imp_lc_rd) Code

Description

Impedance value

1

Tree Canopy

10

2

Grass/Shrub

50

3

Bare Soil

250

4

Water

250

5

Buildings

No Data

6

Local Roads/Railroads

1000

7

Other Paved Surfaces

1000

8

Roads with substantial impact

5000

9

Major roads that are barriers

No Data

No Data

Outside county

No Data

c. With the proximity to buildings and roads added in, local roads have an impedance of 3000, and roads with substantial impacts and impedance of 15,000.

17. Add Wetlands a. Compared NWI (IL_NWI_Current_draft_07062011) and the Lake County Wetland Inventory (WetlandInventory_Lake_2002). The LCWI seemed to identify more areas as wetlands ("TYPE2002" = 'W') than NWI and have better resolution. Some areas classified as wetlands by LCWI were ditches along roads. Some wetlands had been farmed, possibly since the inventory was done. These could be restored, presumably. b. We decided to use LCWI since it has a finer resolution and is specific to the county. It includes areas of open water. c. Extract wetlands ("TYPE2002" = 'W') Page 92 of 172

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d. Convert to grid (grd_wetl_10m) with a value of 1, NoData. e. Subtract non-vegetated surfaces (impervious, open water, bare soil; obtained from land cover and roads: lc_rd_class) f. Save as imp_wetland, with a value of 1.

18. Add Hydric soils a. Create boolean grid b. Subtract impervious surfaces and water. c. Use as divisor (divide by 3): Reclassify 0 and No Data to 1, 1 to 3.

19. Increase impedance near impervious surfaces a. b. c. d.

Based on modeling in GBW region Reclassify grid lc_rd_class to buildings, roads, and other paved surfaces = 1, elsewhere = No Data Calculate Euclidean distance from impervious surfaces (reclassified impervious mask).

Reclassify distance as follows: Distance from nearest Multiply impervious surface impedance by: <10 m

3

10-30 m

2

>30 m

1

e. Saved divisor grid as near_imp_surf.

20. Set impedance of offshore water (>30 m from shore) to NoData, so the program does not select wetland corridors across large rivers or lakes. a. Use water from land cover b. Save grid as imp_offshore

21. Add Protected lands a. We used PAD-US (CBI Edition) Version 2, omitted GAP Status 4 (unprotected) and military bases. b. Converted to a Boolean grid (lake_co_padus). The level of protection varied. c. Based on results from past projects, exclude paved surfaces and open water, using grid lc_rd_class.

Only trees, grass/shrubs, and bare earth receive a discount for being within a protected area. d. Reclassify protected undeveloped land = 2; elsewhere = 1. Saved as imp_protect.

22. Combine a. Give wetlands an impedance of 1. b. Elsewhere, divide land cover + roads impedance grid (wet_imp_lc_rd) by hydric soil impedance (i.e., lower impedance where hydric soils), proximity to impervious surface (i.e., higher impedance <30 m from buildings, roads, and other pavement), offshore water (i.e., no corridors >30 m from shore), and protected land (i.e., lower impedance in undeveloped protected land). c. Save as wet_imped.

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a. After examining spread of impedance values (28 separate values which ranged between 1-15,000), vary by 15%. This will mostly retain rank order but vary values ±15%. The greater the variability (e.g., if increased to 25% or 50%), the more often rank order will be violated. b. Run with 0% variance i. Core wetlands (core_wet) and impedance (wet_imped) have same projection, map extent, and cell size (10 m). ii. Maximum movement from start locations = 1,000,000 iii. Minimum pathway threshold = 1 iv. Maximum movement around pathway = 500 v. Equivalent to 20 m of bare earth or 100 m of grass (seems kind of high) vi. Tested this value in Greater Baltimore Wilderness region and it was acceptable. Smaller values were not. vii. Analysis iterations = 50 viii. Start location % = 1

Result = Wetland Layer 8: Wetland Corridor (corr_wet_bi)

Freshwater Aquatic Systems

Ø Define cover types: Natural streams and lakes. Ø Data Sources: U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA) National Hydrography Dataset (NHD) Medium Resolution. Augmenting NHDPlus Strahler order values using Strahler calculator (http://www.horizon-systems.com/nhdplus/NHDPlusV1_download.php). Hydrology Lines of Lake County, Illinois, Hydrology Polygons of Lake County, Illinois, 2004.

1. Chicago Wilderness Wetlands Task Force data on streams associated with reptiles and amphibians. The mean + 1sd (>13.4) was used to get highest scoring regions within 90 meters of a stream or river, IL Biologically Significant Streams 2. Lake Michigan most stable ravines from the Alliance for the Great Lakes 3. Identify streams/lakes from land form NHDPlus and Lake County’s Hydrology lines and polygons 4. Combine and buffer features by 90 meters.

5. Add known high quality and priority locations of streams/lakes by extracting those stream segments and waterbodies running through Illinois Natural Areas Inventory sites, Illinois Nature Preserves Commission (INPC) Illinois Audubon Society Important Bird Areas (IBAs) and Natural Heritage Element Occurrences 6. Incorporate important streams associated with reptiles and amphibians and buffer by 90 meters 7. Confirmed that IL Biologically Significant Streams grades B and C are included.

8. Add high-quality ravines where data is available. Ravines were ranked with 1-5 value with 1 being the worst.

Selected all ravines with a rank >=3. All banks are in need of restoration (highest value is 2).

9. Add freshwater systems.

10. Add DFIRM floodplains 11. Add pre-settlement water areas.

12. Add ravines not included in Streams/Lakes Layer 3 above. These have been identified as being in need of restoration by the Alliance for the Great Lakes.

Result = Streams/Lakes Layer 4: Freshwater Systems (wat_restore) Page 94 of 172

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13. Develop a ‘mask’ raster dataset and remove developed land, roads, and other human-disturbed areas to remove developed areas.

Result = Streams/Lakes layer 5: Undeveloped Freshwater Systems (undevlp_wat)

4.2.6

Protected Lands, Trails, and Hubs

Protected Lands Ø Inventory of all protected and managed lands: parks, conservation easements, etc. Note: Due to the variety of sources, the datasets used have overlaps between them and occasionally have slightly different boundaries.

Nonetheless, the inventory is believed to be current and comprehensive as of November 2012. Ø Data Sources: Protected Areas Database of the US (PAD-US) - CBI Edition 1.1, 2010, National Conservation Easement Database (NCED), Lake County Forest Preserve District, Citizens for Conservation, Conserve Lake County, IL DNR: INAIs and State Parks and Lake Forest Open Lands Association. Ø The open space was divided into three categories: o Public and private conservation lands (this was the layer converted to the protected lands raster layer (Hub Layer 2) o Public lands not coded as open space. A subset of these county/township/village lands is open land where restoration may be suitable, but another subset of these lands has built structures or impervious surface on them. This layer is useful to review at a site scale to identify specific opportunities on public lands. o Private open space that is not protected, mostly HOA and Country Club lands. Note that a subset of these lands includes built structures or impervious surface on them. This layer is useful to review at a site scale to identify specific opportunities on private lands.

Trails Ø Identify regional, county, and local recreation trails and bike paths network. Data included both existing and planned trails. Ø Data sources: Lake County trails data and municipal/village trails data provided by CMAP Ø We used a functional connectivity approach to identify missing trail linkages. We explored an automated GIS workflow for this process but were unable to use least-cost paths to consistently identify these connections.

Instead, we used a desktop GIS approach to identify nodes where trail connections made functional connections and then used aerial photography and parcel data to identify ways to connect the nodes using existing roads/trails. We have delivered a point feature class of trail nodes and functional connectivity links. When overlaid with existing and planned trails, the layers provide enhanced functional connections throughout the county and connected to adjacent counties. Further work needs to be completed in order to assess the feasibility of each of these proposed connections.

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Hubs Hubs are aggregations of core areas that combine landscape types in an effort to treat areas as unfragmented blocks that include an array of habitats. Although it is important to identify discrete landscape types for analytical purposes, blocks with diverse habitat types often serve as high quality ‘matrix’ areas where the whole is greater than the sum of its parts. For the most part, previous hub delineation methods have focused on simply combining core areas and corridors and optionally adding surrounding buffer areas. Given the previous GIV 1.0 efforts and the interest in being able to compare the results of GIV 1.0 with the refinement completed for GIV 2.1, a merging of datasets was found to be the most useful approach.

1. Merge the following datasets: Ø Core Woodlands/Forest Ø Woodland/Forest Corridors Ø Core Prairies, Savannas and Grassland Blocks Ø Core Wetlands Ø Wetland Corridors Ø Core Streams/Lakes Ø Undeveloped Freshwater Systems Result = Hub Layer 1: GIV Ecological Network (hub_ly1) 2. Convert protected lands layer feature classes to raster and merge rasters. The following datasets were used: Data Sources: Protected Areas Database (PADUS), Lake County Parcel Data, Land Trusts Fee and Easements (provided by Lake County Advisory Committee), National Conservation Easement Database (NCED), Forest Preserve Districts, IDNR Managed Lands Result = Hub Layer 2: Protected Lands Raster (hub_ly2) 3. Combine Hub Layer 1, Hub Layer 2, and Streams/Lakes Layer Result = Hub Layer 3: GIV Composite (hub3) (use for comparison with GIV 2.3 to demonstrate refinement)

Network Ranking We used the Chicago Wilderness GIV version 2 characterization models as a starting point for providing ranking and prioritizing options for the Lake County green infrastructure network. The models allow for visualization of the relative priority of conservation actions in the different parts of the network. These were based on the Maryland Green Infrastructure Assessment cell ecological ranking methodology, which was spearheaded by the Fund’s Ted Weber when he worked for the Maryland Department of Natural Resources.

The model is built on a ‘weighted sum’ 0-100 scale for ease of understanding and use, but there is flexibility in design for these models since we expect users to select specific applications for what they would like to rank and prioritize.

Independent of the rankings selected, the models are built so that layers and weights can be dynamically adjusted with some experience using ArcGIS ModelBuilder. The Fund has provided a toolbox based decision support system that has weights and input layers as variables, which can be used ‘out of the box’ by technically proficient users with an ArcGIS license with the Spatial Analyst extension.

Table 1. Lake County Green Infrastructure GIS Data Layers Available for Ranking Page 96 of 172

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GIV Layer Description

GIV Layer Name

Core woodland/forest

Forest_Core

Core prairies, grasslands and savannas

PGS_Core

Core wetlands

Wetland_Core

Core lakes and streams

Water_Core

Woodland/forest corridors

Forest_Corridor

Wetland corridors

Wetland_Corridor

Undeveloped NHD+ stream buffer

Water_UndevlpSystemsBuffer

Undeveloped freshwater systems

Water_UndevlpSystems

GIV landscape features

Functional connections

Restoration building blocks

Woodland sites

Forest_Sites

Pre-settlement woodland/forest

Forest_Restoration

Pre-settlement prairie/grassland/savanna

PGS_Restoration

Wetland sites

Wetland_Sites

Wetland complexes

Wetland_Complexes

NHD+ raster buffer

Water_AllBuffer

Freshwater systems

Water_FreshWaterSystems

Composite layers

GIV ecological network

Hub Layer 1

Protected lands raster

Hub Layer 2

GIV composite

Hub Layer 3

4.3 Ecosystem services literature review

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Below is the initial list of 24 ecosystem services distilled from multiple sources.

Ecosystem Service

Description

REGULATING & SUPPORTING Hazard Amelioration Water Flow Regulation / Flood Control

Maintain water flow stability and protect areas against flooding (e.g., from storms).

Water Purification

Maintain water quality sufficient for human consumption, recreational uses like swimming and fishing, and aquatic life.

Erosion Control and Sediment Retention

Maintain soil and slope stability, and retain soil and sediment on site.

Groundwater Recharge

Maintain natural rates of groundwater recharge and aquifer replenishment

Air Purification

Remove particulates and other pollutants from the air

Climate Microclimate Moderation

Lower ambient and surface air temperature through shading

Regulation of Water Temperature

Moderate water temperature in streams

Carbon Storage

Sequester carbon in vegetation and soils, thereby reducing atmospheric CO2 and global climate change

Biological Native Flora and Fauna

Maintain species diversity and biomass

Pollination

Provide pollinators for crops and other vegetation important to humans

Pest and Disease Control

Provide biota which consumes pests and control diseases

PROVISIONING Food Production

Production of plant or fungal-based food for human consumption

Game and Fish Production

Production of wild game and fish for human consumption

Fiber Production

Production of wood and other natural fibers for human use

Soil Formation

Long-term production of soil and peat for support of vegetation and other uses

Biochemical Production

Provision of biochemicals, natural medicines, pharmaceuticals, etc.

Genetic Information

Genetic resources for medical and other uses, including those not yet realized

CULTURAL Recreation and Ecotourism Page 98 of 172

Outdoor, nature-based experiences like hiking, birding, hunting, camping, etc.

Last revised 8/20/2017

Ecosystem Service

Description

Savings in Community Services

Savings in community services from not converting natural land to houses

Increase in Property Values

Provide attractive location for homes and businesses

Science and Education

The existence of natural systems and areas for school excursions, advancement of scientific knowledge, etc.

Spiritual and Aesthetic

Aesthetic enjoyment or spiritual or religious fulfillment

Bequest value

The value placed on knowing that future generations will have the option to utilize the resource.

Existence value

The non-use value of simply knowing that particular resources exist, even if they are not used.

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ESTIMATING ECOSYSTEM SERVICE VALUES

Farber et al. (2002)1 list six methods for valuing methods for valuing ecosystem services in monetary terms:

• Avoided cost: Services allow society to avoid costs that would have been incurred in the absence of those services (e.g., natural flood control preventing property damages or natural waste treatment preventing health costs) • Replacement cost: Services could be replaced with man-made systems (e.g., natural waste treatment having to be replaced by costly engineered systems) • Factor income: Services provide for the enhancement of incomes (e.g., water quality increasing commercial fisheries catches and fishermen incomes) • Travel cost: Service demand may require travel, whose costs can reflect the implied value of the service (e.g., value of ecotourism or recreation is at least what a visitor is willing to pay to get there) • Hedonic pricing: Service demand may be reflected in the prices people will pay for associated goods (e.g., increase in housing prices due to water views or access to parks) • Contingent valuation: Service demand may be elicited by posing hypothetical scenarios that involve some valuation of alternatives (e.g., how much people are willing to pay for increased availability of fish or wildlife).

Table. Types of analyses available for selected ecosystem services for the Lake County Green Infrastructure Strategy

Ecosystem Service

Water Flow Regulation / Flood Control

Water Purification

Groundwater Recharge Carbon Storage Air Purification Native Flora & Fauna

Metrics Reduction of flood damage, Reduction of stormwater flows, Reduction of peak discharges, Reduction of combined sewer system costs, Reduction of soil erosion Reduction of N, P, Cl-, sediment, bacteria, and other pollutants for drinking water, swimming, fishing, aquatic life, and other uses.

Supply of water to groundwater rather than surface runoff Reduction of atmospheric CO2 and associated climate effects Removal of SOx, NOx, O3, CO, and PM10 from the air Protection of wildlife habitat Maintenance of ecosystem functions and resilience

Types of economic analyses Avoided cost, Replacement cost

Avoided cost, Replacement cost

Avoided cost, Replacement cost, Price of public water supply Avoided cost, Market price of carbon Avoided cost, Replacement cost Willingness to pay (contingent valuation)

1

Farber, S.C., R. Costanza and M.A. Wilson. 2002. Economic and ecological concepts for valuing ecosystem services.

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Ecosystem Service

Recreation and Ecotourism

Types of economic analyses

Metrics Money spent on nature-based recreation (hunting, fishing, birding, hiking, etc.)

Surveys of money expended on nature-based recreation

Table. Ecosystem service valuation estimates used on maps

ECOSYSTEM SERVICE

Prairie / All numbers in Woodlands / Grassland / $2014/acre/year. Forest Savanna

Wetlands

Natural Floodplains Lakes

Selected

$1,603

$16,000

$22,000

$6,500

$37,000

Median

$1,415

$16,000

$4,900

$3,700

$43,000

Selected

$1,300

$57

$4,350

$0

Median

$1,060

$57

$3,429

$0

Selected

$269

$269

$660

$4,806

$566

Water Flow Regulation/ Flood control

Water Purification

Groundwater Recharge

LANDSCAPE TYPE

Median

$269

$269

$2,479

$4,806

Selected

USED SPATIALLY EXPLICIT DATA FROM NBCD + gSSURGO

Median

$133

$566

Carbon Storage

$82

$136

$0

Water Flow Regulation / Flood Control

Detailed Literature Review

Floods caused more fatalities and property damage than any other type of natural disaster in the U.S. during the twentieth century (Kousky et al., 2013). Wet basements decrease property values by 10-25%, and that almost 40% of small businesses never reopen their doors following a flooding disaster (CNT, 2014). Between 2007 and 2011, over 181,000 flood damage claims and sewer- and drain-backup claims were made across 97% of Cook County ZIP codes, totaling $773 million (CNT, 2014). There was no correlation between damage payouts and presence of FEMA floodplains in the ZIP code, but floodplains constituted just 0.3% of the total acreage in Cook County (CNT, 2014).

Forest, wetlands, and prairies can help maintain water flow stability and protect areas against flooding from storms.

LondoĂąo and Ando (2013) found that residents of Champaign and Urbana, Illinois were each, on average, willing to pay around $21/year to reduce basement flooding. The Conservation Fund (2013) grouped flood protection and erosion control because both are services tied to stormwater regulation, and to treat them separately would partially double Page 101 of 172

Last revised 8/20/2017

count them. For example, a basin built to capture stormwater runoff would also capture eroding sediment, although this would not include the negative effects where the soil is lost.

Woodlands/Forest Forest

Forests perform an important service by reducing downstream flooding through their ability to percolate stormwater (HGAC, 2010). Aerial surveys of a 1986 flood demonstrate that Forest Preserve lands in Lake and Cook counties reduced the property damage along the Des Plaines River (Forest Preserves of Cook County, 2013).

Batker et al. (2010) reported a water flow regulation value of $9.61/ac/year ($2006; $11.36 in $2014) for forest, and a value between $5.72/ac/year and $170.89/ac/year ($2006; $6.76-$202.04 in $2014) for urban green space.

American Forests (2000) estimated that between 1972 and 1999, tree losses in the Houston metro area (including 159,438 acres of areas with >50% tree cover and 101,183 acres with 20-49% tree cover) resulted in an estimated 360 million cubic feet (ft3) increase of stormwater flow during peak storm events. Replacing the lost stormwater retention capacity with engineered systems, at $0.66/ft3 of storage (estimated by the Harris County Flood Control District), would have cost $237 million (American Forests, 2000). The Conservation Fund (2013) considered areas with >50% tree cover as forest, and divided the area of 20-49% tree cover in half, arriving at an estimated $1462 per acre of forest lost ($2010; $1600 in $2014). American Forests (2000) calculated the annual benefits based on stormwater management facilitiesâ&#x20AC;&#x2122; construction costs, plus the cost of the loan or bond to finance construction (but apparently not including operation and maintenance costs) as $17 million annually, or $105/ac/year of forest ($2010; $115 in $2014).

Simulations by Tilley et al. (2012) showed that less runoff was generated from forested watersheds than urban watersheds. Forests, by dampening stormwater discharges, lessen the negative effects of high storm flows, like accelerated erosion and the need for larger public works. The public value of stormwater mitigation by forests was $290/ac/year ($2000; $400 in $2014), and the fair payment price ranged from $9 to $96/ac/year ($2000).

McPherson et al. (2006) and CNT (2010) reported a sample large tree (hackberry, 37-foot spread, 40 years old) intercepted, on average, 5,387 gallons/year of rainfall in the Midwest region, and reduced stormwater runoff by an equivalent amount. A sample medium-sized tree (red oak, 27-foot spread, 40 years old) intercepted 2,690 gallons/year.

When converted to acres, assuming a continuous tree canopy (i.e., forest at least 40 years old), both sizes of trees intercept 205,000-218,000 gallons/year/ac, with the higher number corresponding to larger trees.

McPherson et al. (2006) used 2004 sewer service fees for the City of Minneapolis as a "conservative proxy" for the value of rainfall intercepted and potential cost reductions in stormwater management controlâ&#x20AC;&#x201D;a value that includes the cost of collection, conveyance, and treatment. This fee, $0.0046/gal, was well below the average price of stormwater runoff reduction ($0.089/gal) assessed in similar studies. Multiplying the Minnesota rate by 212,000 gallons/ac/year, the midpoint for medium-sized and large Midwest trees gives a value of $975/ac/year in 2004 dollars ($1,230 in $2014). At $0.089/gal, the value is $18,868/ac/year (presumably also in 2004 dollars; $23,800 in $2014). McPherson et al. (2006) went with the lower number, though (e.g., reporting a value of $24.78 per 40-year-old hackberry, or $1,004/ac/year).

Mittman et al. (2014) reported that in Lancaster, PA, green infrastructure practices (including tree planting and bioretention) would reduce the volume and rate of runoff entering sewer systems. In combined sewer systems such as Lancasterâ&#x20AC;&#x2122;s, this could reduce both the storage and treatment required to manage CSOs. This, in turn, could reduce both the capital and operational costs of "gray infrastructure systems" such as storage tanks and pumping stations. Over 25 years, the avoided capital cost of implementing gray infrastructure would be $120 million and the avoided operational cost $661,000 per year. The unit cost of wastewater treatment and pumping was $0.00125/gallon, and the unit cost for CSO reduction through gray infrastructure storage was $0.23/gallon of CSO treated in an average year. Multiplying $0.23125/gallon by 212,000 gallons/ac/year intercepted by trees (McPherson et al., 2006) gives $49,000/ac/year.

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For the Metropolitan Water Reclamation District (MWRD) of Greater Chicago, CNT (2009, 2010) reported a marginal cost of treating its wastewater and stormwater of $0.0000919 per gallon. The annual avoided cost for stormwater treatment associated with an acre of forest would, therefore, be (using the midpoint between the two tree sizes) $19/ac/year (c. $2009; $21 in $2014). It was not clear how this cost per gallon was calculated, though.

CNT (2010) then added avoided gray infrastructure needs, citing a study in Portland, Oregon (Evans, 2008) that estimated that it costs the city $2.71/square foot in infrastructure costs to manage the stormwater generated from impervious areas. Thus, an acre of natural land would avoid $126,000 in additional costs. Annualized over 20 years, with a 4% interest rate, and excluding maintenance costs, this is $9,265/ac/year ($2014).

Dividing MWRD's $581,701,000 in expenses in 2013 (MWRD, 2012) by 1.4 billion gallons of wastewater per day (511 billion gallons of wastewater per year) gives $0.001138/gallon treated. There is no reason to assume a linear relationship between each gallon of stormwater reduced and total budget, but this would give a value of $241/ac/year in 2013 dollars.

Ford and Sheaffer (1988) reported that during a 100-year flood, the 66,930 acres of land owned and managed by the Forest Preserve District of Cook County, Illinois, stored 63,806 acre-feet of stormwater runoff. About 20% of this land was within the 100-year floodplain. District lands provided about 80% of publicly owned flood storage in the county, much more than engineered structures. The average construction cost for an acre-foot of flood storage in a surface reservoir in Cook County was $9,024 per acre-foot (from a 1987 report). Using this as a replacement cost, the 66,930 acres of District land had a flood storage value of $575,785,344 ($1987), or $18,042/acre ($2014).

We annualized costs by applying the equivalent annual cost (EAC) equation, which is the cost per year of owning and operating an asset over its entire lifespan. The formula is:

EAC = (Asset Price x Discount Rate) / (1 - (1 + Discount Rate)-Number of Periods )

We used the average annual federal inflation rate (3%) for the discount rate, and two different lifespan periods: 20 and 50 years (NVRC (2007) reported that stormwater ponds can be expected to function 20-50 years, assuming regular maintenance). Then, annual operation and maintenance costs must be added. SEWRPC (1991) reported annual operation and maintenance costs about 5% of capital cost for treating large drainage areas (20-1,000 ac); $902/ac/year in this case. For a 20 year lifespan, avoided costs were $2,116/ac/year ($2014); for 50 years, $1,603/ac/year.

Johnston et al. (2004) found that using conservation practices compared to conventional development could reduce 100-year flood damages in a suburban Chicago watershed by $4,337 to $11,732 per acre. For infrastructure benefits, considering only downstream road culverts, the use of conservation design practices upstream would avoid $3.3 million to $4.5 million in costs of culvert replacement or upgrades.

As a note, Dlugolecki (2012) reported that the cost of floodwater caused erosion on downstream users is between $6.40 and $46.10 per ton of sediment. NRCS (2007) estimated Marylandâ&#x20AC;&#x2122;s annual soil loss to erosion at 3.6 tons/ac. With soil retailing at $42/ton, the value of forest in preventing soil erosion is thus $151/ac/year. Avoiding the cost of dredging could be also added to this estimate.

Riparian Forest

Klapproth and Johnson (2001) reported that sedimentation increases the rate at which lakes and reservoirs are filled, costing communities millions of dollars to create new facilities and to maintain existing ones. A 1985 study estimated that 1.4 to 1.5 million acre-feet of reservoir and lake capacity is permanently filled each year with sediment (Klapproth and Johnson, 2001). Nationwide, sedimentation of water storage facilities cost communities nearly $1.1 billion in 1983 (Klapproth and Johnson, 2001). Nearly a million acre-feet of additional storage capacity, at a cost of $600 to $1,400 per acre-foot ($2006), must be built to capture and store sediment (Klapproth and Johnson, 2001).

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Riparian forest buffers play an important role in flood control. As flood waters move into riparian floodplains, vegetation slows the waterâ&#x20AC;&#x2122;s movement, reducing its erosive potential and capturing materials carried by the floodwaters (Klapproth and Johnson, 2001). The porous forest floor acts as a sponge, quickly absorbing and storing floodwaters, then releasing them slowly back into the stream and groundwater (Klapproth and Johnson, 2001). Severe floods in Virginia in 1994-95 caused more than $10 million in damage (Klapproth and Johnson, 2001). In areas where forested buffers existed, the damage to river banks and adjacent farmlands was reduced (Klapproth and Johnson, 2001). From the studies cited above, the value of forests and wetlands in controlling floodwaters is greater along streams and rivers.

Riparian vegetation is especially important for sediment retention. During flood events, streams and rivers overtop their banks, and water flows through the adjacent floodplains and wetlands. Floodwaters often carry large volumes of suspended sediment, mostly fine sand, silt, and clay. Because dense vegetation, microtopography, and woody debris in floodplains and wetlands provide resistance, the flow of water is slowed and sediment is deposited and stored there (Maryland Department of the Environment, 2006).

Riparian forest buffers reduce flood damage as they reduce water velocities and capture sediments. The sedimentation of streams contributes to flood damage by filling in streambeds and increasing the frequency and depth of flooding and by increasing the volume of flood waters, as well as by causing additional damage itself (Klapproth and Johnson, 2001).

In Delaware, Weber (2007a) found that streams were likely to be in better physical condition if their upstream catchment had >45% riparian forest or wetland (within 30m of the stream bank). Streams were rated according to their sediment load, bank stability, and eutrophication (i.e. depletion of oxygen in water).

Wetlands

Any topographic depression in the landscape has the potential to store water, and thereby play a role in flood control.

Wetland basins not already filled to capacity can mitigate flooding by storage, slowing floodwaters, and reducing peaks and increasing the duration of flow (Sather and Smith, 1984). The value of flood control by wetlands increases with: (1) size (i.e., the larger the wetland, the more area for flood storage and velocity reduction), (2) proximity of the wetland to flood waters, (3) location of the wetland (e.g., along a river, lake, or stream), (4) the amount of flooding that would occur without wetlands present, and, (5) the lack of other upstream storage areas such as ponds, lakes, and reservoirs (Mitsch and Gosselink 1993). Locations within the drainage basin, texture of the substrate, and type of vegetation are also factors (Sather and Smith, 1984). Groups of wetlands in a watershed are more effective at flood control than isolated wetlands (Sather and Smith, 1984).

In Wisconsin, watersheds with 30% wetland or lake area had flood peaks 60-80% lower than watersheds with no wetland or lake area (Sather and Smith, 1984). The reduction was 60-65% if the watershed was 15% wetland or lake (Sather and Smith, 1984). A study by the Massachusetts Water Resources Commission on the Neponist River indicated that the loss of 10% of the wetlands along that river would result in flood stage increases of 1.5 feet, and the loss of half the wetlands would increase the flood stage by 3 feet (California Dept. of Water Resources, 2005). Wetlands within and upstream of urban areas are particularly valuable for flood protection (Osmond et al., 1995). The impervious surface in urban areas greatly increases the rate and volume of runoff, thereby increasing the risk of flood damage (Osmond et al., 1995). Brody et al. (2011) found a highly significant (p<0.01) relationship between permits to disturb wetlands and flood damage in dollars in Coastal Texas between 1997 and 2007.

Based on cost differences between channelization versus using wetlands, Ko (2007) estimated the value of wetlands for flood mitigation as $5,800 per acre in a case study. The detention plan included costs of land acquisition, excavation, and structure. Utilizing an already preserved area, which may not require a budget for land acquisition, would have a significantly higher cost savings.

The drainage of wetlands, diversion of the Mississippi and Missouri rivers from their original floodplains, and development in the floodplains were partly responsible for the billions of dollars in damage to businesses, homes, and crops during the Midwest flood of 1993 (Osmond et al., 1995). Hey et al. (2004) wrote that restoring the 100-year flood zone of the Upper Mississippi five-state watershed could store 39 million acre-feet of floodwater, the volume that caused this flood, and save over $16 billion in projected flood damage costs.

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The cost of replacing the natural flood control function of 5,000 acres of drained wetlands in Minnesota was $1.5 million annually, or $388/ac/year in $2014 (EPA, 2006; Sipple, 2007). This was the lowest of available estimates.

Wetlands protected by the Greenseamsâ&#x201E;˘ Program of the Milwaukee Metropolitan Sewerage District can store 1.325 billion gallons of water, at a cost of $22.5 million to protect the land, or $0.017 per gallon (c. $2011). One acre of hydric soils alone (not including surface storage) can hold 2 acre-feet of water, or 651,702 gallons (unpublished data). In contrast, the Milwaukee County Grounds detention basin can store 315 million gallons, at a cost of over $100 million, or $0.31 per gallon (unpublished 2011 data). Protecting an equivalent area of wetlands (483 ac) could save $219,000/ac ($2014). Annualizing over 20 years with a 4% interest rate, this is $15,960/ac/year.

Wetlands surrounding the Boston area have been estimated to prevent $43,700 (adjusted to 2014 dollars) of flood damage per acre of intact wetland (Dlugolecki, 2012; EPA, 2012). Annualizing over 20 years with a 4% interest rate, this is $3,173/ac/year ($2014).

According to EPA (2001, 2006), an acre of wetlands can typically store 1-1.5 million gallons of floodwater. Given a replacement cost of $0.27/gallon (American Forests, 1999), this translates to $390,000-$585,000/ac ($2014).

Annualizing over 20 years with a 4% interest rate, this is $28,000-43,000/ac/year.

Leschine et al. (1997) compared flood protection effectiveness and cost between engineered systems and existing wetlands. Three wetland systems studied by Leschine et al. (1997) provided $39,000-$55,000/ac of flood protection ($2010). A channel and detention pond, costing $195,000 ($1989), would reduce peak flow by 56%, while 23.7 acres of wetlands would reduce it by 80%. After considering the differences in reduction efficiency, Leschine et al. (1997) estimated the value of wetlands for flood mitigation as $20,400 per acre for an isolated wetland and $61,800/ac for a series of wetlands ($2010). Annualizing over 20 years with a 4% interest rate, this is $1,620/ac/year for isolated wetlands and $4,900/ac/year for wetlands in series ($2014).

Wossink and Hunt (2003) compared the annualized construction, land opportunity, and maintenance costs of restored wetlands to stormwater ponds. Weber (2007b) used data and best-fit curves from Wossink and Hunt (2003) to estimate the cost of a stormwater pond that could capture the same amount of runoff as a one acre Coastal Plain wetland in Maryland. According to their data, a one-acre wetland could treat runoff from a 100-acre watershed. The equivalent constructed pond would be 0.0075*100 = 0.75 ac, and have a construction cost of $13,909*100*0.672 = $307,111. The 20-year maintenance cost would be $9,202*100*0.269 = $31,760 (present value), giving a total present value of $338,871 ($2006). Annualized over 20 years, with a 4% interest rate, this is $29,079/ac/year ($2014). Weber (2007b) did not include land opportunity costs, which would increase this value, especially in urban areas.

From CH2MHill (2009), the average construction cost for five detention ponds in the Calumet-Sag Channel watershed in Cook County, IL, was $0.25/gallon ($2014). We examined other watershed plans, but the project costs included other flood control categories besides storage. Multiplying by 1-1.5 million gallons/ac of floodwater (EPA 2001, 2006) gives a replacement cost of $250,000-$375,000/ac. Following the methodology reported under the forest section, we annualized over 20 to 50 years with a 3% discount rate and 5% annual operation and maintenance costs, giving $22,000$44,000/ac/year ($2014).

Thibodeau and Ostro (1981) estimated that the loss of 8,442 acres of wetlands within the Charles River system in Massachusetts would result in annual flood damages of over $17 million ($1976; $8,419/ac/year in $2014). Because of this, the Army Corps of Engineers preserved the wetlands rather than constructing extensive flood control structures (Leschine et al., 1997).

Examining results from 39 studies, Woodward and Wui (2001) reported a value between $89/ac/yr and $1747/ac/yr (mean $393/ac/yr) for flood control by wetlands ($1990). Converting to $2014, this is $162-$3,180/ac/yr (mean $715/ac/yr).

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As a cautionary note, artificially increasing runoff to wetlands (e.g., by directing stormwater flow there) may impact their natural functions. Increased hydroperiods and water depths may kill or stress vegetation, and could change the community to an open water system. Sedimentation may bury plants and seeds.

Wetland vegetation helps control erosion in coastal, lacustrine (i.e. near lakes) and riverine systems by binding and stabilizing substrates, dissipating wave and current energy and trapping sediments (Sather and Smith, 1984). Physical forces may prevent vegetation from establishing; wetland plants are usually found where waves, currents, and wind are not too strong (Sather and Smith, 1984). Wetland erosion control effectiveness depends on the flood tolerance and resistance to undermining of plants, the width of the vegetated shoreline band, the efficiency of the shoreline band in trapping sediments, the soil composition of the bank or shore, the height or slope of the bank or shore, and the elevation of the bank toe with respect to mean storm high water (Sather and Smith, 1984; Osmond et al., 1995). Coastal and estuarine marshes retain sediment brought in by tides and residual suspended sediment from rivers (Maryland Department of the Environment, 2006).

Lakes/Streams Floodplains

California Dept. of Water Resources (2005) reported that reconnecting the Napa River to its floodplain would cost about $250 million, but save about $1.6 billion in flood damage over the next century.

The Resource Coordination Policy Committee (1998) reported over $39 million in average annual damages from flooding in the watersheds of the Chicago metropolitan area ($58 million/year in 2014 dollars). These watersheds totaled 3,874 mi2, and the area subject to flooding was 64,438 acres. Not building in floodplains could save an average $900/ac/year ($2014) in damages.

Kousky et al. (2013) compared flood damage prevention to land purchase costs in the East River Watershed, WI. Preventing additional development in the 100-year floodplain forecast between 2010 and 2025 by purchasing easements would preserve 7403 acres of open space and avoid an average annualized loss (AAL) of $2.63 million/year ($2010), or $388/ac/year ($2014).

Purchasing all floodplain properties would cost more than this, approximately $3 million/year when annualized over 100 years at a 5% discount rate (Kousky et al., 2013). However, some of these properties were disproportionately expensive.

Targeting based on costs, flood depth, and parcel acreage, would cost $298,000/year for 417 parcels totaling 6379 acres, and prevent flood damages around $1.5 million/year. (Note: for the purposes of this study, we are only estimating benefits, which would be added together for the different ecosystem services, and then easement or fee simple costs could be subtracted. Subtracting easement costs for each separate service would count the same cost multiple times.)

Ford and Sheaffer (1988) reported that each floodplain acre in Cook County, IL, that is acquired and maintained as open space stores an average of 3.88 acre-feet of floodwater. The average construction cost for an acre-foot of flood storage in a surface reservoir in Cook County was $9,024 per acre-foot ($1987). Using this as a replacement cost, natural floodplains had a flood storage value of $35,000/acre ($1987). Following the methodology reported under the forest section, we annualized over 20 and 50 years with a 3% discount rate and 5% annual operation and maintenance costs, giving $6,500-$8,600/ac/year ($2014).

Stream buffers

Once a stream is degraded by erosion, it is very expensive to restore. According to MD DNRâ&#x20AC;&#x2122;s Watershed Restoration Division and Baltimore Countyâ&#x20AC;&#x2122;s Department of Environmental Protection and Resource Management, the unit cost for stream restoration, design, and construction averages $1.2 million per mile in urban and suburban watersheds (Moore, 2002). MD DNR estimates that stream restoration in non-urban watersheds costs approximately $0.6 million per mile (Moore, 2002), or around $140 per foot in 2010 dollars. This figure does not include monitoring costs. Marylandâ&#x20AC;&#x2122;s State Highway Administration (SHA) estimated the following construction costs for stream restoration (S. Hertz, SHA, personal communication, July 24, 2007): Page 106 of 172

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• • • •

Full stream restoration (new channel): $300 - $500 per linear foot Bank armoring only/spot restoration: $100 - $300 per linear foot Vegetative stream restoration (e.g. fascines - wood lined trenches): $50 - $100 per linear foot Riparian buffer planting only: $5 - $50 per linear foot

Design costs are typically 30% of the construction costs, and the monitoring budget over 5 years is around $30 per linear foot (S. Hertz, SHA, personal communication, July 24, 2007). Using a construction cost of $100 per linear foot, adding design and monitoring costs, and annualizing over 20 years with a 7% interest rate, this totaled $15/ft/year ($2006).

These costs are equivalent to DNR’s estimate for rural stream restoration. The Maryland Dept. of Natural Resources Stream ReLeaf program recommends a buffer width of 100 feet on each side. In Cecil County, MD, which is still primarily rural, the value of riparian forest (usually recommended for restoration purposes to be 100 ft from either bank) was correspondingly $15/year * 43,560 ft2/ac / 200 ft2 = $3,267/ac/year (in $2014, $3,855/ac/year).

Lakes and ponds

From CH2MHill (2009), the average construction cost for five detention ponds in the Calumet-Sag Channel watershed in Cook County, IL, was $83,100/ac-ft ($2014). If we assume an average depth of 5 feet, this is $415,500/ac. Following the methodology reported under the forest section, we annualized over 20 and 50 years with a 3% discount rate and 5% annual operation and maintenance costs, giving $37,000-$49,000/ac/year ($2014). Storage should be computed separately for each lake and pond by estimating additional storage capacity (i.e., beyond base conditions) rather than just surface area.

Prairie/Grassland/Savanna

Gulf Coast prairies contain deep-rooted grasses and vertisol soils, which can absorb and retain considerable volumes of water. They typically contain wetlands, but many are smaller than the National Wetlands Inventory (NWI) minimum mapping unit (1-3 ac). In the Armand Bayou watershed, prairie pothole wetlands provide at least 3,000 acre-feet of detention over and above the natural storage of the native soils in the area (189,000 acres of prairie pothole habitat in the watershed, which is about 30% depressional wetlands, with about 1 ft average depth.) (Unpublished data).

Batker et al. (2010) reported a water regulation value of $1.65/ac/year ($2006; $1.95 in $2014) for grassland from Costanza et al., 1997.

Brye et al. (2000) reported the mean volumetric water storage for a restored prairie in Wisconsin to be 0.68 m3/m3 (180 gallons/m3) in the upper 1.4 m of soil. This converts to 728,000 gallons/ac. By multiplying by $0.25/gallon (CH2MHill 2009; see wetland methodology) gives a replacement cost of $182,000/ac ($2014). Following the methodology reported under the forest section, we annualized over 20 and 50 years with a 3% discount rate and 5% annual operation and maintenance costs, giving $16,000-$21,000/ac/year ($2014).

Spatial Assessments

MARC and AES (2013) assigned quantitative values to areas for water flow regulation. They ignored variations in precipitation and potential best management practices (BMPs), but assigned a TR55 curve number to each land cover type: the greater the percentage of impervious cover, the greater the estimated runoff potential. They also assigned a hydrologic group (A to D, high to low infiltration rate, converted to a numerical value) to SSURGO soil polygons, and converted this to a grid. They added the two factors (land cover runoff potential plus soil infiltration) together. They did not attempt to compute a dollar value for this or other services.

Kozak et al. (2011) found that in the Des Plaines watershed in the Chicago area, value estimates for wetland ecosystem services varied by nearly three orders of magnitude, showing huge sensitivity to decay parameters. They also stated that ecosystem services are more likely to be scarce in urban than rural landscapes, and therefore more valuable per household at the margin.

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The Conservation Fund (2013) assigned the public value of $290/ac/year from Tilley et al. (2012) to forest cells. Nontidal wetlands were $7,990/ac/year (Thibodeau and Ostro, 1981).

Tidal wetlands were $3,820/ac/year (Costanza et al., 2008). Then, the authors estimated the number of households at risk of flooding, by watershed. From 2010 census data, they identified block centroids falling within FEMA 100 year floodplains. They then summed the number of households in 100-year floodplains by HUC10 watershed. At the watershed level, they hoped spatial errors of omission and commission would cancel each other out.

Because the housing calculation did not consider damage to businesses or institutions, the Conservation Fund (2013) also examined developed land vulnerable to flooding. First, they reclassified 2006 NLCD (National Land Cover Database), giving developed land a relative weight between 1 and 4 (low intensity = 1, medium = 2, and high = 4). They based the reclassification on the principle that on average, high-intensity development contains a higher density of buildings and invested resources than low-intensity development. Next, they identified which developed land falls (using the above relative impact values) within FEMA 100 year floodplains. As with the centroid data, they assumed spatial errors were less important at the watershed level. The results closely resembled those of flood-vulnerable households. Watersheds with more buildings in the floodplain were more vulnerable to flooding, and conservation and restoration efforts in those watersheds should have more economic benefit.

Industrial Economics (2011) applied the InVEST storm peak mitigation model to the Red Clay Creek watershed in the Piedmont region of Delaware to quantify how the presence of wetlands affects the probability of stormwater reaching inland properties. The model estimated the relative contribution of particular areas to flood potential following a storm.

It only considered one type of potential flooding - properties within floodplains of streams and rivers. Additional flooding potential could be associated with, for example, ponding of stormwater in inland areas. They calculated storm surge from tidal waters using different methodologies. In this watershed, Industrial Economics (2011) projected $57$1,690/year ($2010) of additional flood damage impacts to residential structures (other impacts not considered) as 53 acres of wetlands were lost ($1.20-$35/ac/year in $2014).

References in this section

American Forests. 1999. Regional ecosystem analysis: Chesapeake Bay region and the Baltimore-Washington corridor.

American Forests, Washington, DC. American Forests. 2000. Urban ecosystem analysis for the Houston Gulf Coast region: calculating the value of nature.

American Forests, Washington, DC. Batker, D., M. Kocian, B. Lovell, and J. Harrison-Cox. 2010. Flood protection and ecosystem services in the Chehalis River Basin. Earth Economics, Tacoma, WA. Brody, S. D., W. E. Highfield, and J. E. Kang. 2011. Rising waters: the causes and consequences of flooding in the United States. Cambridge Univ. Press, Cambridge, UK. 195 pp.

Brye, K. R., J. M. Norman, L. G. Bundy, and S. T. Gower. 2000. Water-Budget Evaluation of Prairie and Maize Ecosystems.

Soil Sci. Soc. Am. J. 64:715â&#x20AC;&#x201C;724.

California Dept. of Water Resources. 2005. Multi-Objective Approaches to Floodplain Management on a Watershed Basis: Natural Floodplain Functions and Societal Values. Online at http://www.economics.water.ca.gov/studies.cfm. 34 pp.

Center for Neighborhood Technology (CNT). 2009. Green Values Calculator. http://greenvalues.cnt.org/national/benefits_detail.php#reduced-treatment.

Center for Neighborhood Technology (CNT). 2010. The value of green infrastructure: a guide to recognizing its economic, environmental and social benefits. Center for Neighborhood Technology, Chicago, IL.

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Center for Neighborhood Technology (CNT). 2014. The prevalence and cost of urban flooding: a case study of Cook County, IL. Center for Neighborhood Technology, Chicago, IL. CH2MHill. 2009. Detailed Watershed Plan for the Calumet-Sag Channel Watershed. Metropolitan Water Reclamation District of Greater Chicago, Chicago, IL. Conservation Fund, The. 2013. Houston-Galveston Green Infrastructure and Ecosystem Services Assessment.

Dlugolecki, L. 2012. Economic Benefits of Protecting Healthy Watersheds: A Literature Review. U.S. Environmental Protection Agency.

Evans, D. and Associates, Inc. 2008. Cost-Benefit Evaluation of Ecoroofs. City of Portland Bureau of Environmental Services, Portland, OR. Ford, C. R., and J. R. Sheaffer. 1988. Forest Preserve District of Cook County, Illinois: An evaluation of floodwater storage.

Sheaffer & Roland, Inc. Wheaton, IL. Forest Preserves of Cook County. 2013. Floodplain & Stormwater Management. http://fpdcc.com/conservation/floodplain-stormwater-management/. Accessed Aug. 29, 2014.

Hey, D. L., et al. 2004. Flood damage reduction in the Upper Mississippi River basin: an ecological alternative. The Wetlands Initiative, Chicago, IL. Houston-Galveston Area Council (HGAC). 2010. Eco-logical: Creating a regional decision support system for the HoustonGalveston region. Houston-Galveston Area Council, Houston, TX. 63 pp.

Industrial Economics, Inc. 2011. Economic valuation of wetland ecosystem services in Delaware: Final report. Delaware Department of Natural Resources and Environmental Control, Division of Water Resources, Dover, DE. Johnston, D. M., J. B. Braden, and T. H. Price. 2004. The Downstream Economic Benefits from storm Water Management: a Comparison of Conservation and Conventional Development. UCOWR Conference Proceedings, Paper 23. http://opensiuc.lib.siu.edu/ucowrconfs_2004/23 Klapproth, J. C., and J. E. Johnson. 2001. Understanding the science behind riparian forest buffers: benefits to communities and landowners. Virginia Cooperative Extension. Publication Number 420-153.

Ko, J-Y. 2007. The economic value of ecosystem services provided by the Galveston Bay/estuary system. Texas Commission on Environmental Quality, Galveston Bay Estuary Program, Webster, TX. Kousky, C., S. M. Olmstead, M. A. Walls, and M. Macauley. 2013. Strategically placing green infrastructure: cost-effective land conservation in the floodplain. Environ. Sci. Technol. 47 (8):3563–3570.

Kozak, J., C. Lant, S. Shaikh, and G. Wang. 2011. The geography of ecosystem service value: The case of the Des Plaines and Cache River wetlands, Illinois. Applied Geography 31:303-311.

Leschine, T. M., K. F. Wellman, and T. H. Green. 1997. The economic value of wetlands: wetlands’ role in flood protection in western Washington. Ecology Publication No. 97-100. Washington State Dept. of Ecology, Bellevue, WA. Londoño Cadavid, C. and A. W. Ando. 2013. Valuing preferences over stormwater management outcomes including improved hydrologic function. Water Resources Research 49(7):4114–4125.

Maryland Department of the Environment. 2006. Prioritizing sites for wetland restoration, mitigation, and preservation in Maryland. Draft version: April 27, 2006. Maryland Department of the Environment Wetlands and Waterways Program, Baltimore, MD. Page 109 of 172

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McPherson, E., J. R. Simpson, P. J. Peper, S. L. Gardner, K. E. Vargas, S. E. Maco, and Q. Xiao. 2006. Midwest Community Tree Guide: Benefits, Costs, and Strategic Planting. General Technical Report PSW-GTR-199. United States Department of Agriculture, Forest Service, Pacific Southwest Research Station. Davis, CA. Metropolitan Water Reclamation District of Greater Chicago (MWRD). 2012. 2013 Budget. www.mwrd.org.

Mid-America Regional Council (MARC) & Applied Ecological Services (AES). 2013. Kansas City Natural Resources Inventory II Phase 4: Ecosystem Services Method Development.

Mitsch, W. J., and J. G. Gosselink. 1993. Wetlands, 2nd edition. Van Nostrand Reinhold, New York.

Mittman, T., et. al. 2014. The economic benefits of green infrastructure: a case study of Lancaster, PA. EPA 800-R-14007. U.S. Environmental Protection Agency, Washington, DC. Moore, T. (ed.) 2002. Protecting Maryland's Green Infrastructure. The case for aggressive public policies. Maryland Dept. of Natural Resources, Annapolis, MD. Natural Resources Conservation Service (NRCS). 2007. National Resources Inventory 2003 Annual NRI. Online at http://www.nrcs.usda.gov/.

Northern Virginia Regional Commission (NVRC). 2007. Maintaining stormwater systems: a guidebook for private owners and operators in Northern Virginia. Northern Virginia Regional Commission, Fairfax, VA. Osmond, D.L., D.E. Line, J.A. Gale, R.W. Gannon, C.B. Knott, K.A. Bartenhagen, M.H. Turner, S.W. Coffey, J. Spooner, J. Wells, J.C. Walker, L.L. Hargrove, M.A. Foster, P.D. Robillard, and D.W. Lehning. 1995. Values of wetlands. Online at http://www.water.ncsu.edu/watershedss/info/wetlands/values.html.

Resource Coordination Policy Committee. 1998. Our community and flooding: a report on the status of floodwater management in the Chicago metropolitan area.

Sather, J. H. and R.D. Smith. 1984. An overview of major wetland functions and values. U.S. Fish and Wildlife Service FWS/OBS-84/18. Washington, DC. Sipple, B. 2007. Wetlands functions and values. http://www.epa.gov/watertrain/wetlands/.

Southeastern Wisconsin Regional Planning Commission (SEWRPC). 1991. Costs of urban nonpoint source water pollution control measures. Southeastern Wisconsin Regional Planning Commission, Waukesha, WI. Thibodeau, F.R. and B.D. Ostro. 1981. An Economic Analysis of Wetland Preservation. Journal of Environmental Management, 12:19-30.

Tilley, D., E. Campbell, T. Weber, P. May, and C. Streb. 2011. Ecosystem based approach to developing, simulating and testing a Maryland ecological investment corporation that pays forest stewards to provide ecosystem services: Final report. Department of Environmental Science & Technology, University of Maryland, College Park, MD. U.S. Environmental Protection Agency (EPA). 2001. Functions and values of wetlands. EPA Publication 843-F-01-002c.

U.S. Environmental Protection Agency (EPA). 2006. Wetlands: protecting life and property from flooding. EPA843-F-06001.

U.S. Environmental Protection Agency (EPA). 2012. The economic benefits of protecting healthy watersheds. EPA Publication 841-N-12-004.

Weber, T. 2007b. Ecosystem services in Cecil Countyâ&#x20AC;&#x2122;s Green Infrastructure: Technical Report for the Cecil County Green Infrastructure Plan. The Conservation Fund, Annapolis, MD. Page 110 of 172

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Woodward, R. T. and Y.-S. Wui. 2001. The economic value of wetland services: a meta-analysis. Ecological Economics 37:257-270.

Wossink, A., and B. Hunt. 2003. An evaluation of cost and benefits of structural stormwater best management practices in North Carolina. North Carolina Coop. Ext. Service.

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Water Purification

Detailed Literature Review

The recent crisis in Toledo, Ohio, where a Microcystis algal bloom rendered the city's water supply unsafe, highlights our dependence on clean drinking water. Forests, wetlands, and prairies protect waterbodies from pollutants and sedimentation by absorbing and filtering water. They help maintain water quality sufficient for human consumption, recreational uses like swimming and fishing, and aquatic life. Compared to natural ecosystems, urban landscapes add seven times as much nitrogen and ten times as much phosphorus to surface waters (Moore, 2002), and impervious surfaces like roads and parking lots carry pollutants such as oils, grease, heavy metals, and salts to streams. Pollutants of particular interest in the Chicago region include nitrogen (N), phosphorus (P), and chloride (Cl-). LondoĂąo and Ando (2013) found that residents of Champaign and Urbana, Illinois were each, on average, willing to pay $37/year to avoid further deterioration of water quality in streams.

Woodlands/Forest

By slowing surface runoff and providing opportunities for settling and infiltration, forests help remove nutrients, sediments, and other pollutants. Infiltration rates 10-15 times higher than grass turf and 40 times higher than a plowed field are common in forests (Chesapeake Bay Program, 2000; Casey, 2004). Tree roots remove nutrients from settled runoff and groundwater and store them in leaves and wood. Through the process of denitrification, bacteria in the forest floor convert nitrate (which can impair water bodies through eutrophication) to nitrogen gas, which is released into the air (Chesapeake Bay Program, 2000). In-stream and river floodplains, vegetation traps and removes water-borne particulates during storms.

Many studies have shown a relationship between water quality and the amount of forest cover in the watershed.

Baltimore County (2005) found that the more forest cover a watershed had, the lower the concentrations of nitrate in the streams. For sites sampled statewide by the Maryland Biological Stream Survey (MBSS) between 1995 and 1997, Benthic Index of Biotic Integrity (IBI) scores increased with increasing forest cover in the catchment (Roth et al., 1999).

The Hilsenhoff Biotic Index, a macroinvertebrate indicator of organic pollution tolerance, was also significantly correlated with catchment forest cover (Roth et al., 1999). Fewer pollution-tolerant organisms were found in catchments with more forest cover, indicating less stream degradation (Roth et al., 1999). Aquatic salamander richness was also higher in catchments with higher amounts of forest cover (Roth et al., 1999). As indicated by the benthic macroinvertebrate community, watersheds in Baltimore County with >50% forest cover generally had the best stream conditions, followed by watersheds with 40-50% forest (Allen and Weber, 2007).

In some parts of the U.S., attention has focused on the benefits of protecting natural watersheds to assure safe and plentiful drinking water supplies, rather than on building expensive filtration plants to purify water from degraded watersheds (World Resources Institute, 1998). Ernst (2004) cited a study of 27 water suppliers that found that the more forest cover in a watershed, the lower the water treatment costs. According to the study, 55% of the variation in treatment costs can be explained by the percent of forest cover in the source area. Further, for every 10% increase in forest cover in the watershed, treatment and chemical costs decreased about 20%, up to about 60% forest cover (see Figure 1). The study had insufficient data for watersheds with more than 65% forest cover (Ernst, 2004).

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Figure 1. Water treatment costs vs. watershed forest cover (Ernst, 2004).

The forest can filter nitrogen, phosphorus, and sediment from overland runoff. According to Industrial Economics (2011), the economic value of nitrogen removal was $188/kg ($2010), which represented the cost of removing nitrogen by connecting an onsite wastewater treatment and disposal system to sewer districts. As nitrogen is removed, phosphorous is simultaneously filtered. The cost of sediment treatment is much lower than nitrogen.

New York City avoided spending $6-8 billion in constructing new water treatment plants by protecting the upstate watersheds that have accomplished these purification services for free (World Resources Institute, 1998). The annualized construction cost would have been around $500 million/year ($6 billion in 1997, 5% interest rate, 20 years).

In addition, Ernst (2004) reported that annual operating expenses would have been $300 million/year. Based on this economic assessment, the city invested $1.5 billion in buying land around its reservoirs and instituting other protective measures, actions that will not only keep its water pure at a bargain price but also enhance recreation, wildlife habitat, and other ecological benefits (World Resources Institute, 1998; Hanson et al., 2011). The Catskill/Delaware watersheds that supply 90% of New York City's drinking water cover 1,583 mi2 (1 million acres), and are primarily (89%) forested (Mehaffey et al., 2001). On average, this supply of clean drinking water is worth $1,300 per acre of forest per year ($2014).

Riparian forest buffers have proven to be effective at reducing nutrient loads in areas that have largely been deforested.

In Baltimore County, Allen and Weber (2007) found that watersheds with more than about 70% riparian forest had the best stream conditions, followed by watersheds between 40-70%. It appeared that riparian forest was most important in largely deforested watersheds. Riparian forest had a more noticeable impact along perennial streams and shorelines than along intermittent streams. Forested buffers (which are more effective than grass over the long term) can remove up to 21 pounds of nitrogen and 4 pounds of phosphorus per acre per year from upland runoff (Klapproth and Johnson, 2001). Studies have demonstrated reductions of 30 to 98 percent for nitrogen, phosphorus, sediments, pesticides, and other pollutants in surface and groundwater after passing through a riparian forest (Osmond et al., 1995; Chesapeake Bay Program, 2000; Casey, 2004).

Retaining and restoring buffers is one of the least expensive strategies for reducing nitrogen loads (Moore, 2002).

Stream buffers are most effective when they are continuous and sufficiently wide. The Chesapeake Bay Commission (2004) reported that feasible upgrades of wastewater treatment plants to clean their effluent to the Chesapeake Bay would cost an annualized $8.56/lb. of nitrogen and $74.00/lb. of phosphorus ($2004). Using numbers from Klapproth Page 113 of 172

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and Johnson (2001), an acre of riparian forest would correspondingly have a nutrient reduction value of $820/ac/year ($2014). This value is lower than that calculated for general forest in New York, which is counterintuitive and demonstrates the uncertainty of these calculations.

Stream buffers can also attenuate other nonpoint pollution, such as bacteria, although these can be grass. Scientists in Minnesota estimated a buffer 118 feet wide would be required to reduce total coliform bacteria to levels acceptable for human recreational use (Klapproth and Johnson, 2009). Other researchers found that even a narrow (7 foot) filter strip removed nearly 95 percent of fecal coliform bacteria (Klapproth and Johnson, 2009). Rogers and Haines (2005) wrote that effective buffers should be at least 10 meters wide and at least 90% vegetated.

Wetlands

Numerous studies have demonstrated that wetlands change water quality through retention and/or modification of sediments, toxins, and nutrients in the water (Sather and Smith, 1984). As water passes through wetlands, its velocity is reduced, large populations of microbes decompose organic substances, and particles are bound to sediments (Sather and Smith, 1984). Submerged and emergent plants help purify water both directly (by absorbing nutrients and other chemicals through their roots) and indirectly (by supplying substrates for bacterial growth, providing a medium for physical filtration and absorption, and restricting algal growth and wave action). Restored wetlands have been shown to be effective at trapping significant amounts of nutrients and sediments (Jordan, 2002). Both natural and restored wetlands have been effective at treating wastewater (Sather and Smith, 1984). Wetlands are most effective at nutrient transformation and uptake when there are seasonal fluctuations in water levels (Maryland Department of the Environment, 2006).

Scientists have estimated that wetlands can remove between 70% and 90% of entering nitrogen. The estimated mean retention of phosphorus by wetlands is 45%, although wetlands with high soil concentrations of aluminum can remove up to 80% of total phosphorus. Biological oxygen demand (BOD) removal by wetlands can approach 100%. BOD is a measure of the oxygen required for the decomposition of organic matter and oxidation of inorganics such as sulfide and is introduced into surface water through inputs of organic matter such as sewage effluent, surface runoff, and natural biotic processes. If BOD is high, low dissolved oxygen levels result, which can kill aquatic life. Wetlands remove BOD from surface water through decomposition of organic matter or oxidation of inorganics (Osmond et al., 1995).

Wetlands have also been shown to change some toxic substances (e.g., heavy metals and pesticides) to harmless states.

Other substances may be temporarily buried in sediments in wetland areas. Heavy metals are removed from wastewater by ion exchange and adsorption to sediment clays and organic compounds; by precipitation as oxides, hydroxides, carbonates, phosphates and sulfides; and by plant uptake (Sather and Smith, 1984). Heavy metal removal varies 20100% depending on the metal and the wetland (Osmond et al., 1995). Forested wetlands can play a critical role in removing metals downstream of urbanized areas (Osmond et al., 1995). Lead leaking from a hazardous waste site in Florida was retained at high levels by a downstream wetland. The majority of the lead (75-80%) was bound to soil and sediments through adsorption, chelation, and precipitation (Osmond et al., 1995). The rest was bioavailable, absorbed primarily by eelgrass (Osmond et al., 1995). In another study, researchers found that wetland vegetation and organic substrate retained 98% of the lead entering the wetland (Osmond et al., 1995).

The fate of pesticides and other toxins is similar to heavy metals. Some are temporarily buried in sediments, some changed to harmless forms and some may enter the food web (Sather and Smith, 1984). The longer the duration that water and transported materials remain in the wetland, the greater the likelihood that the materials will be retained (Maryland Department of the Environment, 2006). Wetlands are also able to remove pathogens from surface water (Osmond et al., 1995). Rogers and Haines (2005) reported 96-99.9% removal of fecal indicator bacteria by wetlands.

Landers (2006) examined side-by-side comparisons of 11 types of best management practices (BMPs) and found that constructed wetlands were the most effective. The wetland in the study removed 100% of suspended solids, 99% of nitrate, 100% of zinc, and 100% of petroleum byproducts, and reduced peak flows by 85% (Landers, 2006). This greatly exceeded the performance of standard retention ponds, as well as expensive manufactured devices (Landers, 2006).

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Langland and Cronin (2003) reported that wetland restoration and tree planting were the most effective BMPs at reducing sediment runoff from agricultural fields (96% from high-till fields).

USACE (2003) reported average wastewater treatment costs using conventional methods to cost $3.24 per 1000 gallons, but through wetlands construction, only $0.47/1,000 gallons ($2001). With an acre of wetlands typically able to store 1.0-1.5 million gallons of floodwater (EPA, 2006), the gross value of wetlands (they may exist already, not needing construction) for wastewater treatment is $4,350-$6,530/ac/year ($2014). (Author's note: a one-acre wetland flooded with one foot of water would equal 326,000 gallons. On the other hand, a wetland temporarily holding all the precipitation falling on it in one year (not including surface inflows) = 39 inches (Illinois average) * 326,000 gallons/acrefeet * 1 foot/12 inches = 1.1 million gallons/acre.)

The value of wetlands in trapping sediment is higher than that of upland forest since wetlands can trap sediments from upslope, much as an engineered sediment basin does. Typically, wetland vegetation traps 80-90% of sediment from runoff (Osmond et al., 1995). The California Stormwater Quality Association (2003) reports the average annual costs for installing and maintaining a sediment basin as $0.05/gallon ($2006). With an acre of wetlands typically able to store 1.01.5 million gallons of floodwater (EPA, 2006), and multiplying by 0.8-0.9, this translates to $40,000-$67,500/ac/year ($2006; $47,300-$79,800 in $2014).

Studies of wetland water quality benefits cited by the California Dept. of Water Resources (2005) and Sipple (2007) include the following: • A 1978 Michigan study estimated that an average acre of wetlands along the shores of the Great Lakes could provide over $19,000 ($2014) worth of water quality improvement annually.

• Natural waste assimilation by marsh in the Charles River Basin of Massachusetts substituted, per acre, for annual capital costs of $235 plus $4,110 in maintenance and operation costs of a tertiary waste treatment plant ($2014; 1981 study).

• The Congaree Bottomland Hardwood Swamp in South Carolina removes a quantity of pollutants equivalent to a $5 million wastewater treatment plant (1990 study).

• A 2,500-acre wetland in Georgia saved $1 million in water pollution abatement costs annually, or $400/ac/year (1993 report; $700 in $2014).

Hey et al. (2005) found that the cost of restoring and operating wetlands to remove nitrogen and phosphorus was 5070% less than the cost of constructing and operating engineered wastewater treatment systems. To achieve the standards of 3.0 mg/L of nitrogen and 1.0 mg/L of phosphorus that 189,000 acres of wetlands could achieve, $184 million/year of annualized costs would be required to build and operate treatment systems. This translates to a wetland value of $1,200/ac/year ($2014).

Ko (2007) found that a 1,800-acre natural wetland could save $275,000/year ($2010) in annualized capital costs and operation and maintenance to filter wastewater at 1 million gallons per day ($170/ac/year; $2014).

Industrial Economics (2011) reported that wetlands filter 63% of nitrogen, 45% of phosphorous, and retains 69-94% of sediment. The economic value of nitrogen removal was $188/kg ($2010), which represents the cost of removing nitrogen by connecting an onsite wastewater treatment and disposal system to sewer districts. As nitrogen is removed, phosphorous is simultaneously filtered. The cost of sediment treatment is much lower than nitrogen. They reported a $770,000 ($2010) annualized municipal water treatment cost of losing 3,132 acres of wetlands over 15 years or $280/ac/year ($2014).

Using results from 39 studies, Woodward and Wui (2001) reported a water quality value between $126/ac/yr and $1,378/ac/yr (mean $417/ac/yr) for wetlands ($1990; $230-$2,513 in $2014) Prairie/Grassland/Savanna

Industrial Economics (2011) reported that rangeland filters 32% of nitrogen, 40% of phosphorous, and retains 99% of sediment. The economic value of nitrogen removal was $188/kg ($2010), which represents the cost of removing Page 115 of 172

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nitrogen by connecting an onsite wastewater treatment and disposal system to sewer districts. As nitrogen is removed, phosphorous is simultaneously filtered. The cost of sediment treatment is much lower than nitrogen.

Batker et al. (2010) reported a water quality value of $47.91/ac/year ($2006; $57/ac/year in $2014) for grassland from Costanza et al., 1997.

Spatial Assessments

MARC and AES (2013) assigned quantitative values to land cover types for phosphorus export, using values from Jeje (2006). They did not model transport to water bodies.

Bateman et al. (2006) found that in the central UK, the willingness to pay for water quality improvements to the heavily polluted River Tame declined following a log-linear function, reaching zero at a distance of 20-28 km, with bigger improvements having greater WTP amounts and distances.

The Conservation Fund (2013) used the program InVEST (v.2.2.2) to calculate non-point nitrogen retention by subwatershed (HUC-12). The economic value of nitrogen removal was $188/kg ($2010) (Industrial Economics, 2011, which represents the cost of removing nitrogen by connecting an onsite wastewater treatment and disposal system to a centralized sewer. As nitrogen is removed, phosphorus is simultaneously filtered; we did not double count. And the cost of sediment treatment is much lower than nitrogen. We calculated $/ac/year for each cell, which ranged from near $0 to $80,000/ac.

References in this section

Allen, W. L., and T. C. Weber. 2007. Baltimore County land preservation model: water quality assessment. The Conservation Fund, Arlington, VA. Baltimore County. 2005. NPDES - Municipal Stormwater Discharge Permit 2005 Annual Report.

Bateman, I. J., B. H. Day, S. Georgiou, and I. Lake. 2006. The aggregation of environmental benefit values: welfare measures, distance decay, and total WTP. Ecological Economics 60:450-460.

Batker, D., M. Kocian, B. Lovell, and J. Harrison-Cox. 2010. Flood protection and ecosystem services in the Chehalis River Basin. Earth Economics, Tacoma, WA. California Dept. of Water Resources. 2005. Multi-Objective Approaches to Floodplain Management on a Watershed Basis: Natural Floodplain Functions and Societal Values. Online at http://www.economics.water.ca.gov/studies.cfm. 34 pp.

California Stormwater Quality Association. 2003. Sediment basin. BMP fact sheet SE-2 in Stormwater best management practice construction handbook. California Stormwater Quality Association, Menlo Park, CA. Casey, J. F. 2004. The value of riparian forest buffers in the Chesapeake Bay watershed: an economic framework for policy-making. National Oceanic and Atmospheric Administration, Washington DC. Chesapeake Bay Commission. 2004. Cost-effective strategies for the Bay: 6 smart investments for nutrient and sediment reduction. Chesapeake Bay Commission, Annapolis, MD. Chesapeake Bay Program. 2000. Riparian forest buffers. Online at http://www.chesapeakebay.net/info/forestbuff.cfm Conservation Fund, The. 2013. Houston-Galveston Green Infrastructure and Ecosystem Services Assessment.

Costanza, R., O. PĂŠrez-Maqueo, M. Luisa Martinez, P. Sutton, S. Anderson, and K. Mulder. 2008. The value of coastal wetlands for hurricane protection. Ambio 37(4):241-248.

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Ernst, C. 2004. Land conservation and the future of America's drinking water: protecting the source. Trust for Public Land, San Francisco, CA. Hanson, C., et al. 2011. Forests for water: exploring payments for watershed services in the US south. World Resources Institute Issue Brief, Issue 2, p.15.

Hey, D. L., J. A. Kostel, A. P. Hurter, and R. H. Kadlec. 2005. Nutrient farming and traditional removal: an economic comparison. Water Environment Research Foundation, Alexandria, VA. Industrial Economics, Inc. 2011. Economic valuation of wetland ecosystem services in Delaware: Final report. Delaware Department of Natural Resources and Environmental Control, Division of Water Resources, Dover, DE. Jeje, Y. 2006. Export coefficients for total phosphorus, total nitrogen and total suspended solids in the southern Alberta region: a review of literature. Alberta Environment, Edmonton, Canada.

Jordan, T. 2002. Vegetated riparian zones, stream buffers. Critical Area Workshop. May 14, 2002.

Klapproth, J. C., and J. E. Johnson. 2001. Understanding the science behind riparian forest buffers: benefits to communities and landowners. Virginia Cooperative Extension. Publication Number 420-153.

Klapproth, J. C., and J. E. Johnson. 2009. Understanding the science behind riparian forest buffers: effects on water quality. Virginia Cooperative Extension. Publication Number 420-151.

Ko, J-Y. 2007. The economic value of ecosystem services provided by the Galveston Bay/estuary system. Texas Commission on Environmental Quality, Galveston Bay Estuary Program, Webster, TX. Landers, J. 2006. Test results permit side-by-side comparisons of BMPs. Civil Engineering News, April 2006, pp. 34-35.

Langland, M., and T. Cronin (eds.) 2003. A summary report of sediment processes in Chesapeake Bay and watershed.

Water-Resources Investigations Report 03-4123. U.S. Geological Survey, New Cumberland, PA. LondoĂąo Cadavid, C. and A. W. Ando. 2013. Valuing preferences over stormwater management outcomes including improved hydrologic function. Water Resources Research 49(7):4114â&#x20AC;&#x201C;4125.

Maryland Department of the Environment. 2006. Prioritizing sites for wetland restoration, mitigation, and preservation in Maryland. Draft version: April 27, 2006. Maryland Department of the Environment Wetlands and Waterways Program, Baltimore, MD. Mehaffey, M. H., M. S. Nash, T. G. Wade, C. M. Edmonds, D. W. Ebert, K. B. Jones, and A. Rager. 2001. A landscape assessment of the Catskill/Delaware watersheds 1975-1998. EPA/600/R-01/075. Env. Prot. Agency, Las Vegas, NV. Mid-America Regional Council (MARC) & Applied Ecological Services (AES). 2013. Kansas City Natural Resources Inventory II Phase 4: Ecosystem Services Method Development.

Moore, T. (ed.) 2002. Protecting Maryland's Green Infrastructure. The case for aggressive public policies. Maryland Dept. of Natural Resources, Annapolis, MD. Osmond, D.L., D.E. Line, J.A. Gale, R.W. Gannon, C.B. Knott, K.A. Bartenhagen, M.H. Turner, S.W. Coffey, J. Spooner, J. Wells, J.C. Walker, L.L. Hargrove, M.A. Foster, P.D. Robillard, and D.W. Lehning. 1995. Values of wetlands. Online at http://www.water.ncsu.edu/watershedss/info/wetlands/values.html.

Rogers, S., and J. Haines. 2005. Detecting and mitigating the environmental impact of fecal pathogens originating from confined animal feeding operations: review. EPA/600/R-06/021.

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Roth, N. E., M. T. Southerland, G. Mercurio, J. C. Chaillou, P. F. Kazyak, S. S. Stranko, A. P. Prochaska, D. G. Heimbuch, and J. C. Seibel. 1999. State of the Streams: 1995-1997 Maryland Biological Stream Survey Results. Maryland Dept. of Natural Resources, Annapolis, MD. Sather, J. H. and R.D. Smith. 1984. An overview of major wetland functions and values. U.S. Fish and Wildlife Service FWS/OBS-84/18. Washington, DC. Sipple, B. 2007. Wetlands functions and values. http://www.epa.gov/watertrain/wetlands/.

U.S. Army Corps of Engineers (USACE). 2003. Applicability of constructed wetlands for Army installations. Public Works Technical Bulletin 200-1-21. U.S. Army Corps of Engineers, Washington, DC. U.S. Environmental Protection Agency (EPA). 2006. Wetlands: protecting life and property from flooding. EPA843-F-06001.

Woodward, R. T. and Y.-S. Wui. 2001. The economic value of wetland services: a meta-analysis. Ecological Economics 37:257-270.

World Resources Institute. 1998. 1998-99 world resources. World Resources Institute, Washington, DC.

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Groundwater Recharge

Detailed Literature Review

With increasing droughts around the world, humans rely more and more on groundwater for drinking water, irrigation, and other purposes, especially in dry areas with suitable aquifers. In many of these areas, the water table is dropping as water is pumped from the ground faster than it can recharge. In California, wells that used to reach water 500 feet below the surface must now be drilled down 1,000 feet or more, at a cost of more than $300,000 for a single well (Dimick, 2014).

The CMAP region relies primarily on the Cambrian-Ordovician aquifer for groundwater (Sasman et al., 1977). Sand and gravel deposits, coupled with dolomitic materials in underlying shallow bedrock, also contain accessible groundwater (e.g., Baxter & Woodman, Inc., et al., 2006). In some areas, artesian pressure declined more than 850 feet between 1864 and 1971 (Sasman et al., 1977; see Figure 2 from USGS, 1995). Gibb (1973) reported that concrete-cased 36-inch inside diameter wells cost about $24/foot in 1978 ($88/ft in $2014), not including the cost for finishing the well top ($200 in 1978) or the cost of pumping.

Forests, wetlands, and prairies can help maintain natural rates of groundwater recharge and aquifer replenishment.

LondoĂąo and Ando (2013) found that residents of Champaign and Urbana, Illinois were each, on average, willing to pay up to $30/year to improve groundwater infiltration.

Figure 2. Aquifer level decline in the Chicago-Milwaukee region between 1864 and 1980 (USGS, 1995).

Woodlands/Forest

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ground through precipitation. A large tree can return 10 gallons of water a day to the atmosphere (Moore, 2002). Water evaporates more slowly from shaded forest soil than bare soil exposed to the sun.

The natural hydrologic cycle contrasts with what happens when impervious developed areas prevent water infiltration.

In fact, the U.S. Department of Agriculture, Natural Resources Conservation Service (NRCS) estimated that water runoff develops ten times faster on developed land as compared to unaltered landscape (Moore, 2002). The overwhelming majority of rainwater that falls on impervious land is therefore not retained. NRCS stated that the management of precipitation is a major factor in whether or not there is sufficient quantity and quality of drinking water (Moore, 2002).

Studies of desertification have shown that vegetation is a controlling factor in the exchange of water and energy between the land and the atmosphere and that large-scale deforestation dries up an area's climate (Moore, 2002). For example, a study in Brazil showed that forests returned three-fourths of rainfall to the atmosphere, with only one-fourth running into streams and rivers. When land is deforested, however, the ratio is roughly reversed, with a quarter of the rainfall returned to the atmosphere and three-quarters running quickly off the land (cited in Bacon, 2002).

Simulations by Tilley et al. (2012) showed that more water accumulated in forest soils than urban ones (1.59 cm vs. 0.87 cm). Forest stored 50% more water than urban land and allowed 34% more groundwater recharge. Land use was more important in determining sub-surface water storage than physiographic region. The public value of groundwater recharge by forests was $194/ac/year ($2000; $269 in $2014), and the fair payment price (if landowners were paid to retain forest for groundwater recharge) ranged from $6 to $58 per acre per year ($2000).

Streams and Lakes

Batker et al. (2010) reported water supply values of $2,105.11, $4,806.25, and $13,015.08/ac/year ($2006) for riparian buffers.

Batker et al. (2010) reported water supply values of $32.34; $429.30; $565.91; $617.46 and $834.44/ac/year ($2006) for rivers and lakes.

Wetlands

Wetlands act as reservoirs for the watershed, retaining water from precipitation, surface water, and groundwater (Osmond et al., 1995). Most wetlands release this water into connected surface water and groundwater. The effect of wetlands on groundwater recharge and discharge is variable. Some wetlands recharge groundwater, but most wetlands occur where water is discharging to the surface (Sather and Smith, 1984). Wetlands may recharge less than upland forest because of greater evapotranspiration and less permeable soils. Temporary or seasonal wetlands seem more likely to recharge than permanent or semi-permanent wetlands (Sather and Smith, 1984). Wetland features affecting groundwater recharge include hydroperiod, substrate, presence of surface outlets, the amount of edge, and type and amount of vegetation.

Mitsch and Gosselink (1993) reported that stream discharge during the spring from watersheds with 40% wetlands and lakes was 140% greater than watersheds without wetlands or lakes. Forested wetlands overlying permeable soil may release up to 100,000 gallons/ac/day into the groundwater (Osmond et al., 1995). Groundwater can be adversely affected by activities that alter wetland hydrology (Osmond et al., 1995). Drainage of wetlands lowers the water table and reduces the hydraulic head providing the force for groundwater discharge. If a recharge wetland is drained, this can change the hydrology of the watershed. For example, researchers at the University of Florida calculated that if 80% of a 5-acre cypress swamp were drained, available groundwater would be reduced by an estimated 45% (Osmond et al., 1995).

Water supply costs vary greatly from one source to another (California Dept. of Water Resources, 2005). For example, “typical” development costs for the following types of water supply options in California are: • Groundwater/conjunctive use: $150 - $500 per acre-foot • Brackish groundwater recovery: $500 - $1,000 per acre-foot Page 120 of 172

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• • •

Water recycling: $250 - $1,000 per acre-foot New reservoirs: $250 - $1,500 per acre-foot Seawater desalination: up to $2,000 per acre-foot

Often, the supply source is located away from the service area, thus transportation costs are also incurred. For the California State Water Project, transportation costs (capital and O&M) are over $170 per acre-foot to deliver water from the Sacramento-San Joaquin Delta to the metropolitan Los Angeles area. Once within the service area, additional local storage, delivery and treatment costs are incurred before final delivery to the water users (California Dept. of Water Resources, 2005).

A 1975 Massachusetts study cited by California Dept. of Water Resources (2005) concluded that an average acre of wetlands could supply water at a savings of $13,000 per year compared to other water sources ($2014).

A 1992 study estimated that an average acre of wetlands could provide 100,000 gallons per day at a rate of $16.56 per day less than water procured elsewhere (California Dept. of Water Resources, 2005). This savings translated to $9,320 in annual water supply per wetland acre ($2010; $10,190 in $2014) (California Dept. of Water Resources, 2005).

Prairie potholes and other wetlands can contribute significantly to recharging regional groundwater. 20% of wetland water storage can go into groundwater (Mitsch and Gosselink, 1993). Multiplying 20% of 1-1.5 million gallons/ac/year by $0.00331/gallon (approved 2014 water rate for the City of Chicago) gives $660-990/ac/year.

Using results from 39 studies, Woodward and Wui (2001) reported a water quantity value between $6/ac/yr and $2571/ac/yr (mean $127/ac/yr) by wetlands ($1990; $11-$4688 in $2014).

Batker et al. (2010) reported water supply values of $199.11; $542.65; $1,287.83; $2,001.85; $2,192.67; $3,598.28; $10,488.00; and $31,404.56/ac/year ($2006) for freshwater wetlands.

Spatial Assessments

MARC and AES (2013) assigned groundwater recharge values to areas based on soils, land cover, and geology. They assigned TR55 curve numbers based on both the land cover type and soil hydrologic group (following IDNR, 2009). They subtracted this from 100 and multiplied by the transmission rate of the surficial geological material.

Many aquifers in Illinois are confined, which means they cannot be recharged by surface water sources (IDNR, 2014).

The relative thickness of the loess soils generally does not allow water to penetrate down to or percolate up from, the water table (IDNR, 2014). Wetlands and other natural areas can only recharge groundwater supplies in recharge zones, where the substrate is permeable enough to allow an aquifer to be refilled by surface waters. This would have to be mapped as a mask to determine which areas this ecosystem service applies to.

References in this section

Bacon, T. 2002. Deforestation Decreases Rainfall. http://www.magicalliance.org/Forests/deforestation_decreases_rainfall.htm.

Batker, D., M. Kocian, B. Lovell, and J. Harrison-Cox. 2010. Flood protection and ecosystem services in the Chehalis River Basin. Earth Economics, Tacoma, WA. Baxter & Woodman, Inc., Ayres Associates, A. Visocky, Environmental Planning and Economics, Inc., and Planning and Management Consultants, Inc. 2006. County of McHenry, Illinois Groundwater Resources Management Plan. McHenry County Dept. of Planning & Development, Woodstock, IL. California Dept. of Water Resources. 2005. Multi-Objective Approaches to Floodplain Management on a Watershed Basis: Natural Floodplain Functions and Societal Values. Online at http://www.economics.water.ca.gov/studies.cfm. 34 pp.

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Dimick, D. 2014. If you think the water crisis can't get worse, wait until the aquifers are drained. National Geographic.

Aug. 19, 2014.

Gibb, J. P. 1973. Wells and pumping systems for domestic water supplies. ISWS-73-CIR117. Illinois State Water Survey, Urbana, IL. Illinois Department of Natural Resources (IDNR). 2009. Illinois Statewide Comprehensive Outdoor Recreation Plan 2009– 2014.

Illinois Department of Natural Resources (IDNR). 2014. Wetlands: ground water recharge. https://dnr.state.il.us/wetlands/ch2f.htm (Accessed 25 July, 2014) Londoño Cadavid, C. and A. W. Ando. 2013. Valuing preferences over stormwater management outcomes including improved hydrologic function. Water Resources Research 49(7):4114–4125.

Mid-America Regional Council (MARC) & Applied Ecological Services (AES). 2013. Kansas City Natural Resources Inventory II Phase 4: Ecosystem Services Method Development.

Mitsch, W. J., and J. G. Gosselink. 1993. Wetlands, 2nd edition. Van Nostrand Reinhold, New York.

Moore, T. (ed.) 2002. Protecting Maryland's Green Infrastructure. The case for aggressive public policies. Maryland Dept. of Natural Resources, Annapolis, MD. Natural Resources Conservation Service (NRCS). 2007. National Resources Inventory 2003 Annual NRI. Online at http://www.nrcs.usda.gov/.

Osmond, D.L., D.E. Line, J.A. Gale, R.W. Gannon, C.B. Knott, K.A. Bartenhagen, M.H. Turner, S.W. Coffey, J. Spooner, J. Wells, J.C. Walker, L.L. Hargrove, M.A. Foster, P.D. Robillard, and D.W. Lehning. 1995. Values of wetlands. Online at http://www.water.ncsu.edu/watershedss/info/wetlands/values.html.

Sather, J. H. and R.D. Smith. 1984. An overview of major wetland functions and values. U.S. Fish and Wildlife Service FWS/OBS-84/18. Washington, DC. Sasman, R. T., C. R. Benson, J. S. Mende, N. F. Gangler, and V. M. Colvin. 1977. Water-level decline and pumpage in deep wells in the Chicago Region, 1971-1975. SWS/CIR-125/77. Illinois State Water Survey, Urbana, IL. U.S. Geological Survey (USGS). 1995. Ground water atlas of the United States: Segment 10. Hydrologic Investigations Atlas 730-K. USGS, Reston, VA. Tilley, D., E. Campbell, T. Weber, P. May, and C. Streb. 2011. Ecosystem based approach to developing, simulating and testing a Maryland ecological investment corporation that pays forest stewards to provide ecosystem services: Final report. Department of Environmental Science & Technology, University of Maryland, College Park, MD. Woodward, R. T. and Y.-S. Wui. 2001. The economic value of wetland services: a meta-analysis. Ecological Economics 37:257-270.

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Carbon Storage

Detailed Literature Review The majority of scientists agree that global temperatures are rising due to human activities (e.g., Solomon et al., 2007), and the prognosis is grim if we do not act soon. We are already seeing the first effects of climate change, and by the end of the century, our planet could be a radically different place. Vegetation and soils can sequester carbon and thereby help to reduce atmospheric CO2 and global climate change.

Woodlands/Forest

The Stern Review (Stern, 2006) estimated that the economic costs of climate change would be at least 5-20% of global GDP. If current trends continue (using the Intergovernmental Panel on Climate Change (IPCC) A2 scenario – See IPCC, 2000), hurricane damage, real estate losses, energy costs, and water costs will cost the U.S. close to 2% of GDP, or $2 trillion ($2010) annually by 2100 (Ackerman and Stanton, 2008). Factoring in impacts to human and ecosystem health, the cost will be 3.6% of GDP (Ackerman and Stanton, 2008), or $3.6 trillion.

Forests help remove large amounts of CO2 from the air. During photosynthesis, trees convert CO2 into oxygen; carbon is also stored in the body of the tree, in the soil surrounding its roots, and in debris that falls to the ground. Larger and healthier trees sequester carbon at greater rates (Nowak et al., 2013). Barford et al. (2001) found a mean sequestration rate around 2.0 Mg C/ha/year for a mature northern red oak stand. While reforesting abandoned the land, restoring wetlands, and preserving natural areas help to reduce and maintain CO2 levels, developing these lands produces the opposite effect and increases CO2 by releasing previously stored carbon into the atmosphere (Strebel, 2002).

According to Strebel (2002), Maryland’s vegetation absorbs about 55 million Mg (MMT) of CO2 from the atmosphere annually through photosynthesis. About 20% of this net primary productivity (NPP), or 10.6 MMT, is permanently sequestered by wetlands or forests, with little to no sequestration by other land uses. Unmanaged forest stores about 24% of its NPP in large, long-term soil reservoirs. Disturbing mature forests frees this carbon. However, frequent harvesting in degraded areas, if good soil management practices are followed, can result in carbon sequestration both in the soil and in wood products.

Using Forest Inventory and Analysis (FIA) data, Industrial Economics (2011) reported that Delaware forest stores approximately 75 Mg/ha of aboveground carbon, 15 Mg/ha belowground (i.e., roots), and 60 Mg/ha in the soil.

Palustrine forested wetlands store approximately 75 Mg/ha of aboveground carbon, 15 Mg/ha belowground (i.e., roots), and 126 Mg/ha in the soil. Industrial Economics (2011) reported the median value of the social cost of carbon as $118 per Mg of carbon ($2010).

According to the U.S. Forest Service (Smith, J. E., et al., 2005), a 125-year old oak-hickory forest in the northeast U.S. contains 132.2 tons of carbon/acre. The forest in question would be older than this (~165 years) by 2100 if left undisturbed, and an estimate of 150 tons carbon/acre is reasonable. The IPCC A2 scenario (IPCC, 2000) projected 1,773 gigatonnes of carbon added to the atmosphere between 1990-2100. An acre of undisturbed oak-hickory forest would sequester 150 tons of this, contributing a reduction of approximately $300/ac/year ($2010; $330 in $2014) of climaterelated damages (using Ackerman and Stanton, 2008, estimates) by 2100.

Smith, P.D., et al. (2005) found that trees in Houston’s regional forests (8 counties) store 39.2 million tons of carbon, valued at $721 million based on 1994 marginal social cost estimates of $20.3 per metric ton. They sequester 1.6 million tons of carbon each year, at a value of $29 million (Smith, P.D., et al., 2005). Dividing by 2,152 mi2 (1,377,280 ac) of forest, this translated to $31/ac/year of forest ($2010). Using the more recent estimates of $49/ton of carbon ($2010) from Nordhaus (2011), this translated to $75/ac/year of forest ($2010; $82 in $2014). This value could be greater if Houston’s regional forests are allowed to mature, or are sustainably harvested and the wood products retained or buried (i.e., not burned or allowed to oxidize). Tree mortality, fire, and clearing will release carbon into the atmosphere.

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Mittman et al. (2014) reported that in Lancaster, PA, tree planting, and new green roofs would sequester approximately 34 million lbs of CO2/year. They averaged lower- and upper-bound carbon prices, using a value of $0.02308/lb; the total estimated benefit was, therefore, $786,000/year.

Batker et al. (2010) reported a gas and climate regulation value between $27.43/ac/yr and $623.33/ac/yr ($2006; $32$737 in $2014) for mid-seral forest and $99/ac/yr and $990/ac/yr ($2006; $117-$1,170 in $2014) for late-seral forest.

McPherson et al. (2006) reported that even in public areas like parks, large trees (example: hackberry, 40 years old) remove a net 1062 lbs/year of CO2 from the atmosphere. This includes both direct (sequestration minus decomposition and tree care-related emissions) and indirect (avoided power plant emissions) mechanisms. They used a value of $15/ton CO2 reduction, based on the average of high and low estimates by CO2e.com (2002). This website no longer exists. CNT (2010) used an average price of $0.00756/lb CO2 from the European Union's Emissions Trading System (EU ETS) as an example of a fully functioning carbon cap and trade market, and a value from Stern (2006) of $0.0386/lb CO2 that represents the economic impact of climate change. The ETS figure gives a value of $8/large tree/year ($2002), or $430/ac/year ($2014), although there is currently no carbon cap and trade system that covers Illinois. The avoided damages approach gives a value of $41/large tree/year ($2006), or $1,960/ac/year ($2014).

Based on 2007 data, Nowak et al. (2013) estimated trees in the seven-county Chicago region (including the city of Chicago) sequester about 677,000 tons of carbon per year (2.5 million tons per year of CO2) with an associated value of $14.0 million per year. Net carbon sequestration in the Chicago region is estimated at about 476,000 tons per year (1.7 million tons per year of carbon dioxide) based on estimated carbon loss due to tree mortality and decomposition. Given a tree area of 403,000 ac, the carbon sequestration value of forest and woodland was $35/ac/year ($2007; $40 in $2014).

The Conservation Fund (2013) used the Carbon On-Line Estimator (COLE; http://www.ncasi2.org/COLE/index.html; accessed Oct. 4, 2012) for the 13-county Houston-Galveston region. We aggregated plots across the region but separated out upland forest by physiography (class = “xeric” or “mesic” except for floodplains and bottomlands). To note, wetlands (class = “hydric”) did not have enough sample points. We filtered out “nonstocked” and “nonforest” plots. Using regression equations, mature upland forest (100 years after reforestation) in this region stores, on average, the following weight of carbon in its soil and vegetation components: • Loblolly pine: 181.46 Mg/ha (73.43 Mg/ac) • Loblolly pine/hardwood: 127.61 Mg/ha (51.64 Mg/ac) • Mixed upland hardwoods: 120.19 Mg/ha (48.64 Mg/ac) • Sweetgum/Nuttall oak/willow oak: 159.57 Mg/ha (64.58 Mg/ac)

We also aggregated plots (filtered as above) by county (if it had enough plots) or groups of counties: • Walker: 145.55 Mg/ha • Montgomery: 204.05 Mg/ha • Harris: 152.03 Mg/ha • Chambers and Liberty: 126.43 Mg/ha • Galveston, Brazoria, and Matagorda: 126.66 Mg/ha • Austin, Colorado, Wharton, Waller, and Fort Bend: 109.78 Mg/ha

Finally, we decided on a hybrid approach, splitting the study area into the Outer Coastal Plain and Southeastern Mixed Forest biotic provinces (231 and 232) vs. Prairie Parkland (255), using USFS ecological sections (232E, 232F, and 231E vs.

255C and 255D). We filtered out hydric, bottomland, nonstocked and nonforest plots. We crosswalked COLE forest types and National Land Cover Dataset (NLCD). All areas identified in the green infrastructure network design as bottomland forest received a value described in the next section. To note, we used all plots occurring in the study area. Three of the community types (sassafras/persimmon, sweetgum/yellow popular and elm/ash/black locust) may have been mischaracterized (pers. comm. Mickey Merritt 11/27/12 and 12/19/12), but since they were all aggregated (Tables 3 and 4), it would not have affected the calculations.

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Table 3. Carbon storage in Outer Coastal Plain and Southeastern Mixed Forest provinces: COLE forest type NLCD class Mg/ha Mg/ac Loblolly (n=104), shortleaf (n=4), or slash (n=2) Evergreen forest (42) 182.30 73.77 pine Lobolly pine/hardwood (n=37) Mixed forest (43) 139.31 56.38 Post oak/blackjack oak (n=6), (All other upland 147.21 59.57 Sassafras/persimmon (n=2), Sweetgum/yellow forest) poplar (n=5), Elm/ash/black locust (n=1), Mixed upland hardwoods (n=29)

Table 4. Carbon storage in Prairie Parkland province: COLE forest type NLCD class Mg/ha Mg/ac Loblolly (n=33) or shortleaf (n=1) pine Evergreen forest (42) 166.63 67.43 Loblolly pine/hardwood (n=13) Mixed forest (43) 113.61 45.98 Post oak/blackjack oak (n=8), White oak/red (All other upland 115.73 46.83 oak/hickory (n=1), Sassafras/persimmon (n=1), forest) Southern scrub oak (n=5), Mixed upland hardwoods (n=16)

We divided the estimated $3.6 trillion ($2010) annual price tag of increased greenhouse gas emissions in 2100 (Ackerman and Stanton, 2008) by the projected 1,773 gigatonnes of carbon added to the atmosphere between 1990 and 2100 (IPCC A2 scenario; IPCC, 2000). If the effect is linear (a simplifying assumption), each ton (Mg) of carbon emitted into the atmosphere is projected to cause $2 of damage annually. Thus, the values ranged from $94-148/ac/year of avoided climate-related damages.

The Conservation Fund (2013) used COLE (accessed Oct. 4, 2012) for the 13-county H-GAC region. We aggregated plots across the region but separated out bottomland forest by physiography. We filtered out “nonstocked” and “nonforest” plots. Using regression equations, mature bottomland forest (100 years after reforestation) in the Outer Coastal Plain and Southeastern Mixed Forest provinces stored 166.04 Mg/ha (67.19 Mg/ac) of carbon on average, and in the Prairie Parkland province, stored 129.99 Mg/ha (52.61 Mg/ac). At $2/Mg/year, this equates $105/ac/year of avoided climaterelated damages.

Wetlands

Wetlands are the most highly productive terrestrial ecosystems and do not turn over organic matter quickly, accumulating it in the soil or as peat. Thus, if undisturbed, they may sequester CO2 better than any other ecosystem type (Strebel estimated 50% of Net Primary Production – NPP, i.e. the production of organic compounds from atmospheric or aquatic carbon dioxide), although this depends on hydroperiod and other parameters. Wetlands with long periods of inundation are especially effective at storing carbon, in the form of peat.

Industrial Economics (2011) reported that vegetated estuarine wetlands (i.e. tidal marsh) stores approximately seven Mg/ha in plant biomass and 99 Mg/ha in the soil (total 43 Mg/ac), palustrine emergent wetlands store approximately 20 Mg/ha in plant biomass and 104 Mg/ha in the soil (total 50 Mg/ac); palustrine scrub-shrub wetlands store approximately 20 Mg/ha in plant biomass and 149 Mg/ha in the soil (total 68 Mg/ac); and palustrine forested wetlands store approximately 75 Mg/ha of aboveground carbon, 15 Mg/ha belowground (i.e., roots), and 126 Mg/ha in the soil (total 87 Mg/ac). They reported the median value of the social cost of carbon as $118 per Mg of carbon ($2010). Note that this is not a yearly rate.

Using $2/Mg/year from the Ackerman and Stanton (2008) and IPCC calculations, we estimated the values of avoided climate-related damages as $100/ac/year for emergent wetlands, $136/ac/year for scrub-shrub wetlands, and $175/ac/year for forested wetlands.

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Prairie/Grassland/Savanna

Industrial Economics (2011) reported that rangeland stores approximately 3 Mg/ha of aboveground carbon, 2 Mg/ha belowground (i.e., roots), and 73 Mg/ha in the soil. The median value of the social cost of carbon was $118 per Mg of carbon ($2010). This is not a yearly rate. At $2/Mg/year, the value is $63/ac/year ($2014).

Batker et al. (2010) reported a gas and climate regulation value of $3.85/ac/year ($2006; $4.55 in $2014) for grassland from Costanza et al., 1997.

Belowground Carbon

In a study to determine carbon (C) sequestration potential in the Midwest U.S., Fissore et al. (2010) reported mean C sequestration rates for restored prairie pothole wetlands of 3.1 Mg C/ha/ yr. De Luca (2011) remarked that 3-5 Mg C/ha is temporarily retained in the soil each year as metabolic carbon. Much is slowly transformed and eventually respired before the next growing season. The conversion of cropland to grassland on CRP lands results in carbon sequestration rates of 0.5–1 Mg/ha/yr (0.22–0.45 tons/ac/yr) (Follett et al., 2001). Gleason et al. (2008) said this was a conservative estimate.

Brye and Kucharik (2003) measured C sequestration at two prairie sites in Southern Wisconsin and found soil C concentration and content in the top 25 cm, averaged across restored and remnant prairies, were significantly higher (p < 0.001) in fine than coarse-textured soil. Soil C concentration ranged from 15.5 to 37.3 g/kg in the top 25 cm for the restored and remnant prairies at the fine-textured location, while soil C content ranged from 5.1 to 12.2 kg C/m2. Soil C concentration ranged from 5.6 to 12.2 g/kg in the top 25 cm for the restored and remnant prairies at the coarsetextured location, while soil C content ranged from 2.1 to 4.5 kg C/m2 (Brye and Kucharik, 2003).

According to Matamala et al. (2008), tallgrass prairie has 0.7-2.0 kg/m2 of C in root biomass. Decomposition of roots builds up carbon in the soil. Soil organic carbon (SOC) is depleted in plowed fields to the depth of plowing (top 25 cm).

Restoring prairie vegetation rebuilds organic matter in the surface soil. Prior studies cited by the authors reported SOC accumulations of 0.05-0.06 kg C/m2/year following grassland restoration.

Matamala et al. (2008) reported cumulative soil organic carbon to range around 11.6-21.9 kg C/m2 for remnant prairie.

Matamala et al. (2008) examined C and N stocks in cultivated land, restored prairie, and remnant prairie at Fermi National Accelerator Laboratory in Batavia, IL. They found that soil carbon increased at 0.043 kg C/m2/year during the first 26 years of restoration, should reach 50% of storage potential (~12 kg C/m2) in the first ~100 years, and 95% in 444 years. Belowground root mass accrued at 0.018-0.021 kg C/m2/year and was predicted to reach 50% of storage potential (~0.7 kg C/m2) in the first 11-15 years, and 95% in 46-64 years. Microbial biomass accrued at 0.005-0.009 kg C/m2/year and was predicted to reach 50% of storage potential (~0.3-0.7 kg C/m2) in the first 14-39 years, and 95% in 59-168 years.

Remnant prairie sites totaled ~13.5 kg C/m2 below ground (soil organic + roots + microbial).

Aboveground Carbon

Matamala et al. (2008) found that aboveground biomass for restored prairie accrued at 0.06 kg C/m 2/year, and reaches 50% of storage potential (0.76 kg C/m2) in the first 3 years, and 95% in 13 years.

Using the National Biomass and Carbon Dataset (Kellndorfer et al., 2012), we found that core prairies in the CMAP region average 2.25 metric tons of aboveground biomass per hectare, equivalent to approximately 1.125 metric tons of aboveground carbon.

Kucharik et al. (2006) compared the world’s oldest prairie restoration with an adjacent remnant in Southern Wisconsin and found the annual average aboveground net primary productivity (NPP) to be 271 ±51 and 330 ±55 g C/m2 respectively. Another study (Brye et al., 2002) reported NPP on a restored prairie (Goose Pond Sanctuary near Arlington, WI) of 2.6 Mg C/ha/yr.

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Gleason et al. (2008) found vegetable organic carbon in native prairie catchments to be 1.47 Âą 0.14 Mg/ha (0.66 Âą 0.06 Mg/ac).

Combining storages

We used the remnant prairie numbers from Matamala et al. (2008) since they were collected in the CMAP region. Total carbon varied 50-92 Mg/ac. At $2/Mg/year, the value is $100-$184/ac/year ($2014).

Spatial Assessments

In Table 5, Industrial Economics (2011) reported values for carbon storage by land cover type.

Table 5. Aboveground biomass, belowground biomass, and soil carbon storage for land cover types (Industrial Economics, 2011) Aboveground Belowground Soil carbon Cover type carbon (Mg/ha) carbon (Mg/ha) (Mg/ha) Built 0 0 39 Agriculture 10 5 55 Rangeland 3 2 73 Forest 75 15 60 Water 0 0 0 Bare Soil/Sand 0 0 41 Non-Vegetated Estuarine 3 4 158 Wetlands Vegetated Estuarine Wetlands 3 4 99 Palustrine Aquatic Bed Wetlands 20 (Included in 61 aboveground value) Palustrine Emergent Wetlands 20 (Included in 104 aboveground value) Palustrine Forested Wetlands 75 15 126 Palustrine Scrub-Shrub Wetlands 20 (Included in 149 aboveground value)

MARC and AES (2013) assigned ranks to land cover classes based on their ability to store carbon in the soil (Table 6).

Table 6. Ranks assigned by MARC and AES (2013) to land cover classes based on their ability to sequester carbon in the soil. 5 is the highest rank and 0 the lowest.

Land cover type Deciduous forest, Forested wetland Coniferous forest, Upland shrub-scrub Wetland shrub-scrub Herbaceous wetland, Grassland Cultivated, Buildings and Transportation, Barren, Water

Relative value 5 3 2 1 0

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the mature forest (assuming the forest would be allowed to reach maturity) as described previously. We did not attempt to model logging or other disturbances, which would release some carbon back into the atmosphere. We classified bottomland forest by ecoregion and assigned corresponding carbon values.

COLE had too few wetland plots in the study area, so for forested wetlands, we used the vegetation values for bottomland forest by ecoregion, and the soil value (126 Mg/ha) from Industrial Economics (2011). For other wetland types, we used vegetation and soil carbon values from Industrial Economics (2011; Table 7).

Table 7. Reported carbon storage by different classes of wetlands Industrial Economics (2011).

Vegetation carbon (tons/ha) 7 20 20 20 20 90 20

Soil carbon (tons/ha) 99 149 104 61 104 126 149

Total carbon (tons/ha) 106 169 124 81 124 216 169

Wetland type Estuarine emergent Estuarine scrub-shrub Lacustrine emergent Palustrine aquatic bed Palustrine emergent Palustrine forested Palustrine scrub-shrub

For prairie, the Conservation Fund (2013) assigned 78 Mg/ha of carbon storage as reported for rangeland by Industrial Economics (2011). Finally, we merged the values for wetland, forest, and prairie (with wetlands on top). We multiplied these by $2/Mg of avoided annual damage by 2100 to give $/ac/year. Values ranged from $63 to $195/year in $2010 for the year 2100. These values would be lower before 2100 and greater afterward.

References in this section

Ackerman, F., and E. A. Stanton. 2008. The cost of climate change: What weâ&#x20AC;&#x2122;ll pay if global warming continues unchecked. http://www.nrdc.org/globalwarming/cost/cost.pdf.

Barford, C. C., S. C. Wofsy, M. L. Goulden, J. W. Munger, E. H. Pyle, S. P. Urbanski, L. Hutyra, S. R. Saleska, D. Fitzjarrald, and K. Moore. 2001. Factors controlling long- and short-term sequestration of atmospheric CO2 in a mid-latitude forest.

Science 294:1688-1691.

Batker, D., M. Kocian, B. Lovell, and J. Harrison-Cox. 2010. Flood protection and ecosystem services in the Chehalis River Basin. Earth Economics, Tacoma, WA. Brye, K.R., S. T. Gower, J. M. Norman, and L. G. Bundy. 2002. Carbon budgets for a prairie and agroecosystems: effects of land use and interannual variability. Ecological Applications 12(4): 962-979.

Brye, K. R and C. J. Kucharik. 2003. Carbon and nitrogen sequestration in two prairie topochronosequences on contrasting soils in southern Wisconsin. American Midland Naturalist, 149(1):90-103.

Center for Neighborhood Technology (CNT). 2010. The value of green infrastructure: a guide to recognizing its economic, environmental and social benefits. Center for Neighborhood Technology, Chicago, IL. Conservation Fund, The. 2013. Houston-Galveston Green Infrastructure and Ecosystem Services Assessment.

Costanza, R., R. d'Arge, R. de Groot, S. Farber, M. Grasso, B. Hannon, K. Limburg, S. Naeem, R. O'Neill, J. Paruelo, R. Raskin, P. Sutton, and M. van den Belt. 1997. The value of the world's ecosystem services and natural capital. Nature 387:252- 259.

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DeLuca, T. H. and C. A. Zabinski. 2011. Prairie ecosystems and the carbon problem. Frontiers in Ecology and the Environment 9(7): 407-413.

Fissore, C., J. Espeleta, E. A. Nater, S. E. Hobbie, and P. B. Hobbie. 2010. Limited potential for terrestrial carbon sequestration to offset fossil-fuel emissions in the upper midwestern U.S. Frontiers in Ecology and the Environment 8(8):409-413.

Follett, R. F., E. G. Pruessner, S. E. Samson-Liebig, J. M. Kimble, and S. W. Waltman. 2001. Carbon sequestration under the Conservation Reserve Program in the historic grassland soils of the United States of America, in Lal, R., ed., Carbon sequestration and greenhouse effect. Soil Science Society of America, Special Publication No. 57, pp. 27â&#x20AC;&#x201C;40.

Gleason, R. A., M. K. Laubhan, and N. H. Euliss, Jr. (eds.). 2008. Ecosystem services derived from wetland conservation practices in the United States Prairie Pothole Region with an emphasis on the U.S. Department of Agriculture Conservation Reserve and Wetlands Reserve Programs: U.S. Geological Professional Paper 1745. 58 pp.

Industrial Economics, Inc. 2011. Economic valuation of wetland ecosystem services in Delaware: Final report. Delaware Department of Natural Resources and Environmental Control, Division of Water Resources, Dover, DE. Intergovernmental Panel on Climate Change (IPCC). 2000. Emissions Scenarios: Summary for Policymakers. ISBN: 929169-113-5. http://www.ipcc.ch/pdf/special-reports/spm/sres-en.pdf.

Kellndorfer, J., Walker, W., LaPoint, E., Bishop, J., Cormier, T., Fiske, G., Hoppus, M., Kirsch, K., and Westfall, J. 2012.

NACP Aboveground Biomass and Carbon Baseline Data (NBCD 2000), U.S.A., 2000. Data set. Available on-line [http://daac.ornl.gov] from ORNL DAAC, Oak Ridge, Tennessee, U.S.A. Kucharik, C. J., N. J. Fayram, and K. N. Cahill. 2006. A paired study of prairie carbon stocks, fluxes, and phenology: comparing the world's oldest prairie restoration with an adjacent remnant. Global Change Biology 12(1):122-139.

Matamala, R., J. D. Jastrow, R. M. Miller, and C. T. Garten. 2008. Temporal changes in C and N stocks of restored prairie: implications for C sequestration strategies. Ecological Applications 18(6):1470-1488.

McPherson, E., J. R. Simpson, P. J. Peper, S. L. Gardner, K. E. Vargas, S. E. Maco, and Q. Xiao. 2006. Midwest Community Tree Guide: Benefits, Costs, and Strategic Planting. General Technical Report PSW-GTR-199. United States Department of Agriculture, Forest Service, Pacific Southwest Research Station. Davis, CA. Mid-America Regional Council (MARC) & Applied Ecological Services (AES). 2013. Kansas City Natural Resources Inventory II Phase 4: Ecosystem Services Method Development.

Mittman, T., et. al. 2014. The economic benefits of green infrastructure: a case study of Lancaster, PA. EPA 800-R-14007. U.S. Environmental Protection Agency, Washington, DC. Nordhaus, W. 2011. Estimates of the Social Cost of Carbon: Background and Results from the RICE-2011 Model. Cowles Foundation for Research in Economics, Yale University, New Haven, CT. Nowak, D. J., R. E. Hoehn III, A. R. Bodine, D. E. Crane, J. F. Dwyer, V. Bonnewell, and G. Watson. 2013. Urban trees and forests of the Chicago region. Resour. Bull. NRS-84. U.S. Department of Agriculture, Forest Service, Northern Research Station, Newtown Square, PA. Smith, J. E., L. S. Heath, K. E. Skog, and R. A. Birdsey. 2005. Methods for Calculating Forest Ecosystem and Harvested Carbon with Standard Estimates for Forest Types of the United States. U.S. Dept. of Agriculture Forest Service, Northeastern Research Station, General Technical Report NE-343. http://www.treesearch.fs.fed.us/pubs/22954.

Smith, P. D., M. Merritt, D. Nowak, and D. Hitchcock. 2005. Houstonâ&#x20AC;&#x2122;s Regional Forests. Texas Forest Service.

Stern, N. 2006. Stern Review on The Economics of Climate Change. HM Treasury, London, UK. Page 129 of 172

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Strebel, D. E. 2002. Carbon sequestration potential in Maryland (draft version). Versar, Inc., prepared for Maryland Dept.

Nat. Res., Annapolis, MD. Soil Survey Staff. Gridded Soil Survey Geographic (gSSURGO) Database for State name. United States Department of Agriculture, Natural Resources Conservation Service. Available online at https://gdg.sc.egov.usda.gov/. Month, day, year (FYyear official release).

Soil Survey Staff. National Value Added Look Up (valu) Table Database for the Gridded Soil Survey Geographic (gSSURGO) Database for the United States of America and the Territories, Commonwealths, and Island Nations served by the USDA-NRCS. United States Department of Agriculture, Natural Resources Conservation Service. Available online at https://gdg.sc.egov.usda.gov/. Month, day, year (FYyear official release).

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Air Purification

Detailed Literature Review Woodlands/Forest

Trees provide air quality benefits by absorbing sulfur dioxide (SO2) and nitrogen oxide (NO2), two major components of acid rain (American Forests, 1999). In addition, trees can trap ozone, carbon monoxide, and particles in the air, all of which can be harmful to humans (American Forests, 1999). Mechanisms for trees removing pollutants from the air include absorption through leaf stomata (i.e. pores for gaseous exchange) and interception by leaves. The forest soil is also a large and important sink for many air pollutants. This ecosystem service is especially important because of the immediate human health effects.

According to a study by American Forests (1999), trees in the Baltimore-Washington urban corridor removed 34 million pounds of air pollutants in 1997, at a value of $114 million per year ($2010). With 555,090 acres of trees in this area, this translates to a benefit of $206/ac of trees. Tilley et al. (2012) found that ozone was the highest valued pollutant removed by forest in Maryland, at $48/ac/year ($2000; $66 in $2014).

McPherson et al. (2006) reported that a single large tree (hackberry, 47 ft tall, 37 ft spread, 40 years old) could annually uptake 0.72 lbs. of O3 and uptake and avoid 1.59 lbs. of NO2, 0.98 lbs of SO2 and 0.81 lbs of PM10 particulates. For the city of Chicago, Wang et al. (1994) reported the control costs of NOx to be $7,990/ton, ROG $8,150/ton, PM10 $4,660/ton, SOx $9,120/ton, and CO $2440/ton (1989 dollars). Following McPherson et al. (2006), we used control costs to estimate willingness to pay for air-quality improvements (instead of using damage costs, also reported by Wang et al, 1994). CNT (2010) gave a value for O3 equivalent to NO2. Combining and converting to 2014 dollars, this gives an air pollution control value of $29.93/tree/year, or $1,213/ac/year.

Based on 2007 data, Nowak et al. (2013) estimated trees in the seven-county Chicago region (including the city of Chicago) removed 18,080 tons of air pollution (CO, NO2, O3, PM10, SO2) per year with an associated value of $157 million ($2007). They based the dollar figure on 2007 national median externality costs associated with pollutants. Shrub cover in the Chicago region removed an additional estimated 6,090 tons per year, worth $46 million/year. Given an area of 2,602,000 ac, 15.5% tree cover, and 5.5% shrub cover, trees removed $340/ac/year and shrubs $321/ac/year ($2007).

Converting to 2014 dollars, Chicago-area trees remove $390/ac/year and shrubs $368/ac/year.

Spatial Assessments

MARC and AES (2013) assigned ranks to land cover classes based on their ability to remove NOx and SO2 from the air (Table 10). Maes et al. (2011) reported removal rates of NOx and SO2 (reported by MARC and AES (2013) in lbs/ac/yr).

Table 10. Ranks assigned by MARC and AES (2013) to land cover classes based on their ability to remove NOx and SO2 from the air. 5 is the highest rank and 0 the lowest.

Land cover type Relative value Upland Deciduous Forest, Lowland Deciduous 5 Forest Mixed Forest 4.5 Coniferous Forest 3 Shrub-scrub 2 Herbaceous, Cultivated 1 Impervious Buildings, Impervious Other, Barren, 0 Water

The Conservation Fund (2013) assigned the value of $312/ac/year (from Smith et al., 2005) to all forest cells. We recommended that more sophisticated studies attempt to differentiate the air quality value of forests based on their location in urban or rural areas or in relationship to the location of point and nonpoint air pollution sources.

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References in this section

American Forests. 1999. Regional ecosystem analysis: Chesapeake Bay region and the Baltimore-Washington corridor.

American Forests, Washington, DC. Center for Neighborhood Technology (CNT). 2010. The value of green infrastructure: a guide to recognizing its economic, environmental and social benefits. Center for Neighborhood Technology, Chicago, IL. Conservation Fund, The. 2013. Houston-Galveston Green Infrastructure and Ecosystem Services Assessment.

McPherson, E., J. R. Simpson, P. J. Peper, S. L. Gardner, K. E. Vargas, S. E. Maco, and Q. Xiao. 2006. Midwest Community Tree Guide: Benefits, Costs, and Strategic Planting. General Technical Report PSW-GTR-199. United States Department of Agriculture, Forest Service, Pacific Southwest Research Station. Davis, CA. Mid-America Regional Council (MARC) & Applied Ecological Services (AES). 2013. Kansas City Natural Resources Inventory II Phase 4: Ecosystem Services Method Development.

Nowak, D. J., R. E. Hoehn III, A. R. Bodine, D. E. Crane, J. F. Dwyer, V. Bonnewell, and G. Watson. 2013. Urban trees and forests of the Chicago region. Resour. Bull. NRS-84. U.S. Department of Agriculture, Forest Service, Northern Research Station, Newtown Square, PA. Smith, P. D., M. Merritt, D. Nowak, and D. Hitchcock. 2005. Houstonâ&#x20AC;&#x2122;s Regional Forests. Texas Forest Service.

Tilley, D., E. Campbell, T. Weber, P. May, and C. Streb. 2011. Ecosystem based approach to developing, simulating and testing a Maryland ecological investment corporation that pays forest stewards to provide ecosystem services: Final report. Department of Environmental Science & Technology, University of Maryland, College Park, MD. Wang, M. Q., D.J. Santini, and S.A. Warinner. 1994. Methods of valuing air pollution and estimated monetary values of air pollutants in various U.S. regions. Center for Transportation Research, Energy Systems Division, Argonne National Laboratory, Argonne, IL. Native Flora and Fauna

Detailed Literature Review

All ecosystems can be visualized as a web of materials and organisms, interconnected by flows and transformations of energy, matter, and information. Each native species is uniquely adapted to transform and channel energy in an ecosystem, and each plays a role in ecosystem functioning. Ecosystems with higher diversity are generally more efficient. For example, diverse communities are more likely to contain species able to utilize different amounts and combinations of limiting resources like nutrients or light; and more likely to have symbiotic relationships. As species are lost from an ecosystem, those that depend on them for food, pollination, or other needs, also begin to disappear. Many interconnections between species are not even known (witness the difficulty of multi-species fishery management, for example). Ecosystem resistance and resilience to stresses is dependent on species composition and diversity. Diverse communities are more likely to contain species tolerant to disturbances like flooding, drought, or pests. The spread of pests is quicker among spatially contiguous hosts. Monocultures like corn or wheat fields are more susceptible to disease or pest outbreaks than diverse systems and have to be maintained with intense management. Ecosystems with low diversity, like islands or agricultural fields, are also more susceptible to invasion by exotic or weedy species, because of empty niches (Weber, 2003).

Top predators are especially important because they act as ecosystem regulators (Soule and Terbough, 1999). In their absence, trophic structures can become destabilized, with consumers and mesopredators becoming more abundant, and floral recruitment and diversity decreasing (Soule and Terbough, 1999). The loss of top carnivores like cougar and wolves, along with increased edge habitat, has led to an overpopulation of white-tailed deer in many areas. Exceeding the regional carrying capacity, deer over-browse tree seedlings, and herbs. The native herbs are often replaced by exotic Page 132 of 172

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invasives like Japanese stilt grass (Microstegium vimineum) or garlic mustard (Alliaria petiolata), which the deer tend to avoid. The decreased plant diversity, in turn, affects animals dependent on them for food or cover.

The loss of species impacts the functional capacity of the ecosystem to provide services valued by humans. For example, recruitment of oaks has suffered as uncontrolled populations of deer preferentially browse on oak seedlings. Maples, sweetgum, and tulip poplar dominate many Maryland forests, which also have less food value to wildlife than oaks and hickories (Weber, 2007b). As illustrated by a bee study in Costa Rica, biodiversity provides protection from fluctuations, whereas reliance on a single species, domestic honeybees, has left farmers at risk of losing their crops. In another example, Madritch and Hunter (2002) found that intraspecific tree diversity, as expressed in varying leaf litter chemistry, could affect the ecosystem processes of carbon and nitrogen cycling.

One of the greatest values of biodiversity might be a capacity to adapt to change, such as global warming. Another value is the mostly untapped potential of species and genes to tailor crops, cure diseases, and provide other vital services. All of our food crops have their roots in wild species. Wild rice, for example, is an invaluable source of new genetic material for developing disease resistance in one of the world's most important crops.

Host-plant resistance (HPR) is widely used in agriculture to combat pests and diseases because it significantly reduces the need for pesticides, which are both expensive and environmentally destructive. In the wild, all plant species rely on HPR characteristics such as thorns, hairs, coatings, chemicals, and other repellants (Pimentel, 1998). A single tree may contain 1,000 different chemicals (Pimentel, 1998). Such traits can be transferred to cultivated crops. In fact, the vast majority of crops contain some degree of HPR, increasing yields and economic returns (Pimentel, 1998). Pimentel (1998) reported that this saves $80 million per year in potential losses to pests and pathogens in Maryland ($2006) and that the benefits of using HPR nationwide are about $300 for every $1 spent on research and development. The Ramsar Convention on Wetlands (2000a) reported that the value of wild plant traits on a global scale is in the billions of dollars globally.

Pests and diseases often evolve tolerance to crop resistance factors (Pimentel, 1998). A typical lifespan of a commercially bred crop variety has been estimated at 5-10 years before the new genetic material is required to combat pest and disease problems (Ramsar Convention on Wetlands, 2000a). This means new forms of genetic resistance must continue to be identified and obtained from plants in natural ecosystems (Pimentel, 1998).

Over 20,000 medicinal plant species are currently in use, and over 80% of the worldâ&#x20AC;&#x2122;s population depends on traditional medicine for their primary health care needs (Ramsar Convention on Wetlands, 2000a). Roughly half of all prescription medicines are derived from natural sources, not to mention vitamins and herbal supplements. In the U.S., prescription drugs linked to discoveries made in nature have an economic value of $80 billion (Jenkins and Groombridge, 2002b).

Research on a South American clawed toad revealed that chemicals in its skin have potential as antibiotics, fungicides and anti-viral preparations (Ramsar Convention on Wetlands, 2000a). The blood of horseshoe crabs contains a compound used by the pharmaceutical industry to test the purity of drugs and medical equipment that holds human blood (Ramsar Convention on Wetlands, 2000a). However, only a small percentage of species have been examined for potential pharmaceutical applications: less than 1% of the world's 250,000 tropical plants have been screened, for example (Jenkins and Groombridge, 2002). And unfortunately, at current extinction rates of plants and animals, Earth is losing a major drug every two years (Jenkins and Groombridge, 2002). Fowler (2006) writes,

â&#x20AC;&#x153;Increased interest in plants as a source of novel pharmacophores recognizes their chemical diversity and versatility, not matched by synthetic chemistry libraries. In spite of the surge of activity in synthetic chemistry over the last 20 years or so, almost half the some 850 small molecules introduced as drugs were derived from plant sources. Over 100 small molecules derived either directly or indirectly from plants are currently at some point in the clinical trials process. It is argued that the present use of plant-derived drugs and remedies only scratches the surface of what is a major reservoir of untapped potential, the level of biological and chemical diversity possessed by plants having much to offer in the drive for novel therapeutic agents in the fight against the disease.â&#x20AC;?

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Biological diversity and genetic information are not easy to translate into dollar terms. Aside from contributing to other ecosystem functions and values, species and genotypes found in Illinois have unknown potentials for agricultural, pharmaceutical, and biotechnology advances. Illinois supports globally rare species, which are a logical starting point for protecting such a legacy. Since species are irreplaceable once extinct, this should be a constraint on economic activity rather than something to trade off, with a goal to ensure their long-term survival as an investment for future generations. Just as we preserve scientific, engineering, and cultural knowledge in libraries, one could argue we should preserve our world’s genetic library.

In a 2008 survey, 84.6% of Illinois residents thought, "more wildlife habitat should be protected and restored" (IDNR, 2009). 80.6% thought, "More high-quality undisturbed prairie, forest, and wetlands should be acquired/protected."

Londoño and Ando (2013) found that residents of Champaign and Urbana, Illinois were each, on average, willing to pay over $18/year to improve fish habitat.

Woodlands/Forest

Batker et al. (2010) reported habitat values of $269.85; $452.57; and $500.24/ac/year ($2006) for forest. This translates to $319, $535, and $591/ac/year in $2014.

Streams and Lakes

Batker et al. (2010) reported habitat values of $58.89; $269.91; and $500.24/ac/year ($2006) for riparian buffers. This translates to $70, $319, and $591/ac/year in $2014.

Batker et al. (2010) reported habitat values of $17.13, $58.89; $269.91; and $1,479.84/ac/year ($2006) for lakes and rivers. This translates to $20, $70, $319, and $1,749/ac/year in $2014.

Wetlands

Batker et al. (2010) reported habitat values of $58.89; $269.91; $1,479.84; $5,147.20; and $12,537.14/ac/year ($2006) for freshwater wetlands. This translates to $70, $319, $1,749, $6,083, and $14,816/ac/year in $2014.

Using results from 39 studies, Woodward and Wui (2001) reported a wildlife habitat value between $95/ac/yr and $981/ac/yr (mean $306/ac/yr) for wetlands ($1990; $173-$1,789 in $2014).

Spatial Assessments

Large contiguous blocks of natural land are more likely to contain fully functioning ecosystems (e.g., MacArthur and Wilson, 1967; Forman and Godron, 1986; Weber, 2007a), and provide corresponding benefits to humans. Smaller, fragmented ecosystems are more likely to be impaired (Weber et al., 2004, p.59; Weber, 2007b). Retaining connectivity, as appropriately sited and configured corridors can accomplish, can help to offset some of the functional losses caused by fragmentation (e.g., Anderson and Danielson 1997, Beier and Noss 1998, Bennett 1998, Söndgerath and Schröder 2002).

Kozak et al. (2011) reported a study showing that wetland improvements in California to support salmon populations decayed exponentially with a 472 km half-life, a much more gradual decline than the UK case.

MARC and AES (2013) assigned qualitative values for support of native wildlife species diversity at a regional scale, especially of area-sensitive and specialist species. They derived the values from land cover class, polygon size, and distance to roads. First, they weighted land cover class as likely to support area-sensitive and specialist species, with natural communities given a score = 5, grassland = 2, cultivated land = 1 and impervious cover and barren land = 0. They scaled habitat patch size and distance to roads geometrically (Table 8).

Table 8. Patch size and distance from roads vs. wildlife support (MARC and AES, 2013).

Wildlife Group Habitat Patch Road Distances Page 134 of 172

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Size (acres) Area-Sensitive & Specialist Wildlife >1,000 Intermediate Conditions 101-1000 Generalist Wildlife 11-100 Low Habitat Integrity ≤10

(meters) >400 41-400 5-40 ≤4

References in this section

Anderson, G. S., and B. J. Danielson. 1997. The effects of landscape composition and physiognomy on metapopulation size: the role of corridors. Landscape ecology 12:261-271.

Batker, D., M. Kocian, B. Lovell, and J. Harrison-Cox. 2010. Flood protection and ecosystem services in the Chehalis River Basin. Earth Economics, Tacoma, WA. Beier, P., and R. F. Noss. 1998. Do habitat corridors provide connectivity? Conservation Biology 12(6):1241-1252.

Bennett, A. F. 1998. Linkages in the landscape: the role of corridors and sensitivity in wildlife conservation. IUCN, Gland, Switzerland and Cambridge, UK. Forman, R. T. T., and M. Godron. 1986. Landscape Ecology. John Wiley and Sons, New York, NY. Illinois Department of Natural Resources (IDNR). 2009. Illinois Statewide Comprehensive Outdoor Recreation Plan 2009– 2014.

Jenkins, M. D., and B. Groombridge. 2002. World Atlas of Biodiversity: Earth's Living Resources in the 21st Century.

University of California Press.

Kozak, J., C. Lant, S. Shaikh, and G. Wang. 2011. The geography of ecosystem service value: The case of the Des Plaines and Cache River wetlands, Illinois. Applied Geography 31:303-311.

Londoño Cadavid, C. and A. W. Ando. 2013. Valuing preferences over stormwater management outcomes including improved hydrologic function. Water Resources Research 49(7):4114–4125.

MacArthur, R. H. and E. O. Wilson. 1967. The theory of island biogeography. Princeton University Press, Princeton, NJ. Madritch, M. D., and M. D. Hunter. 2002. Phenotypic diversity influences ecosystem functioning in an oak sandhills community. Ecology 83(8):2084-2090.

Mid-America Regional Council (MARC) & Applied Ecological Services (AES). 2013. Kansas City Natural Resources Inventory II Phase 4: Ecosystem Services Method Development.

Pimentel, D. 1998. Economic and environmental benefits of biological diversity in the state of Maryland. pp. 63-75 in Therres, G. D. (ed.) Conservation of biological diversity: a key to the restoration of the Chesapeake Bay ecosystem and beyond. Maryland Dept. Nat. Res., Annapolis, MD. Ramsar Convention on Wetlands. 2000a. Reservoirs of biodiversity. Ramsar Convention Bureau, Gland, Switzerland.

Ramsar Convention on Wetlands. 2000b. Wetland values and functions. Ramsar Convention Bureau, Gland, Switzerland.

Söndgerath, D., and B. Schröder. 2002. Population dynamics and habitat connectivity affecting the spatial spread of populations - a simulation study. Landscape ecology 17:57-70.

Soule, M. E., and J. Terbough. 1999. Continental conservation: scientific foundations of regional reserve networks. Island Press, Washington, DC. 227 pp.

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Weber, T. 2003. Marylandâ&#x20AC;&#x2122;s green infrastructure assessment: a comprehensive strategy for land conservation and restoration. Maryland Dept. Nat. Res., Annapolis, MD. 246pp. plus appendices.

Weber, T. 2007a. Development and application of a statewide conservation network in Delaware, U.S.A. Journal of Conservation Planning 3:17-46.

Weber, T. 2007b. Ecosystem services in Cecil Countyâ&#x20AC;&#x2122;s Green Infrastructure: Technical Report for the Cecil County Green Infrastructure Plan. The Conservation Fund, Annapolis, MD. Weber, T., J. Wolf, P. Blank, R. Aviram, and J. Lister. 2004. Restoration targeting in Maryland's Green Infrastructure.

Maryland Dept. Nat. Res., Annapolis, MD. Woodward, R. T. and Y.-S. Wui. 2001. The economic value of wetland services: a meta-analysis. Ecological Economics 37:257-270.

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Recreation and Ecotourism

Detailed Literature Review

A study by Balmford et al (2002) reported that the economic value of retaining Canadian freshwater marshes for hunting, angling, and trapping was 60% greater than the value derived from converting them to agriculture. This did not include other values such as nutrient cycling, water regulation, and peat accumulation.

The demand for outdoor recreation in the United States has greatly outpaced population growth. Nationally, more than half of all adults hunt, fish, birdwatch or photograph wildlife, spending $59.5 billion annually (Sipple, 2007). Naturerelated recreation is the fastest growing sector of the tourism industry (Sipple, 2007). Visits to national parks jumped 134% between 1965 and 2000, to 284.1 million (McQueen, 2001). Visits to national forests and wildlife refuges have also increased dramatically. Bird watching is the fastest growing outdoor activity, tripling from 1982-83 (21 million participants) to 1997 (63 million) (Sipple, 2007). Nationally, 24.7 million people took trips away from home in 1991 to partake in birding, spending $5.2 billion in goods and services, generating 191,000 jobs, and bringing governments more than $895 million in sales and income tax revenues (Sipple, 2007).

Other fast-growing activities include hiking, backpacking, and camping. In 1993, the 273 million visitors to national parks created more than $10 billion in direct and indirect expenditures, and generated more than 200,000 jobs (McQueen, 2001). The National Park Serviceâ&#x20AC;&#x2122;s operating budget was $1 billion in 1993, bringing taxpayers a 10 to 1 return on their investment (McQueen, 2001). Boating, canoeing, and rafting are popular activities. A 1990 study of whitewater rafters on the Youghiogheny River in Garrett County, Maryland, found that they contributed nearly $1.2 million dollars to the local economy (Klapproth and Johnson, 2001). This included money paid to local rafting companies, lodging, food and beverages, entertainment, souvenirs, boating equipment, and auto-related items (Klapproth and Johnson, 2001).

Hunting and fishing continue to be popular activities. In 1991, 3 million migratory bird hunters generated $1.3 billion in retail sales, with a total economic multiplier effect of $3.9 billion, associated with 46,000 additional jobs and sales and income tax revenues of $176 million (Sipple, 2007). In many states, the opening of deer season is one of the most anticipated days of the year.

In a 2000 study, researchers found that when previously inactive adults incorporated moderate physical activity into their routines, annual mean medical expenditures were reduced by $865 per person (CNT, 2010).

A survey by USFWS and USCB (2014) revealed that in 2011, 3.8 million persons 16 years old and older engaged in fishing, hunting, or wildlife-watching activities in Illinois. Of these, 1.0 million fished, 512 thousand hunted, and 3.0 million (the majority) participated in passive observing, feeding, and photographing wildlife. In the same year, state residents and nonresidents spent $3.8 billion on wildlife-associated recreation in Illinois.

In 2011, residents and non-residents spent 13.3 million days and $973 million fishing in Illinois, presumably most of this in publicly accessible water bodies (USFWS and USCB, 2014). This data excluded Lake Michigan, from which inadequate data existed.

Charbonneau and Caudill (2010) reported an economic multiplier (i.e., including indirect sales stimulated by the direct sales) of 1.72 for trout fishing. Multiplying this by $973 million gives $1.674 billion/year.

Residents and non-residents spent 7.8 million days and $1,216 million hunting (USFWS and USCB, 2014). Of this, $274 million was spent on trip-related expenses, $303 million on equipment, and $573 million on magazines, books, and DVDs, membership dues and contributions, land leasing and ownership, and licenses, stamps, tags, and permits. Most of the time (around 90%) was spent on private land. Of trip-related and hunting equipment expenses ($516 million), 68% was spent hunting big game (primarily deer, with wild turkey a distant second), 21% hunting small game (primarily pheasant, with squirrel hunted half as often), and 11% hunting migratory birds (waterfowl and doves; presumably mostly ducks).

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In 2001, hunters spent $451 million in Illinois (IAFWA, 2002). The total economic multiplier effect was $949 million.

Using the same multiplier for 2011 gives $2,559 million. In 2001, Illinois had 310,458 hunters (mostly for deer) that spent 4.5 million days hunting.

Residents and non-residents spent 6.4 million days watching wildlife away from their home and spent $166 million on trip-related expenditures alone (i.e., excluding equipment) (USFWS and USCB, 2014). Total equipment expenditures, excluding bird food, plantings, birdhouses, etc. were $817 million. Since around 37% of wildlife watchers visited parks or natural areas (either away from home or within a mile of their home), we estimated equipment expenditures of $300 million to visit natural areas to view wildlife. Adding this to $166 million in trip-related expenditures gives $466 million.

The economic multiplier for bird watching was 2.61 (Carver, 2013); Trip and equipment expenditures of $41 billion in 2011 generated $107 billion in total industry output across the United States.

In 2006, there were 257,250 visits to the Minnesota Valley National Wildlife Refuge in Bloomington, MN. Almost all visits were for non-consumptive recreation; primarily trail use, birding, and observation platforms (Fermata, Inc., 2010).

Residents (within 30 miles of the refuge) accounted for 80% of all visitations. Total visitor recreation expenditures in 2006 were $1.3 million, with non-residents accounting for 51% of the total expenditures. The total economic effect was $1.48 returned for every $1 in budgeted expenditures (Fermata, Inc., 2010).

In a 2008 survey, 58.2% of Illinois residents spent time observing birds and other wildlife in 2008 (IDNR, 2009). Of these, 54.7% did so away from home: 6.3% in private areas, 25.8% in city or county parks, 18.4% in state parks, and 4.2% in national parks or areas. 45.4% of residents spent time fishing, primarily at state parks. Fishing and hunting ranked first and second as outdoor activities that rural respondents wanted to start or participate in more often. Over half of the respondents (50.7%) indicated that if lands and facilities were more conveniently located, they might engage in outdoor activities more often (IDNR, 2009).

In the same survey, 97.5% of Illinois residents thought outdoor recreation areas are important for health and fitness (IDNR, 2009). 93.6% thought community recreation areas are important for quality of life and promote economic development. 80.3% thought, "More lands should be acquired for open space and/or for outdoor recreation."

In Illinois, state, local, and federal governments spent $1,529,117,770 on land conservation between 1998 and 2011, conserving 216,066 acres of land. In that same period, referendums approved $1,261,809,549 for land preservation (Trust for Public Land, 2013). On average, 53% of people voting on 70 separate referendums voted for spending new money on land preservation.

In Iowa, more than 25 million visits were made to state parks and lakes and 23 million to county parks each year (Otto et al., 2007). This did not include visits to city parks, state forests and preserves, and river-based activities. For lakes, state parks, county park, and trails, Otto et al. estimated spending levels of $2.63 billion and 50 million visits. With secondary or multiplier effects included, more than 27,400 jobs and $580 million in income were generated annually. The economic surplus exceeded $1.1 billion annually beyond this.

In Iowa and Michigan, most visitors to state parks live within 30 miles of the park (Otto et al., 2007). Stynes (1998) estimated per party spending in Michigan state parks at $76 for camping, $38 for day trips, and $110 for trips including hotel stays ($1997). In SW Michigan, the region closest to NW Indiana, the average party size was 3, 8% of visitors were campers, 64% were day visitors, and 28% stayed in hotels (Stynes, 1998). Combining, average per party expenditures were $76*.08 + $38*.64 + $110*.28 = $61.20. Per person, this was $20.40. Converting to $2014, this was $30/person/visit.

A 1999â&#x20AC;&#x201C;2000 study of visitors to Saylorville Lake, Iowa, estimated $45.53 per party for camping and $41.77 per party for day trips (Otto et al., 2007). A 2002 survey of users of Iowa lakes conducted estimated $43 per party for day visitors and $97 per day for overnight visiting parties (Otto et al., 2007). Otto et al. (2007) estimated $748 million ($2006) spending by day and overnight visitors in Iowa state parks, which totaled 89,318 acres. 95% of the expenditures were for day trips.

Including secondary effects as money is recirculated, an estimated $1.185 billion ($2006) of margined sales, $325 million Page 138 of 172

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value added to GDP, 8,787 jobs and $185.9 million of personal income were directly or indirectly linked to recreational spending at Iowa’s state parks.

Otto et al. (2007) estimated 23.7 million annual visits to Iowa county parks, which totaled 176,385 acres of land and facilities. They estimated expenditures at half the amount for state parks, totaling $600 million. Including secondary effects, an estimated $946 million ($2006) of margined sales, $260 million value added to GDP, 7,024 jobs and $148.6 million of personal income were directly or indirectly linked to recreational spending at Iowa’s county parks.

Otto et al. (2007) estimated 1.37 million people used the 57 trails in Iowa, which totaled 890 miles. Related expenditures on food, beverages, etc. were $8 per person, totaling $10.9 million ($2006). Including secondary effects, an estimated $17.3 million ($2006) of margined sales, $4.7 million value added to GDP, 128 jobs and $2.7 million of personal income were directly or indirectly linked to using Iowa trails.

Otto et al. (2007) estimated 9.4 million day visits and 5.9 million overnight visits to the 132 natural and manmade lakes in Iowa, which covered 324,000 acres of surface area. Based on a 2002 survey at Storm Lake and Rock Creek Lake, Iowa, they estimated expenditures of $43 by day visitors and $97 by overnight visitors, totaling $977 million ($2006). Including secondary effects, an estimated $1.548 billion ($2006) of margined sales, $425 million value added to GDP, 11,479 jobs and $243 million of personal income were directly or indirectly linked to recreational spending at Iowa lakes.

Otto et al. (2007) estimated the benefit from fishing and wildlife recreation activities along the Mississippi River (312 miles of coastline) to be $36.4 million in expenditures, $44.5 million added to GDP, 534 jobs and $9.75 million in personal income. No surveys were done of Iowa’s interior rivers.

The consumer surplus value, or net economic benefit, is the difference between the amount an individual would be willing to pay to enjoy a particular non-market amenity versus the actual costs incurred to obtain or enjoy that amenity (Otto et al. 2007). For the Northeast U.S., a large region that included Illinois, Loomis (2005) reported an average consumer surplus value per person per day of $34.86 for bird watching, $33.11 for camping, $32.60 for fishing, $88.32 for rafting and canoeing, $42.60 for going to the beach, $75.18 for hiking, $47.45 for hunting, $22.21 for swimming, and $31.30 for wildlife viewing ($2004). Otto et al. (2007) extrapolated this data to Iowa, reporting a net annual economic surplus of $219 million for fishing, $198 million for hunting, $134 million for wildlife viewing, and $39 million for rails-totrails recreation. For all categories, the total was more than $1.1 billion ($2006).

In 2009-10 surveys Indiana DNR (2012), asked how much money they were willing to spend per year on their favorite outdoor recreation activity (including cost of equipment, training, travel, etc.), respondents said: • <$100

21% • $101–$250 19% • $251–$500 19% • $501–$750 11% • $751–$1000 8% • >$1000

12% Using the midpoint of these ranges, with $1000-1250 as the highest range (a conservative estimate), the average response was $389/year.

Asked how far they were willing to travel one way to participate in their favorite outdoor recreation activity, respondents said: • 0-5 miles

10% • 6-10 miles 8% • 11-15 miles 6% • 16-25 miles 9% • 26-35 miles 8% • 36-50 miles 17% • 51-75 miles 10% • 76-100 miles 7% Page 139 of 172

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â&#x20AC;˘ >100 miles 21%

According to the Business Analyst Online database (https://bao.arcgis.com/esriBAO/index.html; retrieved December 11, 2015), hospitality and Table 1 lists those business categories associated with natural areas, not including hotels, restaurants, gas stations, outfitters, etc., since it is impossible to know which of these sales were associated with naturebased use.

Table 1. Sales by primarily nature-based business sectors in Lake County, IL (2014)

Category Sales Marinas $39,661,000 Museums, historical sites, zoos, parks $1,622,000 RV Parks/Recreational Camps $86,191,000 Scenic and sightseeing transportation, land $219,000 Scenic and sightseeing transportation, water $4,981,000 Total $132,674,000

Some of the above sales may not be associated with natural areas, but some nature-associated sales were not listed in this table. This probably underestimates spending, since so many categories were left out.

We received 2015 visitation numbers for many of the Lake County parks. Some sites like the stormwater facilities were closed to the public. All other forest preserves were open to the public but some did not have any access and/or use.

Presumably, many of these were multiple visits by the same people, and we assumed the numbers were person-days.

We multiplied the annual visit numbers by $30/person/visit ($2014) from SW MI data (Stynes, 1998). We then added margined sales (including secondary effects as money is recirculated), using a multiplier of 0.581 (subtracting one to avoid double counting). This averaged the value for state parks (0.584) and county parks (0.577) in Iowa, based on data from Otto et al. (2007). Finally, we multiplied the number of visits by $50.53 to get average consumer surplus value per person per day and added this to direct and indirect spending to get total recreation value. The value of $50.53 was the average from Loomis (2005) for bird watching, fishing, general recreation, hiking, hunting, swimming, wildlife viewing, and other recreation, converted to $2014. Table 2 lists the estimated recreation economic value per park.

Table 2. Estimated recreation economic value per park in Lake County, IL. (2015$/year) Annual Preserve Visitors Almond Marsh 5,689 Atkinson Stormwater 0 Berkeley Prairie 2,346 Black Crown 200 Bluebird Meadow 200 Brae Loch Golf Club 21,876 Buffalo Creek 129,402 Cahokia Flatwoods 367,324 Cptn Daniel Wright Woods 568,126 Casey Trail and Greenway 352,763 Community Garden Site 625 Countryside Golf Club 39,015 Cuba Mash 156,220 Duck Farm 224,897 Page 140 of 172

Est. direct spending $170,670

Est. secondary effects $99,159

Est. consumer surplus $287,465

Est. total recreation value $557,294

$70,380 $6,000 $6,000 $656,280 $3,882,060 $11,019,720 $17,043,780 $10,582,890 $18,750 $1,170,450 $4,686,600 $6,746,910

$40,891 $3,486 $3,486 $381,299 $2,255,477 $6,402,457 $9,902,436 $6,148,659 $10,894 $680,031 $2,722,915 $3,919,955

$118,543 $10,106 $10,106 $1,105,394 $6,538,683 $18,560,882 $28,707,407 $17,825,114 $31,581 $1,971,428 $7,893,797 $11,364,045

$229,814 $19,592 $19,592 $2,142,973 $12,676,220 $35,983,059 $55,653,623 $34,556,663 $61,225 $3,821,909 $15,303,311 $22,030,910 Last revised 8/20/2017

Preserve Duffy Stormwater Dutch Gap Edward R. Ryerson CA Egret Marsh Ethel's Woods Fort Sheridan Fox River Gander Mountain General Office Grainger Woods CP Grant Woods Grassy Lake Greenbelt Half Day Hastings Lake Heron Creek Independence Grove Kestrel Ridge Kettle Grove Lake Carina Lake Marie Lakewood Lyons Woods MacArthur Woods Marl Flat Middlefork Savanna McDonald Woods Mill Creek Nippersink Oak-Hickory Old School Oriole Grove Pine Dunes Prairie Stream Prairie Wolf Raven Glen Ray Lake Rollins Savanna Sedge Meadow Sequoit Creek Singing Hills Skokie River Woods Spring Bluff Tanager Kames Page 141 of 172

Annual Visitors 0 200 478,223 200 200 69,176 91,250 8,900 5,200 26,842 112,500 35,498 262,587 186,547 194,017 212,462 470,815 185,322 0 178,245 200 470,815 118,954 343,528 33,420 78,564 164,457 200 252,146 0 425,879 29,654 14,562 256 195,810 68,541 28,162 456,250 245,312 0 77,722 0 28,754 19,654

Est. direct spending

Est. secondary effects

Est. consumer surplus

Est. total recreation value

$6,000 $14,346,690 $6,000 $6,000 $2,075,280 $2,737,500 $267,000 $156,000 $805,260 $3,375,000 $1,064,940 $7,877,610 $5,596,410 $5,820,510 $6,373,860 $14,124,450 $5,559,660

$3,486 $8,335,427 $3,486 $3,486 $1,205,738 $1,590,488 $155,127 $90,636 $467,856 $1,960,875 $618,730 $4,576,891 $3,251,514 $3,381,716 $3,703,213 $8,206,305 $3,230,162

$10,106 $24,164,608 $10,106 $10,106 $3,495,463 $4,610,863 $449,717 $262,756 $1,356,326 $5,684,625 $1,793,714 $13,268,521 $9,426,220 $9,803,679 $10,735,705 $23,790,282 $9,364,321

$19,592 $46,846,725 $19,592 $19,592 $6,776,481 $8,938,850 $871,844 $509,392 $2,629,442 $11,020,500 $3,477,384 $25,723,023 $18,274,144 $19,005,905 $20,812,778 $46,121,037 $18,154,143

$5,347,350 $6,000 $14,124,450 $3,568,620 $10,305,840 $1,002,600 $2,356,920 $4,933,710 $6,000 $7,564,380

$3,106,810 $3,486 $8,206,305 $2,073,368 $5,987,693 $582,511 $1,369,371 $2,866,486 $3,486 $4,394,905

$9,006,720 $10,106 $23,790,282 $6,010,746 $17,358,470 $1,688,713 $3,969,839 $8,310,012 $10,106 $12,740,937

$17,460,880 $19,592 $46,121,037 $11,652,734 $33,652,003 $3,273,823 $7,696,129 $16,110,208 $19,592 $24,700,222

$12,776,370 $889,620 $436,860 $7,680 $5,874,300 $2,056,230 $844,860 $13,687,500 $7,359,360

$7,423,071 $516,869 $253,816 $4,462 $3,412,968 $1,194,670 $490,864 $7,952,438 $4,275,788

$21,519,666 $1,498,417 $735,818 $12,936 $9,894,279 $3,463,377 $1,423,026 $23,054,313 $12,395,615

$41,719,107 $2,904,906 $1,426,494 $25,078 $19,181,548 $6,714,276 $2,758,750 $44,694,250 $24,030,764

$2,331,660

$1,354,694

$3,927,293

$7,613,647

$862,620 $589,620

$501,182 $342,569

$1,452,940 $993,117

$2,816,742 $1,925,306 Last revised 8/20/2017

Preserve Thunderhawk Golf Club Van Patten Woods Wadsworth Savanna Wilmot Woods TOTAL

Chain Oâ&#x20AC;&#x2122; Lakes State Park Volo Bog Illinois Beach State Park Moraine Hills State Park North Point Marina

Annual Visitors 54,612 310,052 233,166 249,658 8,287,19 5

Est. direct spending $1,638,360 $9,301,560 $6,994,980 $7,489,740 $248,615,85 0

Est. secondary effects $951,887 $5,404,206 $4,064,083 $4,351,539 $144,445,80 9

Est. consumer surplus $2,759,544 $15,666,928 $11,781,878 $12,615,219 $418,751,96 3

Est. total recreation value $5,349,792 $30,372,694 $22,840,941 $24,456,498

502,186 95,544 1,061,06 1 615,298 834,055 3,108,14 4

$15,065,580 $2,866,320

$8,753,102 $1,665,332

$25,375,459 $4,827,838

$49,194,141 $9,359,490

$31,831,830 $18,458,940 $25,021,650

$18,494,293 $10,724,644 $14,537,579

$53,615,412 $31,091,008 $42,144,799 $157,054,51 6

$103,941,536 $60,274,592 $81,704,028

$811,813,622

TOTAL $93,244,320 $54,174,950 $304,473,786

For bike paths, we used Otto et al. (2007)'s estimate of $8/person ($9/person in $2014) of expenditures on food, beverages, and misc. supplies. This does not include the cost of bicycles and equipment. For 291,172 bike rides, this equals $2.6 million/year.

In 2014, the U.S. bicycle industry sold $6.1 billion of bicycles and parts (NBDA, 2015). If Lake County residents buy in proportion to their population (0.22% of the national total), and assuming half of these purchases are by bike trail users (which could be an overestimate, but 50% is a standard a priori guess), they spend around $6.7 million annually on bicycles and parts. Assuming half their bike rides are on the Northshore, McClory, and/or the Skokie River Bike Paths (which again could be an overestimate), this equals $12 per person use. We then added a secondary effects multiplier of 0.587 based on data from Otto et al. (2007), and a consumer surplus value of $73.78 ($2004; $92.46 in $2014) for biking from Loomis (2005). Table 3 lists the estimated recreation economic value per trail.

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Table 3. Estimated recreation economic value per bike trail in Lake County, IL. (2015$/year)

Preserve Northshore Bike Path McClory Bike Path Skokie River Bike Path TOTAL

Annual Visitors 73,730 75,214 142,228 291,172

Est. direct spending $1,548,330 $1,579,494 $2,986,788 $6,114,612

Est. secondary effects $908,870 $927,163 $1,753,245 $3,589,277

Est. consumer surplus $6,817,076 $6,954,286 $13,150,401 $26,921,763

Est. total recreation value $9,274,276 $9,460,943 $17,890,433 $36,625,652

Woodlands/Forest

Batker et al. (2010) reported aesthetic and recreation values of $4.89, $5.52, $5.94, $11.78, $17.84, $23.78, $40.76, $104.34, $169.13, $190.66, $538.99, $569.01, and $637.81/ac/year ($2006) for forest. In $2014, this ranged from $6$754/ac/year.

Streams and Lakes

A study in Philadelphia estimated that restoring riparian vegetation would increase recreational trips by almost 350 million over 40 years, and translate to $951.40/ac/year (presumably $2009) (CNT, 2010; $1,057/ac/year in $2014).

Batker et al. (2010) reported aesthetic and recreation values of $1,043; $1,474.20; $2,297.39; $4,420.54; and $10,624.14/ac/year ($2006) for riparian buffers. In $2014, this ranged from $1,233-$12,558/ac/year.

Batker et al. (2010) reported aesthetic and recreation values ranging between $1.69 and $19,699/ac/year (median $283.79; $2006) for rivers and lakes. In $2014, this ranged from $2-$23,284/ac/year (median $335).

Wetlands

Using results from 39 studies, Woodward and Wui (2001) reported a value ($1990) for wetlands between $95/ac/yr and $1,342/ac/yr (mean $357/ac/yr) for recreational fishing, between $25/ac/yr and $197/ac/yr (mean $70/ac/yr) for waterfowl hunting, and between $528/ac/yr and $2,782/ac/yr (mean $1212/ac/yr) for bird watching.

Batker et al. (2010) reported aesthetic and recreation values of $31.47, $34.75, $100.68, $103.35, $656.33, $1,044.66, $1,212.84, $2,100.39, $2,318.09, $4,187.89, $4,626.73, and $9,347.33/ac/year ($2006) for freshwater wetlands.

In $2014, these values ranged from $37-$11,049/ac/year (median $1,434).

Prairie/Grassland/Savanna

Batker et al. (2010) reported an aesthetic and recreation value of $1.01/ac/year ($2006) for grassland ($1/ac/year in $2014).

Spatial Assessments

MARC and AES (2013) ranked areas for recreation potential based on their proximity to public land, roads or trails, and land cover (Table 9).

Table 9. Ranks assigned by MARC and AES (2013) to areas based on their recreation potential. 5 is the highest rank and 0 the lowest.

Type of area Relative value Natural communities that intersect public lands or access points 5 Page 143 of 172

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Natural communities, grassland & cropland that are <200m of public roads & trails Natural communities, grassland & cropland that are >200m from public roads & trails All other land cover polygons

4 3 1

In Maryland, Weber (2007b) allocated USFWS (2003) data to ecosystem types. In 2001, residents and nonresidents spent $116 million on freshwater fishing in Maryland, which depends on forests and wetlands to maintain water quantity and quality. $67 million was spent hunting deer and wild turkey, and $3 million hunting squirrels, all of which are forest-dependent. People spent $11 million hunting duck and geese; the largest percentage of this would be in marshes. People spent $761 million watching wildlife in Maryland, not including home expenditures (bird feeders, bird baths, plantings, bird and wildlife food, etc.) (USFWS, 2003).

Wildlife viewers in Maryland spent $130 million on trip expenditures alone (USFWS, 2003). 90% of wildlife viewers spent at least part of their time watching birds, and 82% of people viewing wildlife away from home visited parks and other public areas. In 1993, there were 273 million visitors to national parks and in 1994-5; there were 54.1 million birdwatchers in the U.S. (McQueen, 2001). If visits to parks in Maryland followed a similar ratio, passive recreation trip expenditures in 2001 were: $130 million + ($130 million * .90 * .82) * (273 million - 54.1 million) / 54.1 million = $518 million.

On trips away from home, wildlife watchers in Maryland were 38% more likely to visit â&#x20AC;&#x153;woodlandsâ&#x20AC;? (upland forest) than wetlands (USFWS, 2003). But the upland forest was 4.72 times more numerous in the state than wetlands (1991-3 NLCD), implying that wetlands were 3.4 times more likely to be visited per acre than upland forest. There was no data to justify assigning different per acre expenditures for non-wildlife recreation, though. To summarize:

Wetland wildlife watching trips (MD total) = $130 million * 0.5 / (0.69 + 0.5) = $54.6 million Forest wildlife watching trips (MD total) = $130 million * 0.69 / (0.69 + 0.5) = $75.4 million

Wetland wildlife watching trips (per ac) = $54.6 million / 0.552 million ac = $99/ac wetland Forest wildlife watching trips (per ac) = $75.4 million / 2.606 million ac = $29/ac upland forest

Other passive recreation trips (MD total) =

($130 million * .90 * .82) * (273 million - 54.1 million) / 54.1 million = $358 million Other passive recreation trips = $358 million / 3.158 million ac = $133/ac forest or wetland Other wildlife watching expenditures = $631 million / 3.158 million ac = $200/ac forest or wetland

Freshwater fishing = $116 million / 2.928 million ac = $40/ac upland forest or forested wetland Forest game hunting = $70 million / 2.606 million ac = $27/ac upland forest Waterfowl hunting = $11 million / 0.230 million ac = $48/ac marsh

Summing and converting from 2001$ to 2006$, Weber (2007b) estimated the recreation value per year as $486/ac for the upland forest, $534/ac for forested wetlands, and $544/ac for marsh.

Baerenklau et al. (2010) estimated the access value for trailheads using a multiple-site zonal travel cost model. Zonal models typically use zip codes as the spatial unit of analysis, which facilitates incorporation of distance and census data as explanatory variables in the regression. The price of a trip from each zip code was estimated as the sum of driving costs and time costs. Driving costs were a function of distance (derived from Google Maps), the average per-mile cost of operating a typical car (from AAA, $0.561/mile in 2005), and the average number of passengers per vehicle (1.5; authorsâ&#x20AC;&#x2122; dataset). Time costs were a function of travel time (derived from Google Maps) and the opportunity cost of time, which was evaluated at one-third of the average hourly per-capita income for each zip code (a standard assumption). They found a highly skewed distribution of recreation values, with the highest values corresponding to parcels with the best view.

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References in this section

Balmford, A., A. Bruner, P. Cooper, R. Costanza, S. Farber, R. E. Green, M. Jenkins, P. Jefferiss, V. Jessamy, J. Madden, K. Munro, N. Myers, S. Naeem, J. Paavola, M. Rayment, S. Rosendo, J. Roughgarden, K. Trumper, and K. Turner. 2002.

Economic reasons for conserving wild nature. Science 297:950- 953.

Baerenklau, K.A., A. González-Cabán, C. Paez, and E. Chavez. 2010. Spatial allocation of forest recreation value. Journal of Forest Economics 16:113-126.

Batker, D., M. Kocian, B. Lovell, and J. Harrison-Cox. 2010. Flood protection and ecosystem services in the Chehalis River Basin. Earth Economics, Tacoma, WA. Carver, E. 2013. Birding in the United States: A demographic and economic analysis. U.S. Fish and Wildlife Service, Division of Economics, Arlington VA. Report 2011-1.

Center for Neighborhood Technology (CNT). 2010. The value of green infrastructure: a guide to recognizing its economic, environmental and social benefits. Center for Neighborhood Technology, Chicago, IL. Charbonneau, J. J., and J. Caudill. 2010. Conserving America’s fisheries: an assessment of economic contributions from fisheries and aquatic resource conservation. U.S. Fish and Wildlife Service, Division of Economics, Arlington VA. Fermata, Inc. 2010. Hackmatack National Wildlife Refuge: Viability study.

Illinois Department of Natural Resources (IDNR). 2009. Illinois Statewide Comprehensive Outdoor Recreation Plan 2009– 2014.

Indiana Department of Natural Resources (Indiana DNR). 2012. Indiana Statewide Outdoor Recreation Plan 2011–2015.

Indiana Department of Natural Resources (Indiana DNR). 2014. State Parks and Reservoirs Visitation - Fiscal Year 2014 (July 1, 2013 - June 30, 2014).

International Association of Fish and Wildlife Agencies (IAFWA). 2002. Economic importance of hunting in America.

IAFWA, Washington, DC. Klapproth, J. C., and J. E. Johnson. 2001. Understanding the science behind riparian forest buffers: benefits to communities and landowners. Virginia Cooperative Extension. Publication Number 420-153.

Loomis, J. 2005. Updated outdoor recreation use values on National Forests and other public lands. U. S. Department of Agriculture. General Technical Report #PNW-GTR-685.

McQueen, M. 2001. Land and water conservation: an assessment of its past, present and future. The Conservation Fund, Arlington, VA. Mid-America Regional Council (MARC) & Applied Ecological Services (AES). 2013. Kansas City Natural Resources Inventory II Phase 4: Ecosystem Services Method Development.

National Park Service (NPS). 2014. National Park Service visitor use statistics. https://irma.nps.gov/Stats/Reports/Park.

Accessed Dec. 18, 2014.

NBDA. 2015. Industry Overview 2014. http://nbda.com/articles/industry-overview-2014-pg34.htm. Accessed Dec. 23, 2015.

Otto, D., D. Monchuk, K. Jintanakul, and C. Kling. 2007. The economic value of Iowa’s natural resources. Iowa State University Department of Economics.

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Sipple, B. 2007. Wetlands functions and values. http://www.epa.gov/watertrain/wetlands/.

Stynes, D. J. 1998. State and regional economic impacts of Michigan State Park visitors. Report to Public Policy Associates and Parks and Recreation Division, Michigan DNR. Thomas, C. C., C. Huber, and L. Koontz. 2014. 2013 National Park visitor spending effects: economic contributions to local communities, states, and the nation. Natural Resource Report NPS/NRSS/EQD/NRRâ&#x20AC;&#x201D;2014/824 Trust for Public Land. 2013. Land Conservation in Illinois. http://www.conservationalmanac.org/secure/almanac/midwest/il/index.html. Accessed July 17, 2014.

U.S. Fish and Wildlife Service (USFWS). 2003. 2001 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: Maryland. FHW/01-MD-Rev. U.S. Fish and Wildlife Service and U.S. Census Bureau (USFWS and USCB). 2014. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation. FHW/11-IL (RV).

Weber, T. 2007b. Ecosystem services in Cecil Countyâ&#x20AC;&#x2122;s Green Infrastructure: Technical Report for the Cecil County Green Infrastructure Plan. The Conservation Fund, Annapolis, MD. Woodward, R. T. and Y.-S. Wui. 2001. The economic value of wetland services: a meta-analysis. Ecological Economics 37:257-270.

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4.4 Terrestrial Movement Analysis Tool description

Introduction: The Terrestrial Movement Analysis tool models landscape connectivity, which is useful to identify and prioritize areas that are important to maintaining wildlife movement and gene flow within a human-modified landscape. The tool treats the landscape as a circulatory system, identifying those pathways most likely to be followed by wildlife. This is done by generating random sets of starting locations (each location corresponding to an individual organism) and then calculating optimal (least cost) paths to all other habitat within the landscape. This process is executed iteratively, with each iteration having a different set of random start locations and corresponding least-cost paths. The tool calculates overall landscape connectivity by summing the least-cost paths from all iterations and then averaging these. This process creates a set of rasters that show pathway usage, the cost of moving through a corridor, and overall landscape movement potential.

Tool Processing Procedures:

The Terrestrial Movement Analysis tool (Figure 1) estimates connectivity within a landscape, first by identifying random start locations of organisms within habitat patches (cores) and then modeling movement away from these locations using least-cost path analysis. This process is repeated iteratively (with a number of iterations set by the user).

Figure 1 - Terrestrial Movement Analysis tool (for ESRI ArcGIS 10.3)

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Figure 2 - Basic processing procedures involved in the model. Appendix 1 has a detailed flow chart of TMA procedures and Appendix 2 contains a table of all intermediate rasters with a brief description that is generated throughout the operation of the tool.

The tool sums outputs from each iteration and then divides by the number of iterations (Figure 2). The start locations are selected by comparing a random raster (with values between 0 and 1) against the user-defined patch or occurrence probability raster (values also between 0 and 1), and selecting the highest proportion of random values (user-defined) that are greater than or equal to the patch cell value (Figure 3). NODATA values for the patches raster will not have seed locations. Pathways and corridors are estimated from start locations by “growing” a cost distance raster away from a “seed” and creating a movement direction raster.

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Figure 3 - Start locations example for four separate iterations The movement direction raster assigns each cell with an 8-direction coding system that provides â&#x20AC;&#x153;directionsâ&#x20AC;? back to the start location (Figure 4).

Figure 4 - Flow direction example. A) Demonstrates the eight directions of movement from the center cell; B) contains the direction coding system for the eight directions; C) Demonstrates the direction of

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flow from the center cell if flow direction is north; D) The movement direction code to move to the north cell.

The movement direction raster is used to accumulate patch areas back to the start locations creating the least-cost pathways weighted by accumulated patch area (Figure 5).

Figure 5 - Pathways to start locations for one iteration The value along the pathway represents the amount of patch area that it’s connected to. Corridors are generated around pathways by “growing” cost distance from the pathways outward to a user-defined maximum cost distance (Input – “Maximum Movement around pathway”) (Figure 6).

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Figure 6 - Inter-corridor cost distance for one iteration This process also generates the inter-corridor movement (Figure 6) and corridor cost rasters (Figure 7), which are used to calculate the movement potential raster.

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Figure 7 - Corridor cost raster for one iteration

General Tool Processing Information:

The Terrestrial Movement Analysis tool is designed to run in ESRI ArcGIS 10 Service Pack 4. The tool generates a temporary workspace (directory) to C:\temp, named LANDCONN followed by a date stamp (year/month/day/hour/minute/second). If the directory C:\temp doesnâ&#x20AC;&#x2122;t exist, the tool will stop and report an error message. Since the tool relies on the COST DISTANCE tool to develop the movement-based rasters, refer to the ESRI COST DISTANCE help for details on its operation and limitations. The tool assumes that the patches and resistance rasters have the same projection, cell size and extent (cell alignment). If the cell size or extents are not the same, the tool will run but may produce results that are incomplete.

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Tool Input Details: 1. Patches Raster: This raster can be a binary, integer, or continuous floating point raster with a range of values between 0 and 1. For example, a layer of core areas might only contain values of 1 (core areas) and 0 or No Data (areas outside cores). Whereas, a habitat suitability layer might contain continuous values between 0 and 1, with 1 representing higher suitability or (in the case of Maxent output) probability of organism occurrence. The values in this raster are also used as weights during the pathway analysis. For example, if core areas have a value of one, then pathway values will represent the average number of core cells that it is connected to. Or the raster values could range between 0 and 1, which would represent the average cumulative resource quality that a pathway is connected to.

2. Landscape Resistance Raster: Raster used to weight movement through cells in the development of pathways and corridors based on cost distance analysis. Values should be greater than zero, with NODATA values treated as absolute barriers to movement. The parameterization of this raster should reflect the difficulty of an organism to travel through a given raster cell given terrain, vegetation, human modification, and other attributes.

For example, if an organism has an affinity for flat grasslands then cells that have a shallow slope and are grasslands could have a weight of 1 and cells that are steep and forested have a value greater than one. The steep forested values should be based on how much it impedes or discourages movement (e.g., 10 times to 1000 times greater).

3. Maximum Movement from Start Locations: This value represents the maximum allowed movement from start locations based on cost distance units (usually much larger than Euclidean distance). An input value of “maximum” indicates that movement from start locations is unlimited, and will result in every cell having a cost distance value. Figure 8 shows how different movement thresholds changed the analysis extent around each start location. As this value increases so do the number and length of corridors in the output. A good practice is to run the tool first set at “maximum”, then assess the corridor output and choose a value that matches the most reasonable looking corridors. The optimal value will depend on the landscape being analyzed; values in the range of 2-4 million generally produce good output.

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Figure 8 - Cost distance allocation zones for start locations using different maximum movement from start location values

4. Minimum Pathway Threshold: This value is the minimum number of accumulated patch raster values (i.e. the number of cells accumulated back to the start locations) that make up a pathway that a corridor will be generated for.

For example, a value of one (the default input value) means that all pathway cells with a value greater than or equal to one will have a corridor generated. Figure 9 demonstrates how this value influences the configuration of pathways that corridors will be generated for. This value is analogous to flow accumulation threshold values when generating hydrologic networks based on an elevation model. As this value increases, the number of corridors in the output will decrease.

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Figure 9 - Minimum pathway threshold values based on accumulated core cells to start locations 5. Maximum Movement Around Pathways: This value can be thought of how wide a corridor around a selected pathway is but is based on cost instead of Euclidean distance. This value can be thought of the degree of movement that would occur while moving along a pathway. Figure 10 depicts how corridor shape changes with different maximum values. â&#x20AC;&#x201C; As this value increases, the corridors in the output become wider. A value of 3,000 â&#x20AC;&#x201C; 6,000 is generally sufficient.

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Figure 10 - Maximum movement around pathways example, showing inter-corridor movement and width based on different maximum movement values.

6. Number of Iterations: The number of iterations involved in the analysis. This number can range from 1 to ~1000 depending on processing time constraints and the maximum movement from start locations threshold. Since start locations are based on a random process, the larger the number of iterations, the greater the chance that all core areas will have a start location. More iterations also create a better representation of connectivity within a landscape. An optimal iteration value has not been evaluated, but the default value of 10 works well when the maximum movement from start locations value is set to MAXIMUM. When maximum movement from start locations values is less than MAXIMUM, more iterations are necessary to connect the landscape due to a smaller window of analysis (Figure 8).

Using 10-20 iterations is adequate when running sensitivity analyses for a new project area. Once the final parameters are determined, the model should be run with 100 iterations. Values higher than this are infeasible for any area greater several thousand square miles due to excessive runtimes. As the number of iterations increases, the mean cost of the corridor network decreases, while the area of the

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network increases slightly. Thus, using 100 iterations provides a compromise in terms of producing the least cost, but most extensive corridor network.

7. Start Location Percentage This value determines the number of random start locations per iteration based on the top nth percentile (Figure 11) of randomly generated values. The default value of one selects the top 1 percentile highest random values as start locations. The smaller this number, the fewer number of start locations (Figure 12), which is necessary for landscapes that are not fragmented to ensure that connectivity between all cores is at its maximum. This number should be larger than 1 for landscapes that are highly fragmented (i.e. lots of NODATA barriers) so that smaller subnetworks will have start locations across all iterations. As this value increases, the number of corridors in the output will decrease.

Figure 11 â&#x20AC;&#x201C; Cumulative Distribution Function (CDF) of random values (0 to 1) showing the percentage of random values above a given Start Location Percentage threshold. The four red threshold breaks were used to generate the start locations in Figure 12.

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Figure 12 â&#x20AC;&#x201C; Start location percentage example, demonstrating how the density of start locations changes based on an increasing percentage. The four percentage breaks used are shown graphically in Figure 11.

8. Impedance Variation (Impedance Limits Raster) If using this parameter, the value at each cell location represents the maximum fraction (+/-) that the cell's impedance value will randomly alter (e.g., a value of .5 means that the impedance value can fluctuate up to 50% of its original value). A value of 0 means the impedance value will not vary. The recommended value range is between 0 and 1.

Figure 13 shows how the impedance raster is altered using a random raster that is filtered by the impedance limits raster. Figure 14 demonstrates how an impedance raster values are randomly altered using the impedance limits raster as a filter to control the degree of alteration. This process starts (Figure 14) by generating a random raster (RR1) with values ranging between 0 and 1 (these values will determine the percent change for an impervious value). The random raster (RR1) is then filtered against the impedance limits raster creating a raster with RR1 values that are less than or equal to the impedance limits values and NULL values that are larger (FR1). Percent increase or decrease of the

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impedance values is determined by creating a second random raster (RR2) and filtering it so that RR2 values that are greater than FR1 are assigned an increased percentage (1 + FR1) and values that are less are assigned a decreasing percentage (1 â&#x20AC;&#x201C; FR1) to create FR2. This raster is multiplied against the impedance raster for areas that are not NULL to derive the modified impedance values with NULL values receiving the original impedance value (Altered Impedance raster). This process allows alternate pathways to be chosen based on local anomalies or to account for uncertainties associated with assigning impedance values.

Figure 13 Flow chart showing the steps involved in altering the impedance raster via a random raster and filtering against the impedance limits raster.

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Figure 14. Example of how the impedance raster (IR) values are altered based on filtering the random raster (RR1) against the impedance limits raster

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Tool Output Details: 1. Movement Raster This raster represents potential movement pathways, with higher values indicating a greater connection to non-zero cells in the patches raster. Pathways are represented as single cell wide paths that end at a start location (not patch edges). The maximum value will be the total sum of all cells within the patches raster, which indicates that it connected to every cell within the landscape. This is rare because of the permutation process, other competing locations, and no data areas that prevent movement. Figure 15 demonstrates how pathways generated at a given iteration have different pathway configurations, and Figure 16 shows the result of averaging the four iterations in Figure 15 into the final average pathway raster.

Figure 15 - Accumulated patch area pathways for four different iterations

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Figure 16 â&#x20AC;&#x201C; Final pathways raster based averaged pathways from Figure 11

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2. Corridor Cost Raster The Corridor cost raster represents the average cost of moving through a given corridor from all start locations that are connected to each other. The average cost is calculated by dividing the total cost of moving through the corridor by the number of times the corridor was used in the analysis, which usually is less than the number of iterations in the analysis. Figure 17 shows the average cost of a given corridor and with blue tones having low average cost values and red being the highest. This is useful in evaluating corridor importance as well as defining isolated patches that are connected to high-cost corridors.

Figure 17 - Average corridor cost from start locations for ten iterations.

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3. Movement Potential Raster The movement potential integrates patch connectivity (pathways), corridor cost, and inter-corridor movement into a single value that ranges between 0 and 1 with one indicating the highest potential for movement. The movement potential integration is a simple metric that ranks pathways (Figure 16), corridor cost (Figure 17) and inter-corridor movement (Figure 6) between 0 and 100 using a cumulative distribution function (CDF) to generate a new raster. The three CDF rasters are averaged together using a weighting scheme (pathways = 0.3, corridor cost =0.35 and inter-corridor movement = 0.35). The weighted averaged raster is then normalized between 0 and 1 to generate the final movement potential raster (Figure 18).

Figure 18 - Movement potential raster ranking pathways and corridors between 0 and 1.

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Appendix 1.

Detailed flow chart of the process involved in the Terrestrial Movement Analysis tool. The red boxes are model inputs with green being model processes and black being intermediate rasters stored in temporary workspace

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Appendix 2.

This table contains all intermediate rasters stored in the temporary workspace with a brief description. Please note that most of these rasters are created and deleted with every iteration instance in the analysis. This means that the values for these rasters are only for the last iteration.

Raster Name

Description

Accum

Accumulation of patch values along “flow paths” from cost analysis for a given iteration. This raster is filtered based on the minimum path size to create pathways and corridors.

Accum1

This raster is the Accum raster with the minimum pathways filtered out. This filter is based on the user-defined parameter Minimum Pathway Threshold. The values in the raster are based on a single iteration instance.

Corcost

This raster is the cost distance (in cost units) from the pathways (Accum1) to a user-defined (Maximum Movement Around Pathways) distance. The values in the raster are based on a single iteration instance.

Corcost1

This raster is the combination of Corcost for two iterations. This is done in conjunction with the raster Costcost3 so that a new raster is not created with each iteration.

Corcost2

This raster is the combination of Corcost for two iterations. This is done in conjunction with the raster Costcost1 so that a new raster is not created with each iteration.

CorCost3

This raster is the combination of Corcost for two iterations. This is done in conjunction with the raster Costcost2 so that a new raster is not created with each iteration.

Cost3

This raster is the average cost (in cost units) for a corridor between patches for a given iteration instance.

Costback

Eight direction back link raster derived from cost distance analysis for a given iteration instance.

Count1

This raster keeps track of corridor usage throughout the analysis for a given iteration. This raster doesn’t keep track of all the iterations it's a corridor window that is added to the Mcout1, Mcount2, and Mcount3 rasters.

Evr

This raster contains random values between 0 – 1 that are >= to the values in the in the patches raster.

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Fcorrcost

This raster is the average corridor cost values for all iterations.

Flow_dir

This raster is Costback raster converted into 8 direction flow direction values so that patch raster values can be accumulated (Accum and Accum1) using the Flow accumulation tool.

Mcost1

This raster is the average corridor cost for Mcost2, Mcost3 and Cost3 across three iteration instances.

Mcost2

This raster is the average corridor cost for Mcost1, Mcost3 and Cost3 across three iteration instances.

Mcost3

This raster is the average corridor cost for Mcost2, Mcost1 and Cost3 across three iteration instances.

Mcount1

This raster is the sum of corridor count (time a corridor is used) by summing rasters Mcount2, Mcount3 and Count1 across three iteration instances.

Mcount2

This raster is the sum of corridor count (time a corridor is used) by summing rasters Mcount1, Mcount3 and Count1 across three iteration instances.

Mcount3

This raster is the sum of corridor count (time a corridor is used) by summing rasters Mcount2, Mcount1, and Count1 across three iteration instances.

Mtemp1

This raster is the sum of accumulated pathways values (Accum1) by summing rastes Mtemp2, Mtemp3 and Accum1 across three iteration instances.

Mtemp2

This raster is the sum of accumulated pathways values (Accum1) by summing rastes Mtemp1, Mtemp3 and Accum1 across three iteration instances.

Mtemp3

This raster is the sum of accumulated pathways values (Accum1) by summing rastes Mtemp2, Mtemp1 and Accum1 across three iteration instances.

Pseeds

This raster is an intermediate raster involved in creating start locations. It holds random values from the Randomseeds raster and is used to rank values so that the top nth percentile can be extracted to create the start locations.

Randomseeds

This raster contains random pixel values between 0 and 1 for the entire extent of the patches raster.

Seeds

This raster contains a cell with the value of one and serves as the start locations that cost distance will be calculated from and be the sink for the accumulated pathways analysis. This raster is deleted and generated with every iteration instance so it only displays the last iteration start locations.

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Slevt

This raster contains values from 1 to 200 based on the random values in the Evt raster and used to select the top Nth percentile of random values to be used as the Seeds raster. This raster is deleted and creates with every iteration instance, so it represents the last iteration.

Slice1

This raster is the Pathways (user-defined name) divided into 100 groups (labeled 1 through 100) based on the natural distribution of the data. This raster is used in conjunction with the Slice2 and Slice3 to calculate the movement potential raster.

Slice2

This raster is the Corridor (user-defined name) divided into 100 groups (labeled 1 through 100) based on the natural distribution of the data. This raster is used in conjunction with the Slice1 and Slice3 to calculate the movement potential raster.

Slice3

This raster is the Fcorrcost raster divided into 100 groups (labeled 1 through 100) based on the natural distribution of the data. This raster is used in conjunction with the Slice1 and Slice2 to calculate the movement potential raster.

Slnorm

This raster is a Natural Log transformation of the weighted average between Slice1, Slice2, and Slice3,

Temp3

This raster is the sum of accumulated values (number of patch cells) for pathways for a given iteration instance.

Totcost

This raster contains cost distance values from the start locations outward until the user-defined values (Maximum Movement from start locations) or to the full extent of the data within the impendence raster.

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Appendix 3.

Sensitivity analysis executed by Michael Schwartz, Senior Environmental Associate with The Conservation Fund, focusing on how increasing the number of iterations for the Terrestrial Movement Analysis tool affects corridor area, spatial arrangement, and average cost, as well as processing time.

Summary While attempting to run sensitivity analyses on various TMA tool parameters I noticed some inconsistencies in the outputs, where changing a parameter along a range did not always produce the expected results e.g. variation in the spatial arrangement of corridors and inconsistent stats. I then decided to run sets of 3 replicates over a range of iterations to determine whether the tool would produce a consistent output using higher numbers of iterations.

I tested the TMA tool at 20, 40, 100, 150, 200, and 300 iterations (3 reps each) using the Central WV test data (~2,000 mi2). The 300 iteration test took 30 hours to complete and was not repeated.

Parameters •

Tool version: 20120816

•

Maximum movement from start locations (MFSL): maximum

•

Minimum Pathway Threshold (MPT): 1

•

Maximum movement around pathways (MAP): 3000

•

Start location percentage (SLP): 5

Findings •

Output still varies per run at 200 iterations (Figure 1).

•

As the number of iterations increases, the mean cost of the network decreases (Figure 2) and area of the network increases slightly (Figure 3).

•

For large areas, any analysis using more than 100 iterations is not likely to be feasible (Figure 4).

•

Recommend using 100 iterations to achieve lower cost networks.

•

Variance in outputs makes it difficult to assess the effects of various parameter settings on outputs.

*All discussions/figures pertain to the “move_cost” output

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Core Rep 1 Rep 2 Rep 3

0

2.5

5

I

10 Miles

Figure 1. Variations in move_cost output at 200 iterations.

70,000 60,000

Mean Cost

50,000 40,000 30,000 20,000 10,000 0 0

50

100

150

200

250

Number of Iterarons

Figure 2. Effect of the number of iterations on the mean cost of the network.

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Total Corridor Area (km2)

1,700

1,650

1,600

1,550

1,500 0

50

100

150

200

250

Number of Iterarons

Figure 3. Effect of the number of iterations on total corridor area.

8.00

Runrme (hrs/1,000 sq. mi.)

7.00 6.00 5.00 4.00 3.00 2.00 1.00 0.00 0

50

100

150

200

250

Number of Iterarons

Figure 4. Time requirements for 1,000 square mile area by number of iterations.

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