FOREST HEALTH RESEARCH PROGRAM
FINAL TECHNICAL REPORT
Vegetation Trends and Cycles in the Fire-Prone Landscapes of Lake, Napa, and Sonoma Counties
Author 1 Arthur Dawson
Historical Ecologist, Baseline Consulting
Author 2 Tosha Comendant
Conservation Science Director, Pepperwood
Author 3 Kai Henifin
Climate and Fire Resilience Coordinator, Pepperwood
Author 4 Lisa Micheli President & CEO, Pepperwood
Author 5 James Thorne
Research Scientist, Department of Environmental Science and Policy, UC Davis
Author 6 Mark Tukman
Principal, Tukman Geospatial, LLC
April 2023
The CAL FIRE Forest Health Research Program is part of California Climate Investments, a statewide initiative that puts billions of Cap-and-Trade dollars to work reducing greenhouse gas emissions, strengthening the economy, and improving public health and the environment particularly in disadvantaged communities.
TERRITORIAL ACKNOWLEDGEMENT
Pepperwood Reserve sits within the traditional homeland of the Wappo people. We respect and honor past, present, and future generations of Wappo and their continued connection to this land. We are grateful for the opportunity to gather in this beautiful place and we give our respect to its first inhabitants.
Authored by Clint McKay (Dry Creek Pomo, Wappo, Wintun)
Suggested citation: Dawson, A. D., Comendant, T. Henifen, K., Thorne, J. H., Tuckman, M. & Micheli, L. 2023. Vegetation Trends and Cycles in the Fire-Prone Landscapes of Lake, Napa, and Sonoma Counties. Pepperwood Preserve, CA.
TABLE OF CONTENTS
Sonoma-Napa Study Area, maps, pie charts, and tables
Sonoma West Study Area, maps, pie charts, and tables
Lake Study Area, maps, pie charts, and tables
Napa East Study Area, maps, pie charts, and tables
Fire and Vegetation Under Indigenous Stewardship
Regional Fire Patterns: 1870-2020
Landscape Variables: Distance Inland, Slope Aspect, Slope Steepness
Frequent and Rare Burn Zones
Regional Vegetation Patterns: 1870-2020
Shrubland Decline
Woodland Expansion: Douglas Fir Expansion, California Bay Expansion
Black Oak Decline
Vegetation Response to Fire: Fire-Shrub-Woodland-Fire Cycle
Vegetation Response to Timber Harvest
Vegetation in the Absence of Fire: Rare Burn Zones
Grassland
Emissions and Sequestration
Vegetation Trends and Cycles in Fire Prone Landscapes of Lake, Napa East and Sonoma Counties
Pepperwood,
Environmental
3
Baseline Consulting, Tukman Geospatial, Thorne
Landscape Analysis
List of Figures, List of Tables, Abbreviations and Terms, 5 Keywords, Acknowledgments, Abstract Introduction 9 Setting 12 Methods and Materials 14 Indigenous Wisdom Historical Record
Mapping
Mapping and Quantifying Vegetation Response to
and Disturbance Emissions and Sequestration Tipping Points for Catastrophic Fire (Addendum) Selected Results 21 Indigenous
Historical
Mapping and Measuring Vegetation Change Mapping Historical Fire Extent and Frequency
Historical Timber Harvest
Fire
Wisdom
Record
Discussion 50
Clint Mckay, (Wappo, Pomo, Wintun) Indigenous Elder
Table A-1: GLO Survey to Modern Vegetation Crosswalk
Table A-2. Woodland Calculations from General Land Office Survey Data
CA Fish and Wildlife: WILDLIFE HABITAT RELATIONSHIP Designations
Table A-3. Confidence Levels for Mapped Accuracy of Historical Fire Perimeters From Narrative
SONOMA WEST: Map, Overview, Vegetation and Fire Tables, Narrative Timeline
SONOMA-NAPA: Map, Overview, Vegetation and Fire Tables
LAKE: Map, Overview, Vegetation and Fire Tables
NAPA EAST: Map, Overview, Vegetation and Fire Tables
Vegetation Trends and Cycles in Fire Prone Landscapes of Lake, Napa East and Sonoma Counties
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Environmental
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Exposure Metric, and
Possible Tipping Point Management Implications 78 Sources 80 Appendix: Comprehensive Results and Supporting Materials A-1 Appendix Table of Contents A-2 General Results and
A-3
Baseline Consulting, Tukman Geospatial, Thorne
Landscape
Addendum: Catastrophic Fire, Wind vs. Fuel-Driven Wildfires, 71 A Fire
a
Supporting Material
Sources Results by Study Area A-10
LIST OF FIGURES
Figure 1. Study Area Regional Map
Figure 2. Sonoma-Napa Study Area, Vegetation Lifeforms, 1872 - 2016
Figure 3. Sonoma-Napa Study Area, Lifeform Comparison by County 1867 - 2016
Figure 4. Sonoma-Napa Study Area, Fire History 1870 - 2020
Figure 5. Sonoma-Napa Study Area, Frequent Burn Zone (FBZ) Lifeforms 1877 - 2013
Figure 6. Sonoma-Napa Study Area, Rare Burn Zone Lifeforms (RBZ) 1867 - 2016
Figure 7. Sonoma West Study Area, Vegetation Lifeforms—1867 - 2013
Figure 8. Sonoma West Study Area Fire History: Documented Fires 1902 – 2020
Figure 9. Sonoma West Study Area, Frequent Burn Zone (FBZ) Lifeforms 1867 - 2013
Figure 10. Sonoma West Timber Harvest Zone (THZ): Intensive Logging, c. 1875 - 1915
Figure 11. Sonoma West Timber Harvest Zone (THZ) Lifeforms 1867 - 2013
Figure 12. Lake Study Area, Vegetation Lifeforms, 1873 - 1993
Figure 13. Lake Study Area, Fire History: Documented Fires – 1874 - 2020
Figure 14. Lake Study Area, Frequent Burn Zone (FBZ) Lifeforms –-1873 – 1993
Figure 15. Lake Study Area, Frequent Burn Zone (FBZ) Post fire Shrub Transitions—1950-1993
Figure 16. Lake Study Area, Rare Burn Zone (RBZ) Lifeforms 1866 – 1993
Figure 17. Napa East Study Area, Vegetation Lifeforms, 1863 - 2016
Figure 18. Napa East Study Area, Fire History: Documented Fires – 1874 – 2020
Figure 19. Napa East Study Area, Frequent Burn Zone (FBZ) Lifeforms –-1863 – 2016
Figure 20. Napa East Study Area, Rare Burn Zone (RBZ) Lifeforms 1876-2016
Figure 21. Average # Fires by Study Area
Figure 22. Average # Fires vs. Distance Inland
Figure 23. Average # Fires vs. Slope Aspect
Figure 24. Average # Fire in Frequent Burn Zones and Study Areas
Figure 25. Sonoma West, % Woodland Cover 1867-2013
Figure 26. Sonoma-Napa, % Woodland Cover 1871-2015
Figure 27. Lake, % Woodland Cover 1871-2015
Figure 28. Napa East, % Woodland Cover 1863-2016
Figure 29. Change in Douglas Fir Cover
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Figure 30. Douglas Fir Elevation Shift, Sonoma-Napa 1870 – 2013
Figure 31. Douglas Fir Elevation Shift, Sonoma West 1870 – 2013
Figure 32. Douglas Fir Elevation Shift, Lake 1870 – 2013
Figure 33. Sonoma-Napa FBZ Lifeform Transitions, 9-49 Years Post Fire
Figure 34. Sonoma West FBZ Lifeform Transitions, 6-54 Years Post Fire
Figure 35. Lake Lifeform FBZ Transitions, 6-49 Years Post Fire
Figure 36. Sonoma-Napa Fire Extent, 1870 – 2020 (as % of Study Area)
Figure 37. Sonoma West Fire Extent, 1916 – 2020 (as % of Study Area)
Figure 38. Lake Fire Extent 1874 - 2020 (as % of Study Area)
Figure 39. Napa East Fire Extent, 1870 – 2020 (as % of Study Area)
Figure 40. Windspeed and Fire Spread, Tubbs and Nunns Fires, October 2017.
Figure 41. Woodland Cover vs. Fire Size (>500 acres) Sonoma-Napa, 1936 – 2017
Figure 42. Woodland Cover vs. Fire Size (>2000 acres) Lake, 1939-2015
Figure 43. Woodland Cover vs. Fire Size (>300 acres) Sonoma West, 1929-2020
Figure 44. Woodland Cover vs. Fire Size (>500 acres) Napa East
LIST OF TABLES
Table 1. Study Area Summary Characteristics
Table 2. Vegetation Categories applicable to all data
Table 3. Mapping Resolution of Vegetation Data
Table 4. Sonoma-Napa FBZ, Lifeform Cover by Date and Rate of Change
Table 5. Sonoma-Napa RBZ, Lifeform Cover by Date and Rate of Change
Table 6. Sonoma West FBZ, Lifeform Cover by Date and Rate of Change
Table 7. Sonoma West THZ, Lifeform Cover by Date and Rate of Change
Table 8. Lake FBZ, Post fire Shrub Transitions, Lifeform by Data and Rate of Change
Table 9. Lake RBZ, Lifeform Cover by Date and Rate of Change
Table 10. Napa East FBZ, Lifeform Cover by Date and Rate of Change
Table 11. Napa East RBZ, Lifeform Cover by Date and Rate of Change
Table 10. Wind-driven vs. Fuel-driven Phases. Sonoma Complex Fires. October 2017
Table 11. Woodland Cover within 2015-2020 Fire Perimeters
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ABBREVIATIONS and TERMS
FBZ: Frequent Burn Zone
GLO: General Land Office surveys, late 19th century
Napa Veg map: Napa Vegetation Map, 2016
Nunns: Nuns [Fire]. Nunns is the original spelling and refers to an early setter.
RBZ: Rare Burn Zone
Soil-Veg maps: Soil-Vegetation maps, 1950 - 1965
Sonoma Veg map: Sonoma Vegetation Map, 2013
THZ: Timber Harvest Zone
VTM: Vegetation Type Maps, 1928-1932. (aka ’Wieslander’)
WHR: Wildlife Habitat Relationship maps
KEYWORDS
Vegetation Response to Fire
Vegetation Trends
Vegetation Cycles
Fire-prone Landscapes
Wildfire Patterns
Prescribed burning
Cultural burning
Fire History
Vegetation History
Northern California
ACKNOWLEDGEMENTS
The assistance and support of many people was essential to completing this project. We are especially grateful to: Amber Manfree; Ben Nichols, CAL FIRE; Carolyn Ruttan, Clear Lake Environmental Center; Chris Carlson, Sonoma Land Trust; Christopher Kam; David Ackerly, UC Berkeley; David Conklin, Bureau of Land Management; Jill Dawson; Kim Batchelder, Sonoma County Agricultural and Open Space District (Ag & Open Space); Lakeport Library staff; Michelle Halbur, Pepperwood; Monica Delmartini, Ag & Open Space; Morgan Gray, Pepperwood; Penny Sirota; Ryan Ferrell, Pepperwood; Michael Gillogly, Pepperwood; and the members of the Sonoma County Forest Conservation Working Group
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This study builds on research conducted in the region over the last two decades, funded by a number of agencies and non-profits, including Audubon Canyon Ranch, Pepperwood, Sonoma County Agricultural and Open Space District, Sonoma Land Trust, Golden Gate National Parks Conservancy, Sonoma Land Trust, and Sonoma Ecology Center.
FUNDING
Funding for this project was provided by the CAL FIRE Forest Health Research Program, Grant 8GG19813. The Forest Health Research Program is part of California Climate Investments, a statewide initiative that puts billions of Cap-and-Trade dollars to work reducing greenhouse gas emissions, strengthening the economy, and improving public health and the environment particularly in disadvantaged communities.
ABSTRACT
Between 2015 and 2020, some of the most destructive and deadly wildfires in California history occurred in Lake, Napa, and Sonoma counties. A long-term understanding of fire and vegetation patterns is needed to inform hazard reduction and forest resilience strategies, and to advance the public awareness needed for improved fire readiness across the region. Four study areas, covering about 200 sq mi. and identified by CAL FIRE as places where communities and the environment are at elevated risk from wildfire, were chosen: one each in Lake, Napa and Sonoma Counties and one straddling the ridge between Napa and Sonoma. Three were in the Mayacamas Range, 30-40 miles inland, and one along the Russian River, about ten miles inland. Indigenous elders provided long-term data for fire and vegetation patterns within a context where cultural burning was regularly practiced. Historical vegetation change over the last 150 years was assessed with a suite of historical surveys and vegetation maps, covering the period from 1870 – 2020. To compare time periods, vegetation data was sorted into broad Lifeform and Forest Type categories. Fire history was assessed using CAL FIRE-mapped perimeters dating to the 1940s and narrative sources (e.g., newspapers) to extend and other narrative sources, earlier fires were mapped to the late 19th century, thus creating a fire record that coincided with the vegetation record. Frequent Burn Zones (FBZs), Rare Burn Zones (RBZs) and Timber Harvest Zones (THZ) were identified and analyzed for vegetation changes and post-fire recovery. Results showed an overall decline in shrublands and an increase in woodlands during the study period. The most fire-prone places were the places where the most dynamic vegetation change occurred. In as little as three decades, places that were exclusively shrublands (100%) in the aftermath of fire, became primarily woodland (65%). Catastrophic fires appear to show a correlation with woodland cover >60%. This has implications for developing a univariate ‘fire exposure metric’ for guiding cultural and prescribed burning and other fuel reduction strategies.
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Within the last ten years, some of the most destructive and deadly wildfires in California history have occurred in Lake, Napa and Sonoma counties. Dozens of people died in these fires, hundreds of thousands evacuated, and nearly 10,000 homes and structures were destroyed. The goal of this project is to better characterize long-term fire and vegetation patterns to inform hazard reduction and forest resilience strategies, and to advance the public awareness needed for improved fire readiness across the region.
In facing the current situation, firefighters, land stewards and the public are realizing that our long-established practices no longer serve us well. There is a recognition that fundamental changes are needed. Most of us are relative newcomers to this land, with roots going back a few generations at most. To thrive here in the long run, or even just survive, we need a deeper understanding of this place. Part of that understanding will be built from scientific studies of vegetation, fire, climate and related disciplines Such knowledge is valuable and useful, but it can perpetuate the illusion that, with enough data, control is possible, and that fire is an adversary to be fought. Effectively reimagining our role as human beings in the landscape and changing our relationships with fire and vegetation is going to require a much broader vision.
As part of that reimagining, this study took an interdisciplinary approach. We incorporated an array of historical and scientific sources and gave equal weight to the perspectives and traditional wisdom of our local Indigenous community. Several people with first-hand experience of cultural burning, as well as knowledge passed down from past generations, shared their knowledge with us. For this gift we are extremely grateful. This Indigenous wisdom (aka Traditional Ecological Knowledge) is a slender thread going from the present all the way back to the beginnings of human time in our region. Clint McKay (Dry Creek Pomo, Wappo, Wintun), Chair of Pepperwood’s Native Advisory Council, shared that he can’t identify his earliest memories of cultural burning it’s part of a cultural tradition extending back to before he was born. Personal memories are less important than the combined memories and experiences of those who came before. As a foundation for responsible stewardship, that knowledge is a form of generational wealth.
Another holder of Indigenous wisdom contacted during this study was Redbird (Pomo, Paiute, Wintu and Wailaki), Stewardship Coordinator at Heron Shadow, a ‘Biocultural Oasis’ in Graton, owned and stewarded by the Cultural Conservancy. On seeing vegetation maps created for this project, he observed that they show ‘what happens when the land is not being tended properly.’ Considering how long his people and their neighbors have cared for this place, that idea makes an appropriate framework for reflecting on the 150 years of vegetation and fire history collected here. If fire can be considered a member of the community, as Heron Shadow’s director Sara Moncada puts it, then the recent catastrophic fires highlight the consequences of ignoring that community member, or thinking we can banish them entirely.
The bulk of this report covers what has happened over the 150-plus years since Indigenous stewardship has been excluded from the landscape. Historical data, including fire and vegetation maps, was collected and created within areas defined as ‘high fire risk’ by CAL FIRE. As a set of ‘natural experiments’ over a long period of time, it evaluates the influence of various factors on local fire history including vegetation changes over that period. No modeling was done for this study, though several landscape and ecological parameters, such as slope aspect and vegetation type, used in fire modeling, were analyzed.
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INTRODUCTION
Within the four study areas in Lake, Napa, and Sonoma counties, modern fire suppression began in the 1930s or 1940s. Thus, about half the record documented in this report occurred prior to suppression and half later, giving something of a ‘before and after’ picture of conditions. The earliest ‘mappable’ data used in this study was collected by surveyors working for the General Land Office, primarily in the 1860s and ‘70s. These 19th-century surveys can be challenging to interpret. Nevertheless, they offer an extremely fine-grained picture of the land and the vegetation on it as it existed just a few years after Indigenous stewardship had ended or gone into steep decline.
Fire regimes in California are highly variable. To be effective, vegetation and land stewardship must account for this variability (Stephens et al 2014). In contrast to southern California (Syphard et al 2019), this study demonstrates that post-fire vegetation recovery in more northern counties can be rapid and dynamic. In many of the most fire-prone areas covered in this study, shrublands (mapped at 100%) converted to woodlands (65% or more) in just three decades. A decade or two later, after the next wildfire comes through, shrublands return and the cycle begins again. Forest recovery after timber harvest occurs almost as quickly with ‘barren’ land returning to 59% forest in about four decades. Within these landscapes are places where no fires or major disturbance have been recorded in the last 150 years.
The Napa East study area illustrates this landscape variability well, with vegetation patterns in sharp contrast to the other study areas. Though it is the most fire-prone of our study areas, it does not follow the pattern mentioned above vegetation change in the wake of fire proceeds so slowly as to be nearly undetectable. Whether this is due to a difference in soils, precipitation or some other factor is unknown at this point.
Mapping and describing the changes in vegetation patterns and fire over the last 150 years is inherently challenging. As described in the Methods section, it requires distilling vegetation data down to its ‘least common denominator.’ What this approach lacks in precision it makes up for in a longer time scale and expanse of landscapes. This lens makes visible the broad outlines of vegetation change over a century and a half and allows us to put present conditions in context. Some line descriptions in the 19th-century surveys are challenging to interpret. Others, like “mostly only chaparral,” provide a sharp and undeniable contrast in places now heavily forested.
Landscapes reflect the practices and preferences of the people living in them, according to the amount of care and attention they receive, or the lack of it. The only known factor which can account for the prevalence of chaparral in the 19th-century surveys is a widespread tradition of cultural burning. As a way of “proper tending,” cultural burning was done in many kinds of habitats. The incidence of chaparral in the surveys is just the most visible marker in the historical record.
It is well known that human actions can harm the natural world. But things are also thrown out of balance by a lack of engagement and stewardship. Recent catastrophic wildfires indicate that this lack of human involvement not only threatens natural systems but puts us in danger as well. It’s impossible to say what our landscapes, with proper tending, could look like in another 150 years. By looking back a century and a half, this report offers a foundation for such long-term thinking through the following lines of inquiry:
1. How has the relationship between vegetation, fire, and people changed over time?
2. What is the relationship between fire frequency, vegetation trends and cycles, landscape variables, and post-disturbance regeneration?
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3. Do vegetation patterns, or other landscape factors suggest a tipping point for large or catastrophic fires? How do these compare with other possible tipping points such as temperature, humidity and wind speed?
4. What is the most effective point in the fire/revegetation cycle for fuel reduction efforts to minimize wildfire emissions and threats to communities and ecosystem services, while also maximizing carbon sequestration for a given location?
5. How might we use fire as a stewardship tool to improve the ecological health of the land?
These questions will be referred to in the ‘Methods’, ‘Results,’ and ‘Discussion’ sections that follow, using these abbreviated phrases:
1. Relationship of vegetation, fire, and people
2. Fire frequency, vegetation patterns and landscape variables
3. Minimizing emissions, maximizing sequestration
4. Tipping points for catastrophic fire
5. Fire as a stewardship tool
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SETTING
The Study areas (Fig. 1) were chosen according to two criteria:
• Places where communities and/or natural resources are at risk from wildfire.
• Places where long-term vegetation records are available
A comparative summary of the characteristics of each study area is included in Table 1 below. A map showing the locations of the four study areas is shown in Figure 1. on the following page Individual maps of each study appear in both the ‘Selected Results’ section and the ‘Comprehensive Results by Study Area’ section of the Appendix.
Table 1. Study Area Summary Characteristics
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NAME EXTENT LOCATION HUMAN IMPACTS RECENT LARGE WILDFIRES VEGETATION (>2%, in order of abundance) Napa East 48 mi2 31,020 acres Mayacamas Range East side of Napa Valley Most inland study area Vineyards Rural development 16% footprint in 2016 Atlas fire 2017 Atlas fire 1981 Atlas fire 1965 Hardwoods Chaparral Grassland 2016 SonomaNapa 48 mi2 30,657 acres Straddles Mayacamas ridge between Sonoma and Napa Valleys Vineyards Rural development 10% footprint in 2013 Nunns fire 2017 Nunns fire 1964 Hardwoods Conifers Chaparral Grasslands 2013/2016 Sonoma West 20 mi2 13,010 acres Russian River Valley northeast of Guerneville Most coastal study area Past timber harvest Rural development 6% footprint in 2013 Walbridge fire 2020 Conifers Hardwoods Grassland Chaparral 2013 Lake 78 mi2 49,624 acres Mayacamas Range immediately south of Clear Lake Most northern study area Past timber harvest Rural development 5% footprint in 1993 Valley fire 2015 Conifers Hardwoods Chaparral Grassland 1993 TOTAL 194 mi2 124,311 acres
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Figure 1. Study Area Regional Map
METHODS and MATERIALS
The landscape covered in this report was identified as a high priority by CAL FIRE and defined as “places in which specific actions can be taken to reduce risk to a forest asset.” Those actions include: Reducing Wildfire Risks to Ecosystem Services; Restoring Fire Damaged Areas; and Reducing Wildfire Threat to Communities. This study highlights areas at particular risk of wildfire but is not intended to be a definitive study of vegetation and wildfire for the region. By the same token, even within the relatively limited area of this study (about 5% of Lake, Napa and Sonoma Counties) there are significant differences between study areas.
INDIGENOUS WISDOM (Traditional Ecological Knowledge)
Applies to: 1) Relationship of vegetation, fire, and people; 2) Fire frequency and vegetation patterns;
5) Fire as a stewardship tool
Clint McKay (Dry Creek Pomo, Wappo, Wintun) spent several hours at Pepperwood recounting his knowledge of cultural burning. A relative of well-known culture keepers Mabel McKay (Cache Creek Pomo) and Laura Somersal (Wappo, Dry Creek Pomo), Clint’s knowledge of cultural burning practices extends in an unbroken lineage all the way back to pre-European settlement days. His experiences growing up on the Dry Creek Rancheria near Healdsburg included direct, first-hand experience with cultural burning. With his multi-tribal background, Clint’s ancestry extends to three of the study areas: Napa East, Sonoma-Napa and Sonoma West.
Another source of Indigenous knowledge was Edward Redbird Willie (Pomo, Paiute, Wintu and Wailaki), Stewardship Coordinator at Heron Shadow, a ‘Biocultural Oasis’ near Graton owned and tended by the Cultural Conservancy. During an on-site tour, Redbird shared his perspective on cultural burning and directed me to several online videos in which he spoke about cultural burning. The Director of Heron Shadow, Sara Moncada (Yaqui/Irish), also contributed her thoughts and perspectives during the on-site tour including the ongoing story of how Heron Shadow has been working with their neighbors to bring cultural burning back to the land.
Several attempts were made to contact an elder at the Middletown Rancheria (Pomo), whose people’s ancestral homelands include the Lake study area. Unfortunately, these were unsuccessful as of the close of the project. As cultural burning practices were somewhat varied from place to place, it should be acknowledged that the information in this report is in no way complete for the region, and the lack of contact with the Middletown Rancheria is a potentially significant gap.
An observation by Clint McKay regarding Douglas fir distribution was corroborated with changes recorded in the historical data. These results are included in a section of the Discussion.
HISTORICAL RECORD
Applies to: 1) Relationship of vegetation, fire, and people; 2) Fire frequency and vegetation patterns; 3) Minimizing emissions, maximizing sequestration; 4) Tipping points for catastrophic fire;
5) Fire as a stewardship tool
Past efforts which informed this project include: the Sonoma Veg Map (Sonoma County 2017); the Napa Veg Map (Napa County 2016); Marin County Historical Wildfire Mapping Project (Dawson 2022); Historical Fire, Vegetation & Change Analysis Project, Bouverie Preserve (Dawson 2019); Estimating Vegetation Reference Conditions by Combining Historical Source Analysis and Soil Phytolith Analysis at Bouverie Preserve (Evett et. al. 2012. Published in Restoration Ecology); Historical Vegetation Upland Pilot Project (Dawson 2014a); and others in the region.
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The approaches used in this study to characterize historical vegetation, map wildfire perimeters in the pre-CAL FIRE era, and to integrate vegetation and fire patterns were largely developed during the efforts mentioned above. This study extends that work by covering a broader geographical area, tapping into the Indigenous wisdom (Traditional Ecological Knowledge) of local tribes, utilizing previously unused sources (such as the SoilVeg maps), and developing trajectories for timber harvest recovery to compare with recovery from wildfire.
Data was collected from a variety of online and physical archives These historical data sources were digitized and mapped using Geographic Information Systems. Quantitative results and summaries are provided in tabular (see ‘Selected Results’ and ‘Appendices’).
MAPPING and MEASURING VEGETATION CHANGE
Applies to: 1) Relationship of vegetation, fire, and people; 2) Fire frequency and vegetation patterns;
3) Minimizing emissions, maximizing sequestration; 4) Tipping points for catastrophic fire;
5) Fire as a stewardship tool
Tracking vegetation changes over long periods of time requires “translating” data collected using different methods and for various purposes into common categories to create a consistent and transparent basis for comparing change over time. Vegetation data sources include:
• General Land Office surveys (predominantly 1860s/70s)
• Vegetation Type Maps or VTMs (1928, 1932. aka ‘Wieslander maps’)
• Soil-Vegetation Maps (1950s/60s)
• Wildlife Habitat Relationship Maps (1993) CA Dept of Fish and Wildlife
• Sonoma County Vegetation Map (2013)
• Napa County Vegetation Map (2016)
(Note that these dates refer to when the data was collected, not necessarily when it was released. This is important for calculating rates of change following a disturbance occurring at a specific point in time.)
Developing a consistent and transparent approach for comparing these half-dozen data sets required distilling the data through the following two filters:
1) Sort the data into five main categories. Because vegetation in all eras was recorded ‘in order of predominance,’ (quote from the 1858 survey manual) it can be sorted into the Lifeform groups herbaceous, shrublands and woodlands used in the Manual of California Vegetation (MCV; CNPS 2007)Or, where those fall short, the addition of ‘Human’ and ‘Other’ covers all the data collected throughout the study period.
2) Where possible, sort the data further into forest types identifiable in all eras (see MCV 2009 and ‘Vegetation Crosswalk’ in Appendix for more detail)
All the data collected over the study period was sorted into these categories, as shown and described in Table 1 on the following page, which provided the primary framework for analyzing vegetation patterns and change over time. These large categories minimize error when comparing vegetation over a long timespan. It is assumed that the data collectors in all time periods could distinguish between these main categories. Identifying vegetation alliances and associations from the historical data is much more uncertain and thus more prone to error and misinterpretation.
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TABLE 2. Vegetation Categories applicable to all data
MAIN CATEGORIES SUBCATEGORIES MCV DEFINITIONS (CNPS 2009; pgs.51-55) EXAMPLES
WOODLANDS “Trees evenly distributed and conspicuous” (MCV category I)
SHRUBLANDS
HERBACEOUS
HUMAN
OTHER
Conifers “Dominated by conifers” (MCV sub-category 4’. 8’)
Oak, Madrone, Alder
Douglas fir; Knobcone Pine Hardwoods “Dominated by evergreen or winter deciduous hardwood trees, or conifers may be associated with them and co-dominant.” (MCV sub-category 4’. 8.)
“Woody shrubs or sub-shrubs conspicuous” (MCV category II)
“Non-woody herbaceous vegetation dominant” (MCV category III)
Human footprint dominant (no MCV definition)
Lack of vegetation dominant (no MCV definition)
Chamise; Manzanita
Native and nonnative grassland, e.g. bunchgrass, Avena spp.
Vineyards, Orchards, roads, structures
Water, rocks, or ‘no data’
Vegetation data for 1993 to the present (WHR, Sonoma Veg Map, Napa Veg Map) was readily available in GIS as polygon shapefiles. Likewise, the Wieslander Vegetation Type Maps (VTM) had already been digitized and brought into GIS with original attributes as well as Wildlife-Habitat Relationship maps (WHR) and MCV classifications. Processing the Soil-Veg maps and the General Land Office surveys (GLO) required laborious ‘heads up’ digitizing drawing the polygons by hand on screen (or lines and points for the surveys) and attributing each feature with the original data.
Once the vegetation record for each study area was brought into GIS, the data was made into maps (see ‘Selected Results’) as well as tables. The ‘Create Report’ feature in GIS was an essential tool for compiling all the data into a form that could be easily input into the tables.
The most current vegetation maps were all produced before the most recent catastrophic fires. In Sonoma county, these maps pre-date the Nunns and Walbridge Fires by 4-7 years respectively; in Napa East, the Atlas Fire by just 1 year; and in Lake county, the Valley Fire by 22 years. We don’t yet have an overview of how the land has and will respond in present time. An update of the Sonoma Veg map is underway, which will provide a look at about 5-7 years of recovery.
The name of trees and shrubs vary somewhat over the study period, with the most variation being in the early surveys. Discrepancies could usually be resolved by researching historical names (e.g. ‘Chemizal’ for Chemisal or Adenostoma fasciculatum, or Madroño for Madrone. see Vegetation Crosswalk in Appendix). Cases which could not be resolved to the species level could still be slotted into lifeform categories or better, allowing changes to be detected at a coarser level.
Mapping resolution varies widely over the study period (Table 3) and was accounted for during the change analysis. The intent of this study was to identify the most significant shifts in vegetation, while conserving as
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much detail as possible. To avoid creating the impression of a higher degree of accuracy than actually exists, percentages of vegetation cover were rounded to the nearest whole number.
TABLE 3. Vegetation Data Mapping Resolution
MAPPING RESOLUTION
Average acres/polygon
*GLO: = Total Acres/#Survey points + Line Descriptions =acres per data ‘bit’
The uncertainties associated with the 19th-century survey data (GLO) present a unique challenge that has been addressed in previous work (Dawson 2014a). Mapping vegetation from the survey record requires accounting for the known biases in the choice of bearing trees (hardwoods over conifers); the unbiased but less precise line descriptions, while also accounting for the proportion of actual bearing trees to the number that would have been marked if they had been available. Every mile of survey line was supposed to have 6 trees marked (four at the section corner and two at the quarter-section corner), if possible. Sometimes only one or two trees were marked and in many cases the surveyors had to build a cairn instead of marking a tree. The lack of bearing trees was interpreted to indicate shrub or grass at those sites rather than woodland (or ‘rock’ or ‘barren’ if warranted by nearby data). Sites that were consistently recorded as shrublands in later years were assumed to be the same for the early surveys. The percentage of marked trees to the total number possible was considered the most accurate measure of woodland cover in the GLO data. Trees <8” diameter marked along survey lines described as shrublands were designated as shrubs.
Figures for the resolution of the GLO surveys may not be directly comparable to the other periods, due to the way this data was collected and recorded. However, it does indicate the level of detail with which the land was surveyed. Accounting for the accuracy of these surveys (see Evett et. al. 2012 and Dawson 2014a), and the distances bearing trees were located from survey points (in both cases < 3 chains = 60 m or ~200 feet), we roughly estimate that the 19th century surveys recorded about 25% of the landscape at some level of detail. Little or no detail should be assumed for the remaining 75%.
For an extensive discussion about using the data from the GLO surveys, see the “Historical Vegetation Mapping Upland Pilot Project” (Dawson 2014a). Available at https://sonomaopenspace. egnyte.com/dl/fNMHZANzqD
It is widely held that the State of California planted Knobcone pines, Harding grass and perhaps other species as a way of reducing erosion and reseeding forestlands after the 1964 Nunns, Hanley, and probably other fires. Some of this is said to have been done by broadcasting seeds from airplanes. While there is no reason to doubt this, and it seems quite plausible, no primary historical records have been located to support this. Botanical
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STUDY
AREA
GLO* c. 1870 VTM 1928, 1932 Soil-Veg c. 1950, 1965 WHR 1993 Veg Maps 2013, 2016 LAKE 42.9 145.1 45.9 10.9 SONOMA WEST 41.3 68.8 15.6 3.2 SONOMA-NAPA 29.0 115.2 20.1 5.9 NAPA EAST 49.2 155.7 9.2 7.5 AVERAGE 45.6 138.7 57.4 14.0 4.6
records going back to the early 20th century show Knobcone pine within the 1964 Nunns’ perimeter decades before that fire
It also seems quite likely that commercial species of conifer, particularly Ponderosa pine and Douglas fir, would have been planted after timber harvest occurred in Lake and perhaps in Sonoma-West as well. Boggs State Forest is currently restoring forest that was burned in the 2015 Valley fire by planting these species (CAL FIRE 2023). This effort is not reflected in the vegetation data used in this study because the most recent vegetation map for the area was made in 1993.
MAPPING HISTORICAL FIRE EXTENT and FREQUENCY
Applies to:
1) Relationship of vegetation, fire, and people; 2) Fire frequency and vegetation patterns; 3) Minimizing emissions, maximizing sequestration; 4) Tipping points for catastrophic fire; 5) Fire as a stewardship tool
Highly accurate CAL FIRE perimeters going back to the 1940s were used for the latter part of the historical record. Drawing perimeters for fires preceding the CAL FIRE era required using the data from narrative accounts in newspapers and other sources. With the exception of the Lake study area, such accounts were accessed online from the California Digital Newspaper Collection at www.cdnc.ucr.edu/
As historical newspapers for Lake county are not yet digitized, data development required visually scanning microfilm at the Lakeport Library. Because headlines were not used for Lake County newspapers before 1900, locating early fire data required visually scanning large blocks of text. The large volume of newspaper data combined with poor image quality, made it important to prioritize time periods. Consequently, most of the pre1900 period was skipped. With a few exceptions, the Lake county fire record begins in 1909.
Historical maps were essential to georeferencing early fire perimeters because old ranch names, bridge crossings and place names from the newspaper reports could be located and used for mapping on contemporary maps. Fire characteristics, including location and extent, were tabulated. A rubric for assigning confidence levels for location and extent (high, medium and low) to these historical fire polygons was developed and applied as an attribute to each perimeter (see Appendix). Each fire was also entered in a table for each study area with columns for extent, date, weather conditions (if known), and the dates of previous fires within the perimeter
The ‘Overlay’ tool in GIS was used to create shapefiles that divided up each study area into polygons drawn according to how many times each area had burned (see ‘Fire History’ maps in ‘Selected Results’). This made the following features visible, which were classified into the following categories (one per study area):
‘Frequent Burn Zones’ (FBZs), defined and delineated according to three criteria:
1) An area that had burned substantially more often than other parts of the study area.
2) Was a single, contiguous polygon not a scattering of polygons. This allowed FBZs to be evaluated as a single landscape unit.
3) Had at least one discrete date when the whole FBZ burned, which could be used to track post-fire vegetation change over time.
‘Rare Burn Zones’(RBZs), which were delineated according to two criteria:
1) Areas that had burned less often than elsewhere in the study area (usually never).
2) Were contiguous, allowing them to be evaluated as single landscape units.
Up through the mid-20th century, ranchers sometimes burned rangeland, woodland and chapparal to clear brush and create forage for livestock (Sampson 1944). These fires were almost always undocumented unless they
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escaped and burned a neighbor’s property. While these fires undoubtedly had some effect on the overall fire history, not enough is known to assess the effect.
MAPPING HISTORICAL TIMBER HARVEST EXTENT
Applies as an alternative disturbance for comparison to: 2) Fire frequency and vegetation patterns
The discovery of a 1926 map of ‘Cut-over Redwood Lands’ (Weber 1926), along with additional historical background, allowed a ‘Timber Harvest Zone’(THZ) to be delineated in the Sonoma West study area and evaluated as a separate landscape unit. The mapping of ‘Barren’ vegetation units in the Lake study area in 1950, just after a large commercial logging operation finished, suggested that this was also a ‘Timber Harvest Zone.’
MAPPING and QUANTIFYING VEGETATION RESPONSE TO FIRE and DISTURBANCE
Applies to: 1) Relationship of vegetation, fire, and people; 2) Fire frequency and vegetation patterns; 3) Minimizing emissions, maximizing sequestration; 4) Tipping points for catastrophic fire; 5) Fire as a stewardship tool
Once all the vegetation, fire, and logging data had been brought into GIS, they were integrated by using the FBZ, RBZ and THZ polygons to clip the vegetation record for each area and trace changes over time. The ‘Create Report’ tool in GIS was used to inventory these landscapes by choosing an attribute, such as vegetation alliance or similar, and directing the tool to calculate the total acreage (e.g. ‘Douglas fir Woodland, 1023 acres’ etc.). This compiled data was used to complete tables and track the changes for each study area, FBZ or other sub area (see Appendix).
Each study area and individual zone was also characterized with the ‘Summarize Elevation’ tool in GIS, which also produced measurements for slope aspect and steepness. Distance from the coast was measured from the centroid for each polygon to the nearest point on the coast. The Sonoma-Napa study area was evaluated as a whole and, for some analyses, divided into the Sonoma-Napa (Napa portion) east of the county line and the Sonoma-Napa (Sonoma portion) west of the line (the county line is on the ridge divide)
EMISSIONS and SEQUESTRATION
Applies to: 3) Minimizing emissions, maximizing sequestration
Emissions and sequestration were investigated through an extensive literature search and communications with experts in the field. Estimates were attempted based on calculated post-fire rates of vegetation change, for above and below ground biomass at various points in the fire cycle, but a lack of data prevented these from being finalized. However, the information collected suggested a general approach and qualitative answer to this question.
TIPPING POINTS FOR CATASTROPHIC FIRE (ADDENDUM)
Applies to: 4. Tipping points for catastrophic fire
As this was not included in the original research plan, we combined additional Methods as well as Results and Discussion in a separate addendum.
Despite the large number of recent catastrophic fires in Lake, Napa, and Sonoma counties, the historical fire record indicated that such fires could be expected to recur in the same places only about once every 40 - 100 years. This suggested creating criteria for ‘catastrophic fires’ based on their unusual size (‘catastrophic’ was chosen over ‘large’ to acknowledge the human impact of these conflagrations) and investigating whether one or more tipping points for these events could be identified
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We looked at wind speed, humidity, fuel configuration and temperature as possible tipping points. Wind speed was tracked over the course of the 2017 Nunns and Tubbs fires. Criteria was developed from the literature to identify ‘wind-driven’ fire conditions from ‘fuel-driven’ fire conditions. MODIS heat maps were used to map the fire spread during these events and ‘percent wind-driven vs. percent fuel-driven’ was calculated (below a threshold of 30 kph wind speed, humidity and temperature alone are not considered sufficient to create extreme fire behavior)
The possibility of a tipping point related to fuel configuration was investigated by estimating the percent woodland cover within these fire perimeters, based on recent vegetation maps and established rates of change.
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SELECTED RESULTS
Since Indigenous wisdom (TEK) preserves the knowledge of fire practices and vegetation patterns which preceded modern vegetation patterns and fire regimes, a summary of conversations with Clint McKay (Wappo, Pomo, Wintun), Edward Redbird Willie (Pomo, Paiute, Wintun and Wailaki) and Sara Moncada (Yaqui/Irish) is included at the beginning of this section. It is intended to serve as a framework for considering the results of the historical research. The Appendix contains the complete notes from these contacts.
These conversations particularly inform three lines of inquiry: 1) Relationship of vegetation, fire, and people; 2) Fire frequency and vegetation patterns; 5) Fire as a stewardship tool
The maps, pie charts and tables that follow (pages 23-48), which were developed from the historical record, are arranged by study area. They provide an overview of vegetation, fire, and timber harvest patterns during the study period (c. 1870 – 2020) and primarily apply to: 1) Relationship of vegetation, fire, and people; 2) Fire frequency and vegetation patterns; 4) Tipping points for catastrophic fire.
The vegetation maps are presented as four ‘snapshots,’ roughly corresponding to:
▪ Late 19th century
▪ Early to mid-20th century
▪ Late 20th century
▪ Early 21st century
The precise years vary according to the available data. Pie charts are included to facilitate visualization of the changes and for ready comparison across time periods and between study areas.
Fire history is combined into a single map for each study area, delineating zones of different fire frequencies. Frequent Burn Zones (FBZs) and Rare Burn Zones (RBZs) are highlighted in these maps.
Timber Harvest Zones (THZs) were mapped from available sources and shown for the Lake and Sonoma West study areas.
Integrated fire and vegetation history are tracked with maps, pie charts and tables for each FBZ and RBZ. These follow the same timeline as the vegetation ‘snapshots’ mentioned above. Vegetation changes within the THZs are covered in the same way.
Calculated rates of vegetation change in response to fire and timber harvest, or in the absence of these disturbances accompany the relevant maps.
Results for the distribution of certain species, which are not covered the Selected Results, are included in the relevant Discussion sections. These species include Douglas fir, California Bay, and California Black oak.
A lack of quantitative data to fully address: “#3) Minimizing emissions, maximizing sequestration” led to it being left out of the quantitative results. However, this line of inquiry, viewed against the background of vegetation change, suggests interesting possibilities and avenues for further research.
Complete tabulated results can be found in the Appendix.
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INDIGENOUS WISDOM
Key points from conversations with Clint McKay, Sara Moncada and Edward “Redbird” Willie:
• Current conditions of vegetation and catastrophic fire are the result of the land not being cared for properly.
• In Indigenous culture, fire is considered a member of the community, far older and wiser than we are.
• Cultural burning was intended to benefit all forms of life.
• Burning was a community activity.
• Burning was done for basket materials, for food and to create travel corridors between villages.
• There was no burning calendar. Close observance of the landscape indicated when to burn.
• Redbud and elderberry were burned every three or four years, after annual harvest.
• The area under a black oak might be burned every couple of years, around late Aug. This makes the acorns easier to gather when they fall, and fire also knocks back acorn worms.
• Burning encouraged the growth of plants and also kept the ground clean.
• Chaparral was tended to especially benefit deer, which use it for forage and cover. Once it gets to be six or eight feet high, it’s harder for the deer to reach the new growth, so it’s burned at that point.
• There were no particular ‘fire specialists.’ Everyone tended the resources they were going to use. Basket weavers burned willows and sedges. Hunters burned chaparral, particularly chamise and leather oak, to provide forage for the deer they were going to hunt.
• The landscape was tended on a small scale. A couple people could handle a burn under a Black oak when conditions were right. An August burn required waiting for a morning with “a little mist, a little dew on the leaves.”
• Larger areas of up to a couple hundred acres were also burned. Travel corridors exceeded this size.
• Cultural burns were started at the bottom of hills and burned toward the top. Ridgetops make a natural fire break. CAL FIRE’s controlled burns are the opposite and backlit downhill.
• The way Traditional Ecological Knowledge looks on the ground may sometimes feel at odds with how it seems when it’s more hypothetical.
• Before contact, there were more oak woodlands and savannah. Douglas fir were on the peaks and ridges. California Bays were in the low places, not canyons exactly, but little drainages that were a little cooler than the surrounding area.
• The decline of cultural burning happened seven generations back counting from the current younger generation.
Complete notes in the Appendix.
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HISTORICAL RECORD
Selected results from the historical research, including maps, pie charts and tables are shown on the following pages (23-48). The map below is identical to the one on page 12 and is included here for ease of reference.
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Figure 2. Sonoma-Napa Study Area, Vegetation Lifeforms—1872 - 2016
c. 1872
1932
1993
2013/2016
Herbaceous Shrub Hardwood Conifer Human Township & Range Lines: 1 mile x 1 mile grid
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SONOMA NAPA c. 1877 1932 1993 c. 1867 1932 2016 SONOMA NAPA EAST Herbaceous Shrub Human Hardwood Conifer 1993 2013
Figure 3. Sonoma-Napa Study Area, Lifeform Comparison by County—1867-2016
Figure 4. Sonoma-Napa Study Area, Fire History:
Documented Fires—1870 - 2020
Average Fire Return Intervals within known fire perimeters (areas without documented fires not included in calculations)
Whole Study Area: 52.9 years, median = 42.0 years
1-2 fires average
Frequent Burn Zone: 28.6 years, median = 28.0 years
4-5 fires average
Napa County: 53.4 years, median = 35.0 years
1-2 fires average
Sonoma County: 55.1 years, median = 44.0 years
2-3 fires average
Township & Range Lines: 1 mile x 1 mile grid
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Herbaceous Shrub Hardwood Conifer Human
c. 1877: Fire history unknown
1932: 9 years post fire
1993: 29 years post fire
2013: 49 years post fire
DATES OF LARGE FIRES: RED = 100% FBZ burned. * only 20 acres were in the FBZ
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Figure 5. Sonoma-Napa Study Area, Frequent Burn Zone (FBZ) Lifeforms—1877-2013
1880 1902 1923
1964 2017 (1996*)
1936
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ANNUAL RATE OF CHANGE (Δ) by
ANNUAL RATE OF CHANGE (Δ) by years post
1877 circa 1932 1993 2013 1964 (est) 2017 (est) 1867-1932 1932-1993 1993-2013 9-29 29-49 Herbaceous 0 0 1 5 3 6 0 0.02 0.2 0.05 0.2 Shrub 56 73 27 13 19 10 0.31 -0.75 -0.7 -2.3 -0.7 Conifer 4 3 31 30 31 30 -0.02 0.46 -0.02 1.4 -0.02 Hardwood 40 23 38 48 44 50 -0.31 0.25 0.5 0.75 0.5 Human/Other 0 1 3 4 3 4 0 0.04 0.05 na na
Table 4. Sonoma-Napa, FBZ, Lifeform Cover by Date and Rate of Change LIFEFORM, % COVER, by date (1964 & 2017 = estimated, immediately preceding major fire)
era
fire
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Figure 6. Sonoma-Napa Study Area, Rare Burn Zone (RBZ) Lifeforms—1867-2016 NO DOCUMENTED LARGE FIRES
Herbaceous Shrub Hardwood Conifer Human
c. 1867
1932
1993
2016
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LIFEFORM, % COVER by date ANNUAL RATE OF CHANGE (Δ) by era c. 1867 1932 1993 2016 1877-1932 1932-1993 1993-2016 Herbaceous 0 1 3 2 0.02 0.03 -0.04 Shrub 64 33 16 11 -0.48 -0.28 -0.22 Conifer 0 1 19 20 0.02 0.3 0.04 Hardwood 29 55 53 59 0.4 -0.03 0.26 Human/Other 7 10 8 8 0.05 -0.03 0
Table 5. Sonoma-Napa, RBZ, Lifeform Cover by Date and Rate of Change
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Figure 7. Sonoma-West Study Area, Vegetation Lifeforms, 1867 - 2013
Herb or Shrub c. 1867 (ambifuous) (a
Herbaceous Shrub Hardwood Conifer Human Township & Range Lines: 1 mile x 1 mile grid
c. 1867
1993
c. 1965
2013
# Fires, % of Study Area
Average Fire Return Intervals within known fire perimeters (areas without documented fires not included in calculations)
Whole Study Area: 36.4 years, median = 27.0 years
1-2 fires average
Frequent Burn Zone: 26.4 years, median = 43.5 years
3-4 fires average
Timber Harvest Zone 50.0 years, median = 45.0 years
<1 fire average
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Figure 8. Sonoma West Study Area, Fire History: Documented Fires—1902 - 2020
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Figure 9. Sonoma West Study Area, Frequent Burn Zone (FBZ) Lifeforms–1867 - 2013 MAJOR FIRES IN 1917, 1929, 1933, 1959, 2020 (Red = 100% FBZ burned)
POST 1959 FIRE RECOVERY, 1965 – 2013
6
1993 34
c. 1965
years post fire
years post fire 2013 54 years post fire
c. 1867: 15 years after last known record of cultural burning
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ANNUAL RATE OF CHANGE (Δ),
years
(era) 1965 1993 2013 2020 (est) 6-34 (1965 – 1993) 34-54 (1993 – 2013) Herbaceous 3 2 2 2 -0.02 0 Shrub 47 17 7 4 -1.1 -0.5 Conifer 4 20 56 69 0.6 1.8 Hardwood 44 60 33 23 0.6 -1.4 Human/Other 2 1 1 1 na na
Table 6. Sonoma West, FBZ, Lifeform Cover by Date and Rate of Change LIFEFORM, % COVER, by date (2020 = estimated, immediately preceding major fire)
by
post fire
Figure 10. Sonoma West Timber Harvest Zone (THZ): Intensive Logging, c. 1875 – 1915
Note: this zone includes the Rare Burn Zone for the Sonoma West study area. Because timber harvest was a significant disturbance, this zone is being evaluated through that lens rather than as a Rare Burn Zone (RBZ).
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c.
Pre-intensive harvest
1993: 80 – 120 Years post harvest
Intensive Logging
c.
50-90 Years post harvest
2013: 100 – 140 Years post harvest
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Figure 11. Sonoma West Timber Harvest Zone (THZ) Lifeforms—1867 - 2013
Herb or Shrub (c. 1867) Herbaceous Shrub Hardwood Conifer Human Township & Range Lines: 1 mile x 1 mile grid
1867:
1965.
c. 1875 – 1915
Table 7. Sonoma West, THZ, Lifeform Cover by Date and Rate of Change
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Consulting,
LIFEFORM, % COVER, by date ANNUAL RATE OF CHANGE (Δ), by era & years post harvest c. 1895 = average harvest date c. 1867 1965 1993 2013 1867 - 1965 Pre-harvest to early recovery 1965 – 1993 c. 70 - 100 years post harvest 1993 – 2013 c. 100 -120 years post harvest Herbaceous 1 3 2 3 0.02 -0.04 0.05 Shrub 13 1 1 1 -0.12 0 0 Conifer 52 10 54 66 -0.55 1.6 0.5 Hardwood 17 61 20 19 0.4 -1.6 0.05 Human/Other 1 26 22 11 0.26 -0.1 -0.6
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Figure 12. Lake Study Area, Vegetation Lifeforms, 1873 - 1993
1928
c. 1950
1993
c.1873
No data, Barren or Other
Township & Range Lines 1 mile x 1 mile grid
Frequent Burn Zone (FBZ) 3-5 Fires
No documented burn: 16%
Average # fires: 2-3
Rare Burn Zone (RBZ) 0 fires
Average Fire Return Intervals within known fire perimeters
(areas without documented fires not included in calculations)
Whole Study Area: 39.0 years, median = 29.0 years
1-2 fires average
Frequent Burn Zone: 26.4 years, median = 26.0 years
3-4 fires average
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Figure 13. Lake Study Area, Fire History: Documented Fires—1874 - 2020
Figure 14. Lake Study Area, Frequent Burn Zone (FBZ) Lifeforms–1873 - 1993
MAJOR FIRES in: 1874, 1909, 1915, 1922, 1944, 1951, 2015 (Red = 100% FBZ burned)
No data, Barren or Other
c. 1873: fire history unknown
c.1950: 6 years post fire
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1928: 19 years post fire
c.1873: Fire
History unknown
1928: 19 years post fire
1993: 49 years post fire
40
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Figure 15. Lake Study Area, Frequent Burn Zone (FBZ) Post fire Shrub Transitions, 1950 - 1993
LIFEFORM, % COVER by date ANNUAL RATE OF CHANGE (Δ) 6 – 49 years post fire c. 1950 1993 Chamise 33 <1 -0.77 Mixed Chaparral: Manzanita & Quercus spp. 67 450.51 Conifer 0 38 0.88 Hardwood 0 16 0.37 Other 0 1 .020
49
Table 8. Lake FBZ, Post fire Shrub Transitions, Lifeform by Date and Rate of Change
1993
years post fire
fire
& Range
c.1950: 6 years post
Township
Lines 1x1 mile grid Other Mixed Chaparral: Manzanita & Quercus spp. Pie charts only
Chamise & Mixed Chaparral Pie chart & Map
Conifer Hardwood c. 1950
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Figure 16. Lake Study Area, Rare Burn Zone (RBZ) Lifeforms—c. 1866 - 1993 NO DOCUMENTED LARGE FIRES. SOME TIMBER HARVEST, 1940S.
Barren (Harvested?)
Township & Range Lines 1 mile x 1 mile grid
c. 1866
1928
c.
1950 1993
Table 9. Lake Study Area, RBZ, Lifeform Cover by Date and Rate of Change
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LIFEFORM % COVER, by date ANNUAL RATES OF CHANGE (Δ), % cover of Study Area 1866* 1928 c. 1950 1993 1866 – 1928 1928 - c. 1950 c. 1950 - 1993 Herbaceous 6 11 13 2 0.08 0.09 -0.26 Shrub 3 2 8 1 -0.02 0.27 -0.16 Conifer 89 86 36 57 -0.05 -2.27 0.49 Hardwood <1 <1 21 34 0 0.95 0.30 Human 1 <1 6 6 0 0.23 0 Other: Unknown, Water, or Barren 0 <1 15 <1 0 0.68 -0.35
Herbaceous or Shrub (uncertain)
17. Napa
Study Area, Vegetation Lifeforms, 1863-2016
No data, Barren or Other
Township & Range Lines 1 mile x 1 mile grid
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Figure
East
c.1863
1932
1993
2016
Documented Fires: 1879-2020
Average Fire Return Intervals within known fire perimeters (areas without documented fires not included in calculations)
Whole Study Area: 38.6 years, median = 38.0 years
2-3 fires average
Frequent Burn Zone: 26.8 years, median = 24 years
4-5 fires average
Rare Burn Zone: 68 years, median = 68 years
1-2 documented fires
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Figure 18. Napa East Study Area, Fire History:
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Figure 19. Napa East Study Area, Frequent Burn Zone (FBZ), 1863-2016 FIRES in 1913, 1936, 1959, 1960, 1968. 1981, 2012, 2013, 2017 (red years > 80% of FBZ burned)
c.1863
1932
1993
2016
Table 10. Napa East, FBZ, Lifeform Cover by Date and Rate of Change
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LIFEFORM % COVER, by date ANNUAL RATES OF CHANGE (Δ), % cover of Study Area C. 1863* 1932 1993 2016 1863 – 1932 1932-1993 1993-2016 Herbaceous 2 1 9 7 -0.07 0.13 -0.09 Herb. or Shrub (uncertain) 15 0 0 0 NA NA NA Shrub 30 40 34 35 -0.03 -0.1 0.04 Conifer 0 0 1 1 0 0.02 0 Hardwood 50 55 43 43 0.07 -0.2 0 Human 2 5 5 7 0.04 0 0.09 Other: Water, Open or Barren 0 0 6 6 0 0.1 0
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Figure 20. Napa East Study Area, Rare Burn Zone (RBZ) Lifeforms, 1876-2016 Burned in 1913 and 1981.
c. 1876
1932
1993
2016
Table 11. Napa East, RBZ, Lifeform Cover by Date and Rate of Change
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LIFEFORM % COVER of RBZ, by date ANNUAL RATE OF CHANGE (Δ), % cover of Study Area c. 1876* 1932 1993 2016 1876 – 1932 1932-1993 1993-2016 Herbaceous 2 4 3 2 0 -0.02 -0.02 Herb. or Shrub (uncertain) 3 0 0 0 NA NA NA Shrub 61 59 45 41 -0.04 -0.23 -0.17 Conifer 0 0 0 1< 0 0 <0.01 Hardwood 31 31 30 30 0.02 -0.02 0 Human 4 5 21 26 0 0.26 0.22 Other: Water, Open or Barren 0 0 <1 <1 0 -0.02 0
DISCUSSION
FIRE and VEGETATION UNDER INDIGENOUS STEWARDSHIP
“Listen to the land, it will tell you what it needs.”
Clint McKay (Wappo, Pomo, Wintun)
Applies to: 1) Relationship of vegetation, fire, and people;
2) Fire frequency and vegetation patterns; 5) Fire as a stewardship tool
Indigenous stewardship should be considered within a cultural context with a completely different world view than the mainstream culture. At the root, this is perhaps the most important lesson we can receive from Native people. If we want things to be different in the future, we will need to begin by considering alternative approaches to fire and vegetation and our relationship with them. Conversations with several Indigenous elders led me to reflect on a number of ideas:
• Fire and vegetation are entities with their own agendas.
• Their agendas don’t necessarily align with ours.
• Human knowledge and control are limited, so humility is wise and appropriate.
• Rather than seeking control, ask: what is the appropriate role of human beings in the landscape? This may include:
o Tending or stewardship
o Helping maintain a balance among living things
• Decisions are based on observation rather than by the calendar.
• Human health and sustenance depend on the health of everything else
• Long-term thinking creates generational wealth
Bullet points cannot capture the nuance and depth of these ideas and may even be misleading. The spoken word is considered the most trustworthy source of knowledge. It should be noted that these are not the direct words of any of the Indigenous elders I spoke with. I don’t believe any of them would claim to speak for someone else. I don’t intend to do that either, but hope to pass along a little of the wisdom and perspective they gifted to me and ask forgiveness for any mistakes or misrepresentations.
As mentioned in the Introduction, Redbird, the Stewardship Coordinator at Heron Shadow, upon seeing the maps in this report, told me that “this is what this place looks like when it’s not being tended properly.” Jose Altimira (as founder of the Sonoma Mission, colonized the traditional lands of the Coast Miwok, Wappo, Pomo and other Indigenous peoples), provides a glimpse of how the land was being tended when he arrived in 1823: “[the hills] were soon to be burned of the long grass by the Indians we met.” Without realizing it, he goes on to describe the result of that tending, “the place is bare of thick woods” (Smilie 1976). What Altimira is describing is a cultural landscape, one shaped by Indigenous practices carried out and refined over many thousands of years Cultural burning was integral to that landscape, an expression of those practices. Just as wildfire is an integral, though unwelcome part of our own cultural landscape.
Cultural burning was widely used by Indigenous peoples in California (Stephens et. al. 2007). Clint McKay’s people occupied three of the four study areas Napa East, Sonoma-Napa and Sonoma West. He described the difference between cultural burning and controlled or prescriptive burning as coming down to who it was intended to benefit "human beings or all living things on the land?” Burning was practiced at a very fine scale. There were no particular fire specialists. Everyone burned the resources they were going to use basket weavers burned willows and sedge beds, hunters burned the chaparral to provide forage for deer.
Clint said that there used to be a lot more redbud and hazel, which were burned to encourage growth. As was elderberry. Cultural burning acted as a pesticide and kept the ground clean. Burning was also used to keep travel corridors open. Such corridors existed between the Dry Creek area and the coast, over to Alexander Valley and across the northern flank of Kanamota (Mt. St. Helena) to the Middletown area and Clear Lake.
Ridgetops, like those at Pepperwood, also served as travel corridors. Clint’s people lived on either side and would burn uphill from both sides. Burning from the base of a slope up tended to push the Douglas fir to the tops of the ridges and kept them from coming down into the valleys. Bays trees tended to be in low places that were cooler than the surrounding area (he remarked that they seem to be adapting to a different climate and showing up in hotter, more open areas, though they don’t seem particularly healthy).
Clint said their goal for burning included the well-being of plants and animals as well as people. They tended chaparral especially for the deer, who use it for forage and cover. There was no set schedule for burning, it didn’t go by the calendar, but rather from observation. Once Chamise, Leather oak and other chaparral plants get to be six or eight feet high, it’s harder for the deer to reach the new growth, so it would be burned at that point.
The area under a black oak might be burned every couple of years, typically in late August. This was partly to make the acorns easier to gather when they fell in the autumn, and fire also knocked back the acorn worms. You’d wait for a morning with a little mist, a little dew on the leaves. It was small scale a couple people could handle it. They also burned areas as large as a hundred or two hundred acres. He heard that near Lytton Springs there were huge beds of clover and places that supported wild onions and carrots.
The GLO surveys used in this study were mostly done in the 1860s and 1870s, with a few going back to as early as 1853. There are reports of cultural burning going on at some scale in the Russian River Valley in 1851 (Marryat 1855) and probably elsewhere in the region. The surveys represent vegetation as it was near the end of extensive tending by Indigenous peoples, or just after. It should be kept in mind that the GLO surveys only covered the boundaries of Mexican land grants and the areas outside them so a detailed record of the valley floors is largely missing. But for the uplands, they are an unmatched source of early vegetation data.
In contrast to modern times, the surveys recorded extensive shrublands from 35% in Lake to over 50% in Napa East (see pg. 54. Grasslands constituted only a few percent of the landscape). At the time of the most recent vegetation maps, shrublands had declined by 15 – 75% from their 19th-century extent (depending on the study area). One of the conclusions from the historical records is that presence and extent of shrublands are closely linked to the frequency of fire. The only known factor which would account for the extensive shrublands recorded in the GLO surveys is the prevalence of cultural burning in the decades before the surveys.
Fire also accounts for another pattern seen in the early survey data the fact that Douglas fir were not particularly common. The ones that were present were mostly restricted to the ridgetops. Clint attributed this to the practice of burning from the bottom of a slope up, which tend to keep seedlings from becoming established on the downhill slope. The top of the ridge acted as a natural fire break where Douglas fir seedlings were able to establish themselves (see pg. 57 for more on this). Large, old Douglas firs still growing on the upper ridges of Pepperwood and elsewhere, may be a remnant of this pattern.
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Vegetation
Fire Prone
Napa
Pepperwood,
REGIONAL FIRE PATTERNS, 1870 -2020
Applies to: 2) Fire frequency and vegetation patterns; 4) Tipping points for catastrophic fire
As the maps show in the Selected Results section, there is a wide variation in fire histories both within each study area and among them. Variation in fire histories is shown below (Figure 21). The number (#) of fires refers to the average number of times a location within the study area was likely to burn, adjusted for the differing lengths of the fire records (which ranged from 118 years to 150 years). The Sonoma-Napa study area was divided into two portions along the ridgeline, which is also the border of the two counties. This was done to highlight the difference in fire histories between these adjacent areas and the similarity between Napa East and the Sonoma-Napa (Sonoma) portion.
LANDSCAPE VARIABLES
Several landscape variables were found to be associated with the fire history of each area:
Distance inland was the most significant factor tested (Fig. 22. Linear trendline)
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Sonoma
Sonoma-Napa Lake Napa East R² =
0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 DISTANCE INLAND (miles) AVERAGE
West
0.8625
# FIRES
0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 SONOMA
AVERAGE # FIRES STUDY AREA
Figure 22. Average # Fires vs. Distance Inland (adjusted to years of fire record)
WEST SONOMANAPA (Napa)
LAKE
NAPA EAST SONOMANAPA (Sonoma)
Figure 21. Average # Fires by Study Area (adjusted to years of fire record)
Slope aspect was the second most significant factor in explaining the variability in fire history (Figure 23), with the exception of Sonoma West. Even though Sonoma West’s aspect is just two degrees from directly south, this orientation is presumably cancelled out by its position near the coast, where conditions are generally wetter and cooler (including Sonoma West drops the trendline’s r-squared value to an insignificant 0.0072).
Removing Sonoma West from the mix and once again considering Sonoma-Napa as two distinct landscapes separated by a ridge, shows a strong correlation between slope aspect and fire history (linear trendline):
Slope steepness showed a negative relationship (r-squared = 0.68) with the number of fires. The steepest study area is Sonoma West, whose fire history appears to be strongly influenced by its proximity to the coast. Likewise, the Sonoma-Napa (Napa) subarea is also steep, but its burn history seems to be more determined by slope aspect than steepness. Because of these apparently overriding influences as well as the fact that the range in steepness among the study areas is small (between 15 and 24 degrees), we concluded that slope steepness is not a significant factor in the variability in fire history.
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Sonoma-Napa (Napa) Lake Napa East Sonoma -Napa (Sonoma) R² = 0.7507 0 20 40 60 80 100 120 140 160 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 DEVIATION FROM SOUTH AVERAGE # FIRES
Figure 23. Average # Fires vs. Slope Aspect Degrees deviation from South (0° on y axis) (Sonoma West not included see text)
FREQUENT and RARE BURN ZONES
The fire histories of the Frequent Burn Zones (FBZs) are more similar to each other than they are to their surrounding study areas (Figure 24). On average, slopes in the FBZs are slightly steeper (4°), higher elevation (+563’), and more south-facing (by 15°) than their associated study area. However, there are substantial variations and exceptions to these general characteristics and it was not possible to make definitive generalizations about their position within the landscape.
Frequent Burn Zones are where the most dynamic vegetation cycles take place. This is covered in the following section.
As might be expected, the characteristics of Rare Burn Zones (RBZs) are the reverse of the FBZs: on average being slightly gentler (6°), lower elevation (-238’), and more north-facing (by 32°), though there are exceptions to these general characteristics The average number of documented fires in the RBZs is zero, with the exception of the Napa East RBZ, where the average # of fires is 1.6 (adjusted for the length of the fire record).
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0.00 1.00 2.00 3.00 4.00 5.00 6.00
SONOMA WEST LAKE SONOMA-NAPA NAPA EAST
# FIRES STUDY AREA
Figure 24. Average # Fires in Frequent Burn Zones and Study Areas (adjusted to years of fire record)
Frequent Burn Zones Study Areas
REGIONAL VEGETATION PATTERNS: 1870 – 2020
Applies to: 1) Relationship of vegetation, fire, and people; 2) Fire frequency and vegetation patterns; 3) Minimizing emissions, maximizing sequestration; 4) Tipping points for catastrophic fire; 5) Fire as a stewardship tool
SHRUBLAND DECLINE
• One of the most significant trends over the 150-year study period was a steep decline in chaparral:
o Sonoma West: 27% 2%. (c. 1867 – 2013; early value +8%)
o Sonoma-Napa: 43% 13% (c. 1871 – c. 2015; early value +4%)
o Lake: 36% 24% (c. 1872 – 1993; early value +4%)
o Napa East: 54% 35% (c. 1863 – 2016; early value +9%)
o Average: 40% — 19% (c. 1870 – c. 2010)
• Shrublands were largely replaced by hardwood and conifer woodlands. In Napa, vineyards replaced some of the shrublands.
• Fire attenuates this trend for periods of time in some places (note shrubland extent in Figure 2 for Sonoma-Napa, nine years after the 1923 Nunns Fire) during the Fire-Shrub-Woodland-Fire Cycle described on page 63. Shrubs are often the dominant vegetation during the initial decades following fire.
WOODLAND EXPANSION
• There has been a general increase in woodland, with the average area with woodland growing from about 53% to 63% of each study area up until 1993, when the most recent vegetation map was made for Lake.
• In the wake of heavy logging between 1875 and 1915, Sonoma West actually increased its tree cover from 61% to 87% over the study period, and from 67% to 87% woodland just between the 1960s and 2013, representing a 30% increase in area (Fig. 25)
• Sonoma-Napa likewise saw an increase from 52% to 72% (a 40% increase in area) over the 150-year study period (Fig. 26)
• Like Sonoma West, the Lake study area saw impacts from logging. While some occurred in the late 19th century, the most significant harvest was in the 1940s. Between 1950 and 1993 (the most recent record) Lake’s woodland cover increased from 39% to 68% (a 74% increase in area), returning it to a forest extent comparable to what existed before timber harvest, though the proportion of hardwood in 1993 is probably substantially higher than it was in the 19th century (Fig 27).
• No evidence was found for commercial logging in Sonoma-Napa or Napa East.
• Napa East may be an exception, showing 7% less woodland cover than in 1932, though possibly a slight increase since the 19th century, depending how the early survey data is interpreted (Fig.28). As the most fire-prone and driest study area, with major wildfires in 1965, 1981 and 2017, conditions in Napa East may make it difficult for extensive woodland to become established.
(Splines in Figures 25-28 were drawn with the “Smoothing” function in Excel, using a Bezier Smoothing Algorithm. Points shown are the actual data points.)
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and Sonoma
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Vegetation Trends and Cycles in Fire Prone Landscapes of Lake, Napa East
Counties
Figure 25. Sonoma West, % Woodland Cover 1867-2013 SONOMA-WEST Conifer SONOMA WEST Hardwood FOREST TOTAL
0 10 20 30 40 50 60 70 80 1860 1880 1900 1920 1940 1960 1980 2000 2020 2040 WOODLAND as % of STUDY AREA YEAR
R² = 0.9997
Figure 26. Sonoma-Napa, % Woodland Cover 1871-2015
Hardwood Conifer Forest Total Poly. (Forest Total)
Vegetation Trends and Cycles in Fire Prone Landscapes of Lake, Napa East and Sonoma Counties Pepperwood, Baseline Consulting, Tukman Geospatial, Thorne Environmental Landscape Analysis 57 0 5 10 15 20 25 30 35 40 45 50 1840 1860 1880 1900 1920 1940 1960 1980 2000 2020 2040 WOODLAND as % of STUDY AREA YEAR
NAPA EAST Conifer NAPA EAST Hardwood FOREST TOTAL 0 10 20 30 40 50 60 70 80 90 1860 1880 1900 1920 1940 1960 1980 2000 2020 WOODLAND as % of STUDY AREA YEAR
Figure 28. Napa East, % Woodland Cover 1863-2016
Figure 27. Lake, % Woodland Cover--1872-1993
LAKE Conifer LAKE Hardwood FOREST total
Douglas Fir Expansion
One of the more notable characteristics recorded by the 19th-century surveys, when compared with the landscape of the last few decades, is the nominal presence of Douglas fir. While they seem to have been avoided as bearing trees, perhaps due to concerns they would be cut for lumber, they are also relatively uncommon in the line descriptions, which were free of such bias. Surveyors were instructed to record vegetation in these descriptions in ‘order of abundance’ and there is no known reason to believe Douglas fir would not have been recorded if they were, in fact, there.
Cover
Clint McKay (Dry Creek Pomo/Wappo/Wintun), as a keeper of Traditional Ecological Knowledge or TEK for much of project area, stated that in pre-white settlement times Douglas fir was mostly found high up, “on the peaks and ridges.” He attributed this to the practice of burning slopes from the bottom up, which restricted the downhill expansion of Doug fir. He also mentioned that: “Pepperwood’s ridgetops were used as a traffic corridor for people and animals” whose open character was maintained by cultural burning Such a burn pattern would have also tended to exclude Douglas fir from some of the highest elevations. Given that by the late 19th-century, Doug fir’s extent was no longer being limited by cultural burning, it would have begun expanding mostly downslope But there would also have been some room to expand upslope
With the exception of Napa East, all study areas showed Douglas fir expanding in area since the early or mid-20th century (Fig. 29). While not symbolized separately in the Results section, Douglas fir is a major component of the Conifer forest shown in these maps (see Table A-4 on page A-10 in the Appendix for an overview of this shift) See vegetation tables in the Appendix for the percent of Doug fir cover). Coverage in the late 19th-century appears to have been on the order of 1-4% in these areas. Coverage in Napa East appears to have been close to 0% until after 1932. This was corroborated by a multi-generational resident of Napa East (Manfree 2023).
All areas except Napa East showed Douglas fir expanding its elevational range by 1800’ (Sonoma West) to 3500’ (Lake). The expansion in both cases was primarily downhill. Graphs and detailed results for each area are covered below Over the study period, slope aspects on which Douglas fir were recorded expanded from one or two directions to all eight cardinal and intermediate directions.
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0 5 10 15 20 25 30 35 40 1920 1940 1960 1980 2000 2020 DOUGLAS FIR as % of STUDY AREA YEAR
Sonoma-Napa
Figure 29. Change in Douglas Fir
1928 - 2013
Sonoma West Lake
Sonoma-Napa
On the east (Napa) side of the study area, Douglas Fir expanded its elevational range from about 1500 feet in the late 19th century to about 2200 feet in 2013. On the West (Sonoma) side, the expansion was more rapid, increasing from 650’ in the 19th century to over 2000’ in 2013, for an average of 9.6’ annually (Fig. 30).
EAST, Upper & Lower limits
STUDY AREA LIMIT
WEST AV
EAST AV
WEST, Upper & Lower limits
Throughout the Sonoma-Napa study area, downhill expansion of Douglas fir has been about twice as fast downhill as uphill about 3.5’ vs. 1.7’ annually
The speed of downhill expansion appears to have been fastest in the earlier part of the study period, 1871 –1932, when the rate is estimated at 5.9’/year. The speed slowed in the mid-20th century, 1932-1993, to 2.2’/year, and again to 0.8’ year between 1993 and 2013.
The speed of downhill Doug fir expansion appears to have been substantially faster on the west side of the study area (Sonoma County) than on the east side (Napa County).
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0 500 1000 1500 2000 2500 3000 1860 1880 1900 1920 1940 1960 1980 2000 2020 2040 ELEVATION (feet) YEAR
Figure 30. Douglas Fir Elevation Shift Sonoma-Napa East--1870 - 2013
Sonoma West
Like the Sonoma-Napa and Lake Study Areas, Sonoma West also saw Douglas fir expanding downhill over the study period. Unlike those areas, up through the 1960s there was no uphill expansion, but a downhill shift of the upper edge of Doug fir woodland. This situation might be attributed to the impact of logging up through that time, as well as the loss of trees in wildfires.
Following the 1960s, Douglas fir expanded rapidly uphill, and was recorded on the study area’s uppermost ridges by 1993. The rate of uphill expansion appears to have been several times that of the other study areas. By 2000, Douglas fir had expanded to the highest and lowest elevations in the study area
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0 500 1000 1500 2000 2500 1850 1900 1950 2000 2050 ELEVATION (feet) YEAR
MAXIMUM MINIMUM AVERAGE STUDY AREA LIMIT
Figure 31. Douglas Fir Elevation Shift Sonoma West--1867-2013
Like the Sonoma-Napa and Sonoma-West Study Areas, the Lake Study Area also saw Douglas fir expanding downhill over the study period. In this case, uphill expansion was only a little slower than downhill. Douglas fir reached about 90% of its current elevational range by 1928.
Doug fir’s apparent movement downhill since 1950 has been very slow, at less than one foot per year (0.8’). This is similar to that seen in the Sonoma-Napa Study Area, where recent expansion has also been under one foot per year (0.7’ on the east side, 0.9 on the west).
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Lake
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 1860 1880 1900 1920 1940 1960 1980 2000 ELEVATION (feet) YEAR
MAXIMUM MINIMUM AVERAGE STUDY AREA LIMIT
Figure 32. Douglas Fir Elevation Shift, Lake 1872-1993
California Bay Expansion
• In the Napa East, Sonoma-Napa and Sonoma West areas, California Bay were present but not abundant in the 19th century. They do not appear at all in the record for Lake. Early surveys only rarely recorded Bays either as bearing trees or in Line descriptions, which recorded vegetation in ‘order of abundance.’ This absence strongly suggests they were not abundant at that time (see Vegetation tables in the Appendices for each Study Area).
• Vegetation data suggests an increase in California Bay over the study period In Sonoma West, Bay quadrupled (4X) in area between the 1960s and 2010s. The increase in other study areas is less conclusive due to Bay being lumped into the ‘Montane Hardwood’ category in 20th century surveys.
BLACK OAK DECLINE
• Black oaks are known to be in decline over much of California (Hammett et. al. 2017; Long et. al 2017). This decline has been tied to fire suppression in the 20th century and the cessation of cultural burning by Indigenous peoples.
• At the time the 19th-century surveys were made, Indigenous tending of Black oaks had only recently come to a close or been severely reduced. Not surprisingly, Black oaks are a significant presence in the early surveys, representing about 15% of the all the 19th-century bearing trees included in this study (148/986).
• Black oak presence ranged from 8% of bearing trees in Lake and Sonoma West, to 18% in Napa East, to 34% for Sonoma-Napa (it’s unknown if surveyors preferred this species over other oaks). In later mapping, Black oaks were often lumped into ‘Montane Hardwood,’ ‘Montane Hardwood-Conifer,’ and ‘Mixed Oak’ categories (Anderson 1993, McDonald 1993, MCV 2009), obscuring their subsequent history.
• Black oak’s varying distribution may reflect both environmental factors and the distribution of Indigenous peoples. As Black oaks are a ‘cultural keystone species’ that were (and still are) tended accordingly, it would be expected to find more Black oaks where high concentrations of Indigenous people as are believed to have been living in Napa and Sonoma Valleys before 19th-century settlement (compared to Sonoma West and Lake). The relationship may well have gone both ways, with people choosing to live near Black oak woodlands and Black oaks prospering under Indigenous stewardship.
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VEGETATION RESPONSE TO FIRE
Fire-Shrub-Woodland-Fire Cycle
The most dynamic vegetation changes occur in the Frequent Burn Zones (FBZs) of Sonoma-Napa, Sonoma West and Lake study areas. Over a period of 40 to 60 years, vegetation swings back and forth between being primarily shrubland to primarily woodland, with wildfire acting as the ‘reset button’ on the successional clock. Vegetation history and fire history are especially closely linked in these areas.
Immediately after a fire, shrubs, particularly chamise, quickly become the dominant lifeform, covering from half to three-quarters of these FBZs. As years pass without fire, woodlands begin replace the shrublands. By 2013, forty-nine years after the 1964 fire, woodlands covered 78% of the Sonoma-Napa FBZ, having replaced shrublands at an annual rate of 1.30%. After the 2017 Nunns Fire, the area again reverted to shrubland (Dawson 2018), thus presumably beginning another cycle.
Vegetation in the Sonoma West FBZ shows a similar response, being 47% shrub at six years post fire, declining to 7% shrub 54 years after a fire. Woodlands increased during this time from 48% to 90%, for a replacement rate of 0.88%/year The Lake FBZ shows a similar pattern: at 6 years post fire, 50% was designated shrub or ‘barren’ and 41% woodland. Forty-three years later, shrublands were reduced to 21%, while woodlands covered 77% of the landscape—giving an annual replacement rate of shrubland by woodland of 0.84%.
Going one step further, we clipped out the post-fire shrublands in these FBZs that is areas with 100% shrub in the first decade after a fire. Tracking change revealed an even more rapid succession, with woodland replacing shrublands at the rate of 3.25%/year (Sonoma-Napa), 2.4 %/year (Sonoma West), and 1.26%/year (Lake). The rate of replacement declines with time, going down to only 0.5% in Sonoma-Napa and Sonoma West (Lake lacks the data to track this metric).
This agrees with the findings of many researchers that fire has many ecosystem benefits, including promoting the creation of biomass (productivity) by replenishing soil fertility and reducing competition (California Air Resources Board 2021). Chamise and Manzanita have been shown to grow most quickly in the first 8-10 years after fire, with growth tapering off after that (Sampson 1944). Clint McKay stated that his people would burn chaparral when it grew too high for the deer to browse easily, which may have more or less coincided with early post-fire period.
The speed of this transition also points out the potential for error when using vegetation maps more than a few years old for analysis. Within a ten-year time frame, shrublands declined by up to 1/3 while woodlands increased by a similar amount.
The fire vegetation cycle in the Napa East FBZ is nearly non-existent compared to the other three areas, remaining more or less in a steady state between 12 and 35 years post fire. Clipping out just the 1993 shrublands (12 years post fire) reveals weak evidence for the fire-shrub-woodland cycle, with woodland replacing shrub at an annual rate of just 0.13%.
An extensive literature search was unable to locate other studies or documentation of the fire-shrub-woodlandfire cycle.
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While the general pattern of woodlands replacing shrublands holds true in all four study areas (if weakly in Napa East), the patterns vary considerably:
Sonoma-Napa: Hardwoods (oaks, madrone and bay, in order of abundance) replace shrublands about twice as fast as conifers. Likewise, the rate of replacement by knobcone pine was more rapid than for Douglas fir, though this could have been enhanced by active seeding after the 1964 fire (Fig. 33).
Sonoma-West: Similar to Sonoma-Napa, Hardwoods initially replaced shrublands more rapidly than conifers in the first few decades after a fire. However, by 54 years post fire, conifers covered twice as much area as hardwoods, with Douglas fir and redwoods taking up about equal portions (Fig. 34).
Lake: By 49 years post-disturbance (possibly a combination of fire and timber harvest) conifers had replaced shrublands at more than twice the rate of hardwoods (Lake lacks any earlier data). Forest types, in order of abundance, are Klamath Mixed Conifer, Closed-Cone Pine Cypress and Douglas fir. It is unknown if any post fire or post harvest planting was done (Fig. 35).
Napa East: Woodlands replaced shrublands very slowly between 1993 and 2016 (12 to 35 years post fire). These were all hardwood species no conifers were recorded (No figure. See Appendix).
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0 10 20 30 40 50 60 70 80 90 0 10 20 30 40 50 60 LIFEFORM COVER % of STUDY AREA YEARS POST-FIRE
Figure 33. Sonoma-Napa FBZ Lifeform Transitions 9-49 Years Post Fire
Sonoma-Napa Woodland Total Sonoma-Napa Shrub
Sonoma-Napa Conifer Sonoma-Napa Hardwood
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Vegetation
Figure 34. Sonoma West FBZ Lifeform Transitions
6-54
Years Post Fire
0 10 20 30 40 50 60 70 80 90 6 49 % of STUDY AREA YEARS POST FIRE
Sonoma West Woodland Total Sonoma West Shrub Sonoma West Conifer Sonoma West Hardwood
Figure 35. Lake Lifeform FBZ Transitions
6-49
Years Post Fire Shrub/Barren/Herb Conifer Hardwood Forest Total
VEGETATION RESPONSE TO TIMBER HARVEST
The 1950 Soil-Veg map for the Lake study area includes 9655 acres designated as ‘Barren’ for vegetation type. Two decades earlier, 75% of this area had been forested with conifers (50%) and hardwoods (25%). It is assumed that timber was harvested here in the 1940s as part of a large, documented commercial logging operation (California Department of Forestry). By 1993, 59% of this ‘Barren’ area had returned to woodland, with 35% Conifer and 24% Hardwoods. Ponderosa pine was the most abundant conifer in 1928, while Doug fir was the least abundant (4%). By 1993 it was almost the reverse: Doug fir being the most abundant (14%) and Ponderosa the second least common (6%). It is unknown whether replanting was done after the timber harvest which could account for some of the change.
The annual rate of replacement of ‘barrenland’ with woodland in the Lake study area between 1950 and 1993 was 1.37%, very similar to the rate of shrub-to-woodland replacement in the FBZs, which ranged from about 0.8% to 1.3% annually.
In 1965, fifty years after the end of intensive logging in the Sonoma West study area, the former harvest area (Weber 1926) was 71% forest. This is close to the extent of forest around 1870, before intensive logging. But what had been predominately Redwood forest before harvest (c. 1870) was now Tan oak, Coast Live oak and Madrone woodlands, comprising 61% of the harvest area. By the time this woodland was mapped again, in 1993, it had returned to being predominately conifer (54%), dominated by Redwoods. The hardwoods had shrunk to one-third of their extent less than three decades earlier (from 61% to 20%). Some of this decline can probably be attributed to hardwoods being overtopped by conifers and thus were no longer mapped as the most abundant forest tree. Tan oak in particular shows a steep decline as a forest type, going from 21% in 1965 to 3% in 2013 (or a little higher if you include the 1% Doug fir-Tan Oak mixed woodland).
It should be noted that between 1965 and 2013, the Timber Harvest Zone shows an accelerating decline in the human footprint (22% down to 9% in less than 50 years) with a corresponding increase in the forested area. Interestingly, the combined acreage for ‘Woodland’ and ‘Human’ footprint is remarkably constant (growing only about 100 acres over a half century). The most obvious explanation is to assume that as the trees grew, their canopies hid more and more of the human infrastructure from the mappers’ view directly above (e.g. aerial or satellite imagery).
Second-growth redwoods at one former homestead in the Calabazas Creek Preserve (Sonoma-Napa) indicate timber harvesting by homesteaders in the 19th-th century, probably for their own use and was non-commercial. Salvage logging is known to have occurred at the Preserve after the 1964 fire. As this was concomitant with the fire, the burn and harvest are considered a single disturbance for the purposes of this study. This could skew the analysis of vegetation change in the FBZ, though as shown above, there seems to be little difference in recovery rates between fire and harvest disturbance.
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VEGETATION CHANGE in the ABSENCE OF FIRE: RARE BURN ZONES (RBZs)
Overall, vegetation change in the RBZs occurs at a fraction of the rate seen in the Frequent Burn Zones.
Sonoma-Napa: Given the large proportion (about 2/3) of chamise and young (small diameter) oaks recorded here around 1867, we can infer that this area experienced Indigenous cultural burning in the early 19th century. By 1932, the RBZ was mapped at 56% woodland, which was all oak except for 1% Douglas fir. Sixty years later, in 1993, this area was 72% woodland, one-quarter of which was conifer (mostly Douglas fir).
The annual woodland expansion rate was 0.27%, about half that seen in the FBZ at 30 years+ post fire. Douglas fir was responsible for this increase. The hardwood proportion declined slightly over the 20th century. Between 1993 and 2016, woodland extent continued to increase at roughly the same rate (0.3%/year), adding 7% during this time period. Hardwood forest made up the bulk of the increase (6% vs.1% for conifers).
Sonoma West: As the Rare Burn in Sonoma West also represents the timber harvest area, this RBZ was not assessed as an RBZ.
Lake: The RBZ for Lake is also difficult to interpret due to timber harvest overlapping with this zone. Taking the 43 years of record free from documented disturbance (1950 – 1993), we see the woodland extent growing from 68% to 89%, close to the estimated pre-harvest value in the 19th century. This gives an annual woodland expansion rate of 0.49%, about the same as the later post-fire period in the FBZs. The higher rate here than in Sonoma-Napa (0.27%) may represent a shorter time since disturbance in Lake Conifers were responsible for the majority of this increase in the Lake RBZ.
Napa East: The Napa East Rare Burn Zone was the only RBZ with documented fires, which occurred in 1913 and 1981. In 1932, 19 years after this fire, 31% of this FBZ was recorded as woodland. There was virtually the same woodland extent in 1993 (30%). The 14% decrease in shrublands was primarily taken up by an increased human footprint. The same trajectory happened again between 1993 and 2016, with woodland unchanged and shrublands being converted to agriculture.
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GRASSLAND
• Grassland (Herbaceous Lifeform) was not a large component of vegetation in most places and times included in this study, usually covering well below ten percent of the landscape.
• Estimates for grassland cover in the 19th century are all in the low single digits (considering the later record, lumped ‘herb or shrub’ designations applied to the old survey records are probably shrub).
• In Sonoma West, Lake, and Napa East grassland cover peaked in the aftermath of timber harvest and fire, reaching 8%, 11% and 9% respectively, before declining Grassland in the Sonoma-Napa study area appears to be very slowly increasing, from 2% to 5% in 80+ years.
• Grassland appears to be the most stable lifeform on all four landscapes. The dynamic cycle between shrubs and woodland, driven by fire, does not appear to be at work in a significant way between grasslands and shrubs or grasslands and woodland.
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Vegetation
EMISSIONS and SEQUESTRATION
Applies to: 1) Relationship of vegetation, fire, and people; 2) Fire frequency and vegetation patterns; 3) Minimizing emissions, maximizing sequestration; 5) Fire as a stewardship tool
We intended to develop recommendations for a management approach that would maximize carbon sequestration, minimize emissions, and reduce the wildfire hazard to communities. After putting substantial thought and effort into background research attempting to quantify emission and sequestration values under different fire regimes, it became clear that so many questions remained that any conclusions drawn would be little more than speculative.
Ottmar (2013) acknowledges that a lack of data restricts “our ability to ascertain the true contribution of wildland fire to GHG and aerosol emissions.” Furthermore, information is limited on the “production and sequestration of BC [black carbon] into the soils following wildfire that may serve as a partial offset of GHG and aerosols.” We do know that wildfires generally consume two to four times as much fuel per acre as prescribed fires, resulting in more greenhouse gas emissions (Berger et. al. 2018; Ottmar 2013). This is because wildfire fuels are usually drier, crown fires contribute additional biomass, and wind speed is higher. All these factors increase fuel consumption and thus emissions as compared to prescribed burns.
Over long time periods (e.g. multiple decades) in unmanaged fire regimes, wildfire carbon emissions “are balanced by carbon capture from forest regrowth…unless a lasting shift in plant community type occurs and/or fire return intervals change” (Sommers et. al. 2014). To the extent that our study areas could be considered to have ‘unmanaged fire regimes” it is possible that such a balance exists in certain places, though it is impossible to know.
Estimating carbon capture or sequestration is equally, or even more difficult than estimating emissions. Research is needed to understand the charred residue and ash remaining after fire, how much of its carbon becomes sequestered, and how much black carbon, organic carbon and brown carbon end up in the atmosphere (Ottmar 2013). Likewise, the fate of underground carbon in roots killed by fire in not well known.
One suggestion to address these questions is to develop “enhanced monitoring programs that improve our understanding of long-term, landscape-scale ecological responses to fire, provide data to evaluate effectiveness of management activities, and identify key emerging ecological dynamics” (Sommers et. al 2014). One consistent finding in this study was that the most fire-prone places, the FBZs, tend to have the most dynamic cycles of vegetation change. The speed of transitions there, from shrubland to woodland in a few decades suggests that these places may be where the highest sequestration rates in the landscape are occurring. The transition rates in the FBZs peak in the first two to three decades after a fire and then slow down by as much as 85% (for example, from 3.25% to 0.5% annually in the Sonoma West FBZ). Likewise, chamise and manzanita are most vigorous in the early years following a fire (Sampson 1944) and thus presumably sequestering more carbon during that period.
A global study of above and below ground carbon stocks (Ma et. al 2021) found that shrublands sequestered nearly half their carbon in underground biomass (47%). In contrast, forests only sequester 22% below ground. This suggests that in some cases, shrublands may be better carbon sinks than forests, assuming that below ground carbon is better protected from wildfire.
One of the goals of Indigenous stewardship, including cultural burning, according to Clint McKay, is to benefit all the living things on the land. This implies a thriving landscape and, in scientific terms, has high productivity. Net primary productivity can be used “to identify ecosystem carbon sources/sinks, playing an important role in
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carbon balance” (Liao 2022). This suggests that the vegetation patterns created by Indigenous stewardship, practiced with the intent of benefitting all living things, may also have maximized carbon sequestration. In addition, as mentioned above. Intentional burning (e.g. cultural or prescriptive) produces only a fraction of the emissions caused by unintentional burning in a wildfire.
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ADDENDUM
CATASTROPHIC FIRE, WIND vs. FUEL-DRIVEN WILDFIRES, A FIRE EXPOSURE METRIC, and a POSSIBLE TIPPING POINT
Applies to: 1) Relationship of vegetation, fire, and people; 2) Fire frequency and vegetation patterns;
3) Minimizing 4) Tipping points for catastrophic fire; 5) Fire as a stewardship tool
Recent large wildfires in Sonoma, Napa, and Lake Counties include the Valley Fire in 2015; the Nunns, Tubbs and Atlas Fires in 2017; the Kincade Fire in 2019; and the Walbridge and Glass Fires in 2020. Together they burned about 370,000 acres, or nearly 600 square miles. For people who lost their homes, the life of a loved one or even their own, these were obviously catastrophic events. Preparing for and perhaps preventing such huge fires is a key question as climate change steadily moves the world into new and unfamiliar territory. There is concern that “current fire prediction systems…may not be capable of modeling fire behavior in future fire environments” (Sommers et. al. 2014).
Are these recent fires truly unprecedented? Are we already in a “future fire environment? The answers to these questions may be both ‘yes’ and ‘no.’ According the ‘2017 Sonoma Complex Fires’ story map website (Sonoma County 2019): “The 2017 fires were extreme, but not unprecedented” with “similar firestorms in 1964, 1923, and 1870.” But considering just the Nunns Fires of 1923, 1964 and 2017 shows that, although weather conditions were similar, the 2017 fire was close to twice as large as any previous fire (Fig. 36). On the other hand, the 2017 Tubbs fire (outside our study areas) does fit within the historical pattern and was quite a bit smaller than the 1964 Hanley fire (about 36,000 acres vs. 55,000 in 1964).
Looking at the ‘Fire Size’ graphs (as measured within the study areas Figures 36-39), shows the Valley and Nunns fires truly were unprecedented. The Walbridge fire was slightly larger than any before it in Sonoma West. The 2017 Atlas fire was slightly smaller than the 1981 Atlas fire.
For this discussion, ‘catastrophic fire’ is defined as one of the ten labeled fires in Figures 36-40, each of which covered >35% of their respective study area (the 1964 Nunns Fire was smaller but is still within living memory and included for comparison). These wildfires are clearly an order of magnitude larger than the others. Within the human community, these fires are well remembered for many decades afterwards.
What factors are behind these catastrophic fires? Is there a tipping point that might account for their unusual size? A tipping point would exist if a small change in conditions led to a dramatic change in outcome. This could be a slight increase in wind speed or temperature, a slight decrease in humidity, or some other seemingly minor shift in conditions that turns an average fire into a catastrophic one.
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0 10 20 30 40 50 60 70 80 1850 1900 1950 2000 2050 % OF STUDY AREA YEAR
Figure 36. Sonoma-Napa Fire Extent 1870 - 2020 (as % of Study Area) NUNNS 2017
NUNNS 1923
NUNNS 1964
High winds have been a common element in most, if not all these catastrophic fires. Wind speed data is not available for most of these events. But newspaper descriptions ‘howling winds,’ ‘hurricane force,’ and ‘difficult to stand’ suggest conditions similar to those recorded in 2017. The 2017 ‘Wine Country Fires,’ which include the Tubbs and Nunns fires, have been used as examples of ‘winddriven’ versus ‘fuel-driven’ wildfires (Keene and Syphard 2020). Likewise, the ‘2017 Sonoma Complex Fires’ webpages (Sonoma County 2019) link these fires to Sonoma County’s ‘fire-prone wind corridors.’
Wildfire forecasters have identified a trio of tipping points known as the “30-30-30 Crossover Rule.” As described by Steffens (2016), if a wildfire starts while the temperature is 30C or above, the relative humidity is 30% or less and the wind speed is 30km/h or stronger, it will exhibit extreme fire behavior and be difficult to control until weather conditions change.
Using data from Geyser Peak and Sonoma Mountain, we evaluated wind conditions during the 2017 Nunns and Tubbs fires a portion of Nunns and all of Tubbs were outside our study areas but provide a useful comparison in a more regional context. We assumed a critical threshold of 18.6 mph windspeed for a ‘wind-driven’ fire. Using these criteria, the conditions for a wind-driven fire lasted from the evening of October 8 through noon on October 9. Both the Tubbs and Nunns fires started around midnight. Using MODIS data (Fig. 40), which shows heat data at 6hour intervals, we designated areas that burned before 12:30 pm on October 9 as ‘wind-driven’ and those that burned afterwards as ‘fuel-driven.’
Under the “30-30-30” rule, the combination of humidity, temperature and wind creates a
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0 10 20 30 40 50 60 1850 1900 1950 2000 2050 % of STUDY AREA YEAR
0 10 20 30 40 50 1850 1900 1950 2000 2050 % OF STUDY AREA YEAR
Figure 38. Lake Fire Extent, 1874 -2020 (as % of Study Area)
WALBRIDGE
1917 VALLEY 2015 0 10 20 30 40 50 60 70 80 90 1870 1920 1970 2020 % of STUDY AREA YEAR
Figure 37. Sonoma West Fire Extent 1916 – 2020 (as % of Study Area)
2020 FIRE
OF
ATLAS 2017 ATLAS 1981 1913 FIRE 1965 FIRE
Figure 39. Napa East Fire Extent, 1879 - 2020 (as % of Study Area)
tipping point for extreme fire behavior. Since all three are required, removing windspeed from the mix would mean that humidity and temperature do not represent tipping points either individually or in combination.
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Figure 40. Windspeed and Fire Spread, Tubbs and Nunns Fires. October 2017.
Taking both fires together, shows 41% of the area burned during the wind-driven phase and 59% burned during the fuel-driven phase. Separating out the two fires however, shows two very different patterns, visible on the map (Fig. 40) and quantified in Table 10 below:
To some degree, both fires were hybrids of wind-driven and fuel-driven. But it makes sense to designate Tubbs as primarily wind-driven and to consider wind speed a possible tipping point that explains the size of that conflagration. It also seems reasonable to designate the Nunns Fire as primarily fuel-driven and thus wind would not be a tipping point responsible for its size.
As for the question of whether the winds driving these fires are becoming more frequent or intense, Williams (et.al. 2019) found that for the state as a whole, “The character of offshore wind events did not change since records began in the mid-1900s.” In relation to wildfire, in southern California at least, “there is little evidence that the increase in the number of catastrophic fires is the result of increased intensity of … wind events.” (Keene Syphard 2020). This agrees with the apparent similarity in wind conditions during historical and recent catastrophic fires documented in this study. As an example, in Sonoma-Napa, high winds were reported during the catastrophic fires of 1923, 1964 and 2017. Yet the acreage burned spanned a wide range, from roughly 10,000 in 1964 to 20,000 in 1923 to 55,000 in 2017.
While wind plays an important role in these fires, it appears that wind alone does not represent a tipping point driving catastrophic fires, at least in these locations. However, it could be considered a tipping point for ignition given the number of fires started by trees falling on electrical lines and equipment during high wind events.
Given that the Nunns fire began as a wind-driven event but soon became a fuel-driven fire, what might explain its unprecedented size? One possibility is the amount or configuration of the fuel itself. In “A simple metric of landscape fire exposure,” (Beverly et.al. 2020) describes how “Proximity of landcover elements to each other will enable or constrain fire spread” and how “a metric of landscape fire exposure” can be created, “based solely on a grid cell’s proximity to nearby hazardous fuel capable of transmitting fire to its location.” To evaluate the accuracy of this metric, they looked at whether “burned areas occurred preferentially in locations with high exposure.”
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Wind-driven Phase Fuel-driven Phase TOTAL Nunns Fire 23% 12,586 acres 77% 42,260 acres 100% 54,846 Tubbs Fire 68% 24,740 acres 32% 11,748 acres 100% 36,488 TOTAL 41% 37,326 acres 59% 54,008 100% 91,334 acres
Table 10. Wind-driven vs. Fuel-driven Phases. ‘Sonoma Complex Fires’ October 2017
A FIRE EXPOSURE METRIC
The spatial arrangement of vegetation is considered a bottom-up (endogenous) control on fire propagation, while climate and weather are top-down (exogenous). The “fire exposure metric” developed by Beverly is a “numeric rating of the potential for fire transmission to a location given surrounding fuel composition and configuration, irrespective of weather or other fire controls.” Within their study area, which covered 100 million acres in Canada, all “wood fuel types” were “classified as hazardous fuels capable of transmitting fire within a 500m range.” It was assumed that “all hazardous fuel cells” contributed “equally to exposure irrespective of fuel type or configuration within the circular fuel neighborhood.” Exposure was estimated for a single 500m distance range.
The fire exposure metric represents not an estimated probability of occurrence, but rather “a physical quantity whose value at any point in time and space can be measured.” Applying this metric to their study area, Beverly reported ”the results showed average exposure in burned areas was 66.2%, while in unburned areas it was only 49.7%. In other words, a 16.5% change in exposure determined whether a location did or didn’t burn. A minor change in conditions led to a dramatic change in outcome- a tipping point.
Beverly acknowledges that the fire exposure metric may seem overly simplistic, but cites Perera, who noted “the lack of consensus among ecologists about the desirability of simple parsimonious models vs. complex simulations of disturbance processes. The question of appropriate model complexity has been largely ignored by wildland fire modelers” (Perera et. al. 2015). Beverly observes that “simulated burn probability maps,” created with modeling, “have exhibited poor alignment with subsequent observed wildfires.” Yet Beverly’s research found that “simple, deterministic, univariate metric of fire exposure aligned well with real-world fires observed in our study area.” Their approach “represents a departure from computationally complex and data-intensive approaches for characterizing fire spread potential across landscapes.”
Beverly’s results are closely aligned with the predictions of percolation theory. Percolation theory offers a simple approach applicable to many kinds of complex systems, including wildfire. Even the most basic model a grid with empty or occupied cells (trees) shows a tipping point occurs when about 60% of the cells are occupied. A few percent below this, say 57%, results in burns averaging less than 10% of the grid. Raising it slightly to 62%, results in more than 80% of the area being burned (Dawson 2022; Stessel 2016). This illustrates the effect of crossing a tipping point A five percent increase in occupied cells (trees) resulted in an 8x increase in the burned area. Sixty percent is the same value mentioned by Beverly. Caldarelli states that percolation “can help to describe the fire evolution. By mapping fire dynamics into the percolation models, the strategies for fire control might be improved.” (Caldarelli et. al. 2001. Note that some researchers are cautious about applying percolation theory to wildfires see Hunt 2007).
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Fire Prone
Napa
A POSSIBLE TIPPING POINT
The positions of the catastrophic fires in the graphs in Figures 36-39 are well above and separated from those of any other fires. The large difference in outcomes suggests that a tipping point was exceeded which drove these fires to their unusual, and in many cases, unprecedented sizes. In this study, measurements of percent woodland cover appear to work as a rough equivalent to Beverly’s ‘fire exposure metric.’
Using the established rates of woodland expansion for each study area, the percent cover was estimated for fires going back to the 1930s (before that time the data is too sparse for making estimates). Plotting percent woodland cover, estimated for the year of each fire, against fire size shows a clear relationship between fire size and woodland cover, with a tipping point between 60 and 75% (trend lines are exponential).
Because of the century-long gap in vegetation data for Sonoma West, as well as a timber harvest that covered half the study area, only the Frequent Burn Zone there was used for analysis. Given that vegetation patterns for Napa East seem to be of a different nature than elsewhere, it is not surprising that the results there do not indicate a tipping point driven by woodland cover. The prevalence of grassland in Napa East in 1993 and 2016 (9% and 8% respectively) following the 1981 Atlas fire hints at a possible type conversion as has been studied in southern California following fire. The persistence or expansion of grassland in Napa East following the 2017 Atlas fire remains to be seen. But if observed, would suggest fire-vegetation history more akin to southern California than to the other three study areas.
To further test whether ‘percent woodland cover’ might serve as a univariate fire exposure metric, this value was calculated for the footprints of other recent catastrophic fires in Sonoma County using the 2013 Veg Map and also from the 1993 WHR map. Using the established rates of woodland expansion, the values were estimated for the year of each fire (Table 11).
Overall, the results support the possibility that woodland cover is a tipping point for catastrophic fire. In 1993, the woodland cover inside 2/3 of the catastrophic fire perimeters was <62%. By their ignition dates, between 2015 and 2020, all except Kincade were > 66% woodland cover. This is well above both the theoretical percolation threshold and that observed by Beverly
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R² = 0.7794 0 20 40 60 80 100 0 20 40 60 80 100 FIRE SIZE (% of Area) % WOODLAND COVER (estimated)
NUNNS 2017 R² = 0.6266 0 10 20 30 40 50 60 0 20 40 60 80 100 FIRE SIZE (% of Area) % WOODLAND (estimated)
Figure 41. Woodland Cover vs. Fire Size (> 500 acres) Sonoma-Napa, 1936 - 2017
VALLEY 2015
Figure 42. Woodland Cover vs. Fire Size (>2000 acres) Lake, 1939-2015
(2021) in the empirical data (60% in both cases). Other factors may explain the size of the Kincade fire, which was just below this threshold.
As for the Tubbs fire, it’s possible that woodland cover above the threshold contributed to its rapid spread during the wind-driven phase. It also may account for the 10,000 acres burned during the fueldriven phase, which would still be considered a large wildfire for Sonoma County.
The areas within the perimeters of the Walbridge and Valley fires both had > 70% woodland cover in 1993. The random nature of ignitions may account for the firefree period preceding these fires. Averaging the remaining perimeters gives a value well below 60% woodland cover in 1993.
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.
Ignition
1993 GLASS, 2020 76% 62% WALBRIDGE, 2020 86% 72% KINCADE, 2019 58% 45% NUNNS, 2017 69% 57% TUBBS, 2017 66% 54% VALLEY, 2015 88% 79% AVERAGE 74% 62% EXCLUDING WALBRIDGE & VALLEY 67% 54.5% R² = 0.9231 0 10 20 30 40 50 60 70 80 0 20 40 60 80 100 FIRE SIZE (as % of area) % WOODLAND (estimated)
Table 11. Woodland Cover within 2015 – 2020 Fire Perimeters At
(estimated)
(>
R² = 0.8756 0 10 20 30 40 50 60 70 80 90 100 110 0 20 40 60 80 100 FIRE SIZE (% of area) % WOODLAND (estimated)
Figure 43. Woodland Cover vs. Fire Size
500 acres) Napa East
2017 WALBRIDGE 2020 1959 FIRE
Figure 42. Woodland Cover vs. Fire Size Sonoma West FBZ: 1929-2020
ATLAS
MANAGEMENT IMPLICATIONS
These results provide a rare opportunity to estimate how the landcover of this fire-prone region may have looked at the time of European contact after millennia of Indigenous stewardship. What we learn is that chapparal would have comprised a much larger extent of vegetation cover over this landscape, on the order of 50% areal extent. We were able to measure how this chaparral extent declined greatly during post-contact periods. The extent of chapparal was effectively reduced to approximately half of what was present at European contact, with a complementary expansion of coniferous (Douglas Fir) and in some cases hardwood landcover extent, amounting to approximately a doubling of forest cover. Our working hypothesis is that this effect is due in part to the removal of cultural fire from the landscape, and other forms of Indigenous stewardship, as a result in changes of land tenure.
Moving forward, a better understanding of these historical trends can help inform what people term “healthy forest” land cover targets. What is considered “health” is worth examining closely to inform project-specific definitions, but in general management efforts appear to aim for a combination of wildfire resilience (including reducing threats of catastrophic fire to human communities) and ecosystem function.
Our results suggest that with the reintroduction of more active stewardship, including the restoration of cultural burning, building management targets with goals for chaparral as a dynamic part of the vegetation landcover mosaic will be key. This will be a deviation from historical approaches to planning management of forested areas as a stand-alone management unit, as these authors have observed when adaptive management plans for the region effectively “clip out” shrubs from management consideration. With this historical understanding, managers should consider chapparal a worthy ecosystem management target, and a critical element of a healthy functioning system in high fire return interval landscapes.
Another take home is that management targets in this landscape need to allow for dynamic vegetation and fire cycles over time, with planning accommodating shorter time intervals between fire events. Given the fire history of the study areas, it should be assumed that wildfire could potentially return within a few decades to places that have recently burned, and conversely that wholesale prevention of burns in these landscapes could lead to higher severity wildfires over the long term. This analysis can start to inform cyclical targets ranging from 1) lowfuel conditions typical of immediate post-treatment (or post-fire), to 2) the maximum tolerable fuels condition that should trigger a treatment scenario to reduce below high fire hazard conditions. In these study areas, the invasion of Douglas Fire into lower elevations has increased fuel hazards: consideration of the removal of low elevation Douglas firs could be part of a landscape-scale fuel reduction strategy. Here we propose a ‘Fire Exposure Metric’ to the region, where % woodland cover serves as a potential risk indicator.
Deeper analysis of what differentiates frequent burn zones from rare burn zones may help refine how to adjust management in response to topographic, weather and ecosystem drivers. The concept of tipping points, especially looking at how essentially “overstocking” of fuels resulting from fire suppression may increase conditions favoring fire spread due to canopy connectivity, could help refine cyclical forest management targets, with an upper threshold for stem density and canopy closure. With more analysis, the existence of a threshold for woodland cover as a tipping point for catastrophic fire would help refine priorities and timing of fuel reduction work. We estimated that a long-term rate of burning or thinning approximately 5 acres per1000 acres management are per year could help keep woody vegetation below the identified 60% threshold of high fire hazard. While this study focused primarily on the vegetation dimensions of frequent burn zones, further exploration of the role of wind corridors should be a high priority.
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Given that 90% of wildfires are started by humans, it should also be assumed that, whether intentionally or unintentionally, people will be the ignition source. As this region is experiencing an upsurge in the restoration of cultural and prescribed burning, there is the opportunity to incorporate this body of work into the return of intentional fire to the landscape, with appropriate safeguards and oversight. Leverage the opportunities presented by recent fires to apply stewardship approaches within their perimeters aimed at fuel reduction and ecological health.
Overall, the authors believe that with a better understanding of the historical ecology of our region, and the fact that greater spatial extent particularly of coniferous forest is in fact a historical anomaly, rather than the standard for a “healthy landscape,” can help move managers and the public to embrace more resilient landscape management targets. We are essentially inviting consideration of an alternative model for healthy vegetation patterns, one where chaparral is valued for habitat and carbon sequestration in a balanced mix with woodlands. Included in this proposed paradigm shift is the idea that the return of shrubs, in certain places, indicates the potential to restore a more resilient (and more frequent) fire cycle (including humans) through partnership with our local Indigenous leadership.
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SOURCES
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Healdsburg Tribune. 1933. “300 Acres of Mill Creek Timber Land Burned” October 20.
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Healdsburg Tribune. 1936. “County Fires Sweep 3000 Acres Bare.” Dec. 1.
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Press Democrat, The. 1902. “Landscape Doomed.” Fire above Glen Ellen. October 4.
Press Democrat, The. 1913. “Fire in Napa County Hills Last Night.” Described as on the county line opposite Glen Ellen. Started on 9-22. September 23.
Press Democrat. 1902a. “The Forest Fires.” Between Korbel and Guerneville. Started on July 15. July 17 edition. May have been across river from study area.
Press Democrat. 1902b. “Three Fires Burn.”
Press Democrat. 1903. “Two Fires Raging.” Yarbrough Canyon and Fitch Mountain. Started on July 2. July 3 edition.
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Press Democrat. 1909. “Campers Must Be Very Careful Now. State Forester Sends Warning Regarding the Starting of Any Forest Fires.” Include a list of 12 fire wardens in the county, including Thomas Johnson in Glen Ellen. 6-121909.
Press Democrat. 1910. “Report Big Forest Fire” July 11.
Press Democrat. 1916. “Flames Menace Rio Nido.” July 9.
Press Democrat. 1916b. “Forest Fire Breaks Out Again.” July 11.
Press Democrat. 1917a. “Great Damage Already Done As Fire Sweeps Over Big Area.” July 22.
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San Francisco Call. 1916a. “Fire Sweeps on Rio Nido.” July 13.
San Francisco Call. 1916b. “12 Big Forest Fires Spread in Sonoma.” September 12.
San Francisco Call. 1917a. “Resort Fire Swept.” July 21.
San Francisco Call. 1917b. “Rich Homes, Wineries of Four Sections Menaced” July 23.
San Francisco Call. 1917c. “Father and Son Believed Dead in the Flames.” July 24.
San Francisco Call. 1917d. “Fighters Win War on Forest Flames.” July 25.
San Francisco Call. 1917e. “Guerneville Fire Out After Long Battle.” July 26.
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Sargent, C.S. 1881. “Map of a Portion of California Showing the Distribution of Redwood Forests with Special Reference to the Lumber Industry.” Department of the Interior, Tenth Census of the United States. Shows conditions in 1880.
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Sayre, M.S. 1889. “Transcript of the Field Notes of the Survey of the Exterior and Subdivision Lines of Township 12 North Range 8 W.” General Land Office, U.S. Department of Interior. Microfiche obtained from Bureau of Land Management. Sacramento, California.
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Sonoma County Agricultural Preservation and Open Space District. 2014. “Key to Lifeform Classes—Phase 1 of the Sonoma County Veg Map.” Updated August 15, 2014. Accessed via: https://tukmangeospatial.egnyte.com/h-s/20130220/abc9964b29554abb
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Sonoma Democrat. 1871. “Woods on Fire.” Description of a wildfire in Sonoma Valley burning for five or six miles in a southeasterly direction. October 14.
Sonoma Democrat. 1871b. “Barn and Hay Burned.” Same fire as above October 21.
Sonoma Democrat. 1871c. “Woods Near Calistoga on Fire.” [reprint from the Calistoga Tribune, October 14.] October 28.
Sonoma Democrat. 1882. “That Dry Creek Fire.” Describes intentional burn started by ranchers a week or two earlier (October 7).
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