The landscape drives the stream: unraveling ecological mechanisms to improve restoration

The landscape drives the stream Unraveling ecological mechanisms to improve restoration

Paula Caroline dos Reis Oliveira

This research was conducted at the Institute for Biodiversity and Ecosystem Dynamics (IBED), Freshwater and Marine Ecology, Universiteit van Amsterdam, The Netherlands under the auspices of the Graduate School for Socio-Economic and Natural Sciences of the Environment (SENSE).

Funding for the research leading to this thesis was received through the CNPq Brazil (grant number 200879/2014-6, 2014), Science Without Borders program.

ISBN 978-94-91407-77-2 Cover: Helena Freddi Layout: JoĂŁo Lotufo Drawings: CĂŠsar Claro Trevelin Publisher: Universiteit van Amsterdam, IBED Amsterdam 2019

The landscape drives the stream Unraveling ecological mechanisms to improve restoration

ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. ir. K.I.J. Maex ten overstaan van een door het College voor Promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel op woensdag 20 november 2019, te 12:00 uur. door Paula Caroline dos Reis Oliveira geboren te Sao Paulo

Promotiecommissie: Promotores: prof. dr. ir. P.F.M. Verdonschot, Universiteit van Amsterdam dr. M.H.S. Kraak, Universiteit van Amsterdam Copromotores: dr. R.C.M. Verdonschot, Wageningen University & Research dr. H.G. van der Geest, Universiteit van Amsterdam Overige leden: prof. dr. M.A.S. Graรงa, Universidade de Coimbra prof. dr. A.P. van Wezel, Universiteit van Amsterdam prof. dr. W.P. de Voogt, Universiteit van Amsterdam prof. dr. C.A.M. van Gestel, Vrije Universiteit Amsterdam dr. M.C. van Riel, Universiteit van Amsterdam dr. L.H. Cammeraat, Universiteit van Amsterdam Faculteit der Natuurwetenschappen, Wiskunde en Informatica

Table of contents Chapter 1

General introduction

7

Chapter 2

40 years of stream restoration: lessons learned and future perspectives

15

Submitted to Journal of Environmental Management

Chapter 3

Sediment composition mediated land use effects on lowland streams ecosystems

35

Published in Science of the Total Environment

Chapter 4

Land use affects lowland stream ecosystems through dissolved oxygen regimes

57

Scientific Reports, under review

Chapter 5

Responses of macroinvertebrate communities to land use specific sediment characteristics in lowland streams

87

Science of the Total Environment, under review

Chapter 6

Lowland stream restoration by sand addition: impact, recovery and beneficial effects on benthic invertebrates

105

Published in River Research and Applications

Chapter 7

Synthesis

133

References

147

Summary

179

Samenvatting

185

Acknowledgements

193

Curriculum vitae

197

Chapter 1 General introduction

The landscape drives the stream

1.1 The landscape drives the stream Stream networks are an integrated part of landscapes and cannot be viewed in isolation from the surrounding terrestrial environment (Fausch et al., 2002; Ward, the valley rules the stream�. In accordance with Hynes, it is essential that any action aiming to improve aquatic ecosystem quality should be underpinned by knowledge of valley-stream interactions. Since anthropogenic activities continuously change the

CHAPTER 1

1989; Wiens, 2002; Poole, 2002). In 1975, H.B.N. Hynes stated that “In every respect,

is crucial to be able to protect and restore stream biodiversity and ecosystem processes.

To increase biodiversity and to achieve water quality goals (United Nations Millennium Development Goals; United Nations, 2008), around the world many attempts to reverse and mitigate degradation of stream ecosystems have been undertaken. Especially in the USA and in Europe legislation to support stream

CHAPTER 3

(e.g. Malmqvist and Rundle, 2002), unraveling the underlying ecological mechanisms

CHAPTER 2

landscape and impoverish as well as disconnect aquatic and terrestrial ecosystems

Directive (WFD) in Europe (Carvalho et al., 2019) and the Clean Water act in the USA (Doyle and Shields, 2012). Simultaneously, existing knowledge on stream ecology was translated more and more into restoration practices (Palmer et al., 2005; Lake et al.,

CHAPTER 4

ecosystem restoration has been implemented, such as the Water Framework

2005; Jahnig et. al, 2010; Roni et al., 2008; Verdonschot et al., 2016).

In stream restoration, outcomes below expectation are usually associated

CHAPTER 5

2007). Nevertheless, many restoration projects remained unsuccessful (Palmer et al.,

and implementation of measures (Jahnig et al., 2011). Stream restoration projects mostly targeted problems related to hydromorphological degradation, mainly focused on local interventions in stream channels and riparian zones (Lake, 2007). This made

CHAPTER 6

with a lack of a proper definition of goals and a consequent mismatch in the selection

due to channelization and flow regulation, and riparian zones were often converted into agricultural or urban areas, isolating the streams from the valleys (Violin et al.

2011; Verdonschot, 2006). Moreover, since stream morphology and hydrology are strongly interrelated, artificial changes in flow regime and a low hydromorphic habitat diversity are associated with low biodiversity and the loss of ecosystem processes (e.g.

Kingsford, 2000). Hence, hydromorphological measures may indeed restore biodiversity, as riverine species are adapted to natural hydraulic dynamics (Garcia et

9

CHAPTER 7

sense, because many stream ecosystems were hydromorphologically homogenized

Chapter 1

al., 2017), and habitat quality and many ecosystem processes are directly related to stream hydromorphology (Ward, 1989; Resh et al., 1988; Bunn and Arthington, 2002).

In addition to the beneficial effects of hydromorphological measures on CHAPTER 1

stream ecosystems, physico-chemical and biological aspects should be addressed as

CHAPTER 2

1994). Moreover, also biological factors such as species composition (Atkinson et al.,

well (e.g. Lake and Bond 2007; Palmer et al., 1997). Streams are impacted by a wide range of stressors, including changes in temperature (Rader et al., 2008), light (Liboriussen et al., 2005), nutrients (Friberg et al., 2010) and toxicants (Lenat et al., 2014), population dynamics (Tonkin et al., 2014) and the introduction of invasive species (Matsuzaki et al., 2012) can impact stream ecosystem functioning (Muotka and Laasonen, 2002). Yet, these factors are less frequently targeted in restoration

CHAPTER 3

projects, mainly because many of these stressors act on larger spatial scales, like entire streams, stream valleys or even catchments (e.g. Frissell et al. 1986, Poff et al., 1997; Allan, 2004), while in contrast most restoration measures consider small scales only (e.g., Sudduth et al., 2007). The lack of selecting the appropriate spatial scale is recognized as an important cause of the low success rates of restoration projects

CHAPTER 4

(Vehanen et al., 2010; Sundermann, et al., 2011). Moreover, when stream restoration measures are carried out in isolation, targeting only short stream stretches with a strong focus on instream effects, the connection between the stream and the surrounding terrestrial ecosystems in the valley is ignored (Pilotto et al., 2018).

CHAPTER 5

Thus,

improving

restoration

measures

requires

integrating

hydromorphological, physico-chemical and biological aspects (NĂľges et al., 2016) and addressing these over the appropriate spatial scales of catchment, valley and stream

CHAPTER 6

(Bernhardt and Palmer, 2011; Schiff et al., 2011; Verdonschot et al. 2012; Kail and

CHAPTER 7

1.2 Terrestrial inputs from the valley into the stream

Hering, 2009; Stranko et al., 2012; Weigelhofer et al, 2013).

To study the effects of the stream valley on the stream, analysing the relationship between instream processes and the land use in the valley could be a starting point. Stream ecosystems receive, amongst others, sediment, detritus, woody debris and nutrients from the adjacent terrestrial environment (Cummins et al., 1979; Jordan et al., 1997; Schriever et al., 2007). Many streams are predominantly fueled by allochthonous organic matter (Bernhardt et al., 2018), supporting most of the aquatic food-web. However, streams under influence of anthropogenic activities in the stream 10

The landscape drives the stream

valley receive less (course) particulate organic matter in comparison to un-impacted streams, whilst receiving more nutrients and toxicants (Collins et al., 2008; Bernhardt et al., 2017), as well as fine sediments (MacDonald et al., 2010; Guan et al., 2017).

sediment could be substantial (Naden et al., 2016).

Deposited fine sediments change the physical structure of the stream bed as well as the chemical composition of the sediment and the overlaying water.

Consequently, benthic invertebrates inhabiting these stream deposition zones are confronted with several physical and chemical stressors. The accumulation of fine particles in organs, such as gills and filter feeding apparatus, may cause disruption of respiration and feeding (Iglesias et al., 1996), while sessile or semi-sessile aquatic organisms may be buried by the deposited material (Wood et al., 2005). Alterations in the input of fine particles in stream deposition zones often lead to changes in the

CHAPTER 2

flowing streams, such as low gradient lowland streams, the amount of accumulated

CHAPTER 3

other depressions in the streambed (James, 2010; Zhang, 2017). Especially in slow

CHAPTER 1

These fine sediments accumulate in low flow deposition zones, such as pools and

al., 2014), oxygen concentration (Triska et al., 1993; Mulholland et al., 2005), the presence of potentially toxic substances (Larsen et al., 2010; Lopez-Doval et al., 2010), an increased turbidity (Sutherland et al., 2002), a decreased light availability for

CHAPTER 4

amount and type of organic matter, nutrient dynamics (Jordan et al., 1997; Stelze et

invertebrates (Burdon et al., 2013; Larsen et al., 2011; Ramezani et al., 2014) and a decrease of instream detritus and sediment quality (Ekholm and Krogerus, 2003; MacDonald et al., 2001; RabenĂ­ et al., 2005; Graham, 1990; Rowe et al., 1998).

CHAPTER 5

primary producers (Quinn et al., 1992), a reduction of habitats for aquatic

are still not fully understood.

1.3 Aim and objectives Since land use determines the origin, nature and quantity of the terrestrial inputs (Kellner, 2019) and the instream deposited particles (Phillips, 1991; Kronvang et al., 2013), we postulate that their effects on in-stream functioning and biodiversity are strongly land use specific. But only by unravelling the underlying mechanisms we will be able to better identify the stressors involved and to determine the pathways to restore degraded lowland stream ecosystems.

11

CHAPTER 7

effects to stream valley land use in terms of quality and quantity of terrestrial inputs

CHAPTER 6

Nonetheless, the underlying mechanisms linking these adverse instream ecological

Chapter 1

The aim of this thesis was therefore to unravel the mechanisms by which land use affects structure and functioning of lowland stream ecosystems.

To this end the following objectives were defined: CHAPTER 1

•

To evaluate 40 years of stream restoration practices by assessing the influence of policy goals on stream restoration efforts, the biophysical restoration objectives, the restoration measures, the scale on which these

CHAPTER 2

measures were applied and the accompanying monitoring efforts.

•

To unravel the mechanisms by which terrestrial runoff affects sediment composition and macroinvertebrate community composition in deposition zones of lowland stream ecosystems.

•

To determine if lowland stream sediment characteristics in terms of food

CHAPTER 3

resources and habitat structure are land use specific and if they shape macroinvertebrate communities.

•

To assess the impact of catchment land use on the structure (macroinvertebrate community composition) and functioning (instream

CHAPTER 4

oxygen regimes) of lowland stream ecosystems.

•

To improve the success of stream restoration projects by applying a novel approach, consisting of the addition of sand to the stream channel in combination with the introduction of coarse woody debris, to restore sandy‐

CHAPTER 5

bottom lowland streams degraded by channelization and channel incision.

CHAPTER 6

1.4 Outline In chapter 2, 40 years of ecological lowland stream restoration practices were evaluated based on an analysis of the influence of policy goals on stream restoration efforts, biophysical restoration objectives, restoration measures applied, the scale of application of these measures, and the accompanying monitoring efforts.

CHAPTER 7

To this purpose we combined information from five stream restoration surveys that were held among the regional water authorities in the Netherlands over the last 40 years and from an analysis of the international scientific publications on stream restoration spanning the same time period.

In chapter 3, we studied the effects of land use type related runoff on sediment composition and the subsequent impact on macroinvertebrates community composition in lowland stream deposition zones. The results of this chapter pointed at 12

The landscape drives the stream

a crucial role of sediment oxygen demand and sediment quality in linking land use to instream ecological effects. Therefore, in the chapters four and five we unraveled the mechanism of land use specific sediment deposition in lowland streams impacting purpose, in chapter 4, we studied the land use specific effects of sediment composition and substrate cover on dissolved oxygen regime, sediment oxygen demand and macroinvertebrate community composition. In chapter 5, we studied the

CHAPTER 1

instream oxygen regimes and macroinvertebrate habitat and food quality. To this

use types in the valley.

In chapter 6, a novel experimental stream restoration technique used to improve stream hydrology and morphology and to reconnect the lowland stream to its valley was introduced. Here, we tested the addition of sand in combination with woody debris in a previously incised, channelized lowland stream.

CHAPTER 3

on macroinvertebrate community composition in streams impacted by different land

CHAPTER 2

role of habitat structure and food quality of the sediment as an environmental filter

pathways by which land use type affects the structure and functioning of lowland stream ecosystems. Therewith we will be able to better identify the stressors involved

CHAPTER 7

CHAPTER 6

CHAPTER 5

and to determine the pathways to restore degraded lowland stream ecosystems.

CHAPTER 4

Finally, in the synthesis we proposed a framework to evaluate the main

13

Chapter 2 40 years of stream restoration: lessons learned and future perspectives Paula C. dos Reis Oliveira Harm G. van der Geest Michiel H. S. Kraak Judith J. Westveer Ralf C. M. Verdonschot Piet F. M. Verdonschot Submitted to Journal of Environmental Management

Author contributions: PCRO, JJW and PFMV designed the study. PCRO and JJW conducted the survey. PCRO performed the literature review. PCRO, JJW, PFMV, MK, HG and RCMV wrote most of the manuscript.

The landscape drives the stream

A mismatch between restoration goals and measures was observed.

•

Proper stream restoration monitoring delays, acceleration is recommended.

•

Large scale processes need much more attention in restoration.

Abstract Stream restoration efforts have increased, but its success rate is still rather low. The underlying reasons for these unsuccessful restoration efforts remain inconclusive and need urgent clarification. Therefore, the aim of the present study was to evaluate 40 years of stream restoration to fuel future perspectives. To this purpose we evaluated the influence of policy goals on stream restoration efforts, biophysical restoration objectives, restoration measures applied including its scale and monitoring efforts. Information was obtained from five stream restoration surveys that were held among the regional water authorities in the Netherlands over the last 40 years, and from an analysis of the international scientific publications on

CHAPTER 2

•

CHAPTER 3

Legislation motivated the increase in stream restoration efforts.

CHAPTER 4

•

CHAPTER 1

Highlights

environmental legislation. However, proper monitoring of its effects was often lacking. Furthermore, a mismatch between the initial restoration goals and the actual restoration measures taken to achieve these goals was observed. Measures are still mainly focused on hydromorphological techniques, while biological goals remain underexposed and therefore need to be better targeted. Moreover, restoration

CHAPTER 6

a considerable increase in stream restoration efforts, especially motivated by

CHAPTER 5

stream restoration spanning the same time period. Our study showed that there was

large scale ecological processes for stream ecosystem recovery. In order to increase the success rate of restoration projects, it is recommended to improve the design of the accompanying monitoring programmes, allowing to evaluate, over longer time periods, if the measures taken led to the desired results, and secondly to scale up the spatial scale of stream restoration projects from local instream efforts to catchment wide measures to tackle the overriding effects of catchment wide stressors.

17

CHAPTER 7

practices occur mainly on small scales, despite the widely recognized relevance of

Chapter 2

Key words: freshwater restoration, legislation, WFD, clean water act, catchment scale, restoration techniques.

1. Introduction CHAPTER 1

Degradation of stream ecosystems is widely recognized as the main cause of biodiversity impoverishment and the loss of ecosystem services (Malmqvist and Rundle, 2002; TEEB, 2010). To halt further degradation of the ecological, hydrological, morphological and physical-chemical status of water bodies, national and

CHAPTER 2

international regulatory organizations enforced legislations, such as the Water Framework Directive (WFD) in Europe (Carvalho et al., 2018) and the Clean Water Act in the USA (Doyle and Shields, 2012). These incentives boosted the number of planned and realized stream restoration projects (Bernhardt and Palmer, 2007; Violin et al.,

CHAPTER 3

2011; Wilcock et al., 2009). In parallel, the scientific community made efforts to enhance the knowledge on stream restoration ecology and to translate this knowledge into restoration practices (Palmer et al., 1997; Lake et al., 2007).

CHAPTER 4

Despite the rapid increase in stream restoration funding, activities and research, success rates remained quite low (Palmer et al., 2010). Restoration practices still do not sufficiently take into account the appropriate scales, ranging from instream habitats to entire catchments, nor the complexity of stream ecosystems and should consider the key hydrological, morphological, chemical, and biological actors in

CHAPTER 5

concert (NĂľges et al., 2016). Hence, the precise reasons for the unsuccessful restoration efforts remain still inconclusive (e.g. Miller and Kochel, 2009; NĂľges et al., 2016) and need urgent clarification. The aim of the present study was therefore to evaluate 40 years of stream restoration to fuel future perspectives. To this purpose

CHAPTER 6

we evaluated: (1) the influence of policy goals on stream restoration efforts, (2) biophysical restoration objectives, (3) restoration measures, (4) the scale on which these measures were applied, and (5) monitoring efforts. To this end we integrated information obtained from five stream restoration surveys that were held among

CHAPTER 7

water authorities in the Netherlands over the last 40 years, and from an analysis of the international scientific publications on stream restoration spanning the same time period.

2. Sources of information Dutch stream restoration questionnaires were send to the regional water authorities and nature conservation agencies in the Netherlands in 1993 (Hermens and Wassink, 1992; Verdonschot et al., 1995), 1998 (Verdonschot, 1999; Verdonschot 18

The landscape drives the stream

and Nijboer, 2002), 2003 (Nijboer et al., 2004), 2008 (Didderen et al., 2009), and 2015 (this study). All questionnaires considered policy goals (mostly legislation and regulations), biophysical objectives, measures applied, the spatial scale of the

organisms were included in the most recent survey.

A literature review was carried out covering the period from 1975 to 2015 (in supplementary material). In total, 260 scientific articles on restoration of low-gradient streams were examined on: geographic location, policy goals, biophysical objectives, restoration measures, spatial scale and the monitored groups of aquatic organisms. To aid comparisons, both the results of the Dutch restoration questionnaires and those obtained in the literature study were grouped in similar time-clusters: before 1993, 1994-1998, 1999-2003, 2004-2008 and 2009-2015.

CHAPTER 2

anthropogenic land use and on awareness regarding the dispersal capacity of aquatic

CHAPTER 3

progressive insights, additional questions on the effects of large-scale pressures from

CHAPTER 1

measures, and monitoring efforts (Table S1, in supplementary material). Based on

Our analysis covered four decades of stream restoration practice. Since the first restoration projects documented in the early eighties of the previous century, a strong increase in the number of projects carried out by the Dutch water authorities is

CHAPTER 4

3. The influence of policy goals on stream restoration efforts

carried out, in the most recent years about 30-35 new restoration projects were performed yearly. This increase in project numbers is corroborated by an increase in numbers of international scientific publications (Figure 1A). Most of the scientific

CHAPTER 5

observed (Figure 1, top panel). While in the previous century only a few projects were

important legislations and regulations regarding freshwater ecosystem restoration (Figure 1B).

In addition, in the questionnaires the Dutch water managers were asked to what extent these policy goals motivated their restoration efforts. From the answers it became clear that new projects directly aimed to implement preceding legislations and regulations. In the Netherlands, especially the legislation from 1990 to establish a National Ecological Network (EHS; Minsterie van LNV, 1990) to protect and connect natural areas, the designation of Natura 2000 sites to protect threatened species and their habitats based on the provisions of the Birds and Habitats directives (EC, 1992)

19

CHAPTER 7

into the underlying motivations, a timeline was constructed showing the most

CHAPTER 6

publications referred to projects in the USA (49 %) and Europe (34 %). To gain insight

Chapter 2

and the EU WFD from 2000 (EC, 2000) to protect and manage water resources were leading.

Similarly, in the USA various consecutive regulations motivated stream CHAPTER 1

restoration. The United States (U.S) Clean Water Act (33 U.S.C. §1251 et seq., 1972),

CHAPTER 2

was first mentioned as part of the mitigation sequence. The ‘principles for ecological

enacted in 1972 to regulate pollutant discharges and to define quality standards for surface waters, formed the umbrella for the Wetland Restoration Act (16 U.S.C. 3951 et seq.; 104 Stat. 4779, 1990), in which restoration of degraded stream ecosystems restoration of aquatic resources’ in 2000 was the next important milestone in stream restoration policy (USEPA, 2000), while in 2008 restoration was also clearly defined as compensatory mitigation in a regulation under the Clean Water Act (CWA, Section

CHAPTER 3

404).

In the open literature, examples of the initiation of new restoration projects after new regulations came into practice can be found in consecutive publications, amongst others by McCuskey et al., (1994), Johnson et al. (2002), Shields et al. (2003),

CHAPTER 4

Frimpong et al., (2006), Stokstad (2008) and Shields (2009). These examples show the importance of environmental legislation as a regulatory tool to start stream restoration projects, despite the many obstacles to be taken, such as methodological issues and the design of monitoring programmes (Bernhardt and Palmer, 2011;

CHAPTER 5

Voulvoulis et al., 2017; Birk et al., 2012; Carvalho et al., 2018). As a positive feedback of the increased number of restoration projects, science further developed, which in turn allowed to refine the regulatory requirements (Hill et al., 2013).

CHAPTER 6 CHAPTER 7 20

The landscape drives the stream

Dutch restoration projects Publications

CHAPTER 1

250

150

1999-2003

2004-2008

2009-2015

1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Period

Natuurbeleidsplan EHS

Clean Water Act

1

Natura 2000

Water Framework Directive – WFD

Principles for ecological restoration

Wetland Restoration Act

First deadline of WFD

National compensatory mitigation policy

Figure 1: Timeline of the number of Dutch stream restoration projects and scientific publications per time period (before 1993, 1993-1998, 1999-2003, 2004-2008, and 2009-2015)(A), and the introduction of freshwater restoration legislations and regulations in the Netherlands, Europe (yellow) and the USA (blue) (B).

4. Biophysical restoration objectives

CHAPTER 3

1993-1998

CHAPTER 4

before 1993

CHAPTER 5

0

CHAPTER 6

50

CHAPTER 2

100

Morphological objectives were the most frequently referred ones during all studied periods in both Dutch restoration projects and scientific publications (Figure 2, first panel). The measures involved were re-profiling of the stream bed and banks and re-meandering of the stream channel, in the Netherlands as well as abroad (e.g., Rinaldi and Johnson, 1997; Kondolf et al., 2001; Kasahara and Hill, 2006; Krapesch et al., 2009; Schiff et al., 2011; Kristensena et al., 2014).

In Dutch restoration projects hydrological objectives were frequently referred to by the water authorities, but these appeared to a lesser extent in the 21

CHAPTER 7

Number

200

Chapter 2

scientific publications (Figure 2, second panel). In contrast, until 2004 biological objectives were more frequently mentioned in the scientific literature than in the Dutch questionnaires. In the most recent questionnaire, however, the biological objectives became the most important ones in the Dutch projects, driven by the WFD CHAPTER 1

that requires specific biological goals to be achieved (Figure 2, third panel). Yet, to achieve these goals, in the Dutch projects as well as in the scientific publications, almost no direct biological measures (e.g., species reintroduction and invasive species control) were taken, but only indirect ones, mainly hydromorphological measures to

CHAPTER 2

improve habitat quality and connectivity (e.g. constructing fish ladders and bypasses alongside dammed streams).

Chemical water quality objectives were less frequently mentioned by the

CHAPTER 3

Dutch water authorities and in the scientific literature, except for the period 20042008 (72%; Figure 2, fourth panel). Given that in the period before 1993 many wastewater treatment plants (WWTP) were built and improved, it is surprising that chemical objectives were not more prominent in this period. However, because WWPT’s are more associated with human health and sanitation rather than with

CHAPTER 4

freshwater ecosystem restoration, most probably these measures were not identified as stream restoration measures in our literature review (Figure 2 fourth panel).

Societal objectives were least considered in Dutch stream restoration projects and in scientific publications (Figure 2 bottom panel).

CHAPTER 5 CHAPTER 6 CHAPTER 7 22

CHAPTER 4 CHAPTER 5 CHAPTER 6

n.a.

CHAPTER 7

Societal objectives

Chemichal objectives

Biological objectives

CHAPTER 3

CHAPTER 2

Morphological objectives

CHAPTER 1

Hydrological objectives

The landscape drives the stream

1

Figure 2: Percentage of objectives named in the surveys related to hydrology, morphology, chemistry, biology and society in Dutch stream restoration projects (D) and in scientific publications (S) per time period (before 1993: D n=45; S n=9, 1993-1998: D n=59; S n=22, 19992003: D n= 101; S n=38, 2004-2008: D n= 82; S n=52, 2009-2015 : D n= 246; S n=143).

23

Chapter 2

5. Restoration measures The five most frequently applied Dutch stream restoration measures all concerned hydromorphological improvements: re-meandering, channel re-profiling, providing space for inundation, bypassing dams and stimulating the development of CHAPTER 1

riparian vegetation (Table 1). In the literature, a very similar pattern was observed, since the majority of publications referred to hydromorphological measures, especially enhancing instream structure (e.g., rocks), adding large wood, riparian vegetation development, re-meandering and creating space for inundation (Table 1).

CHAPTER 2

Yet, a more diverse set of measures was applied in the Dutch restoration projects.

Improving chemical water quality and applying biological management measures became more apparent only after 2009. In Dutch restoration projects,

CHAPTER 3

measures to improve the chemical water quality often referred to the reduction of runoff of fertilizers, the construction of (riparian) buffer zones and, more recently, changing the land use of the stream valley. Internationally, the main measures to improve water quality were dredging the stream bottom and improving wastewater treatment efficiency. Biological measures applied in stream restoration projects were

CHAPTER 4

recorded mostly after 2004. Dutch measures were generally related to changes in instream vegetation mowing practices, while the exclusion of herbivores by fencing riparian zones was internationally the most commonly mentioned measure, followed by the re-introduction of species (Table 1).

CHAPTER 5 CHAPTER 6 CHAPTER 7 24

The landscape drives the stream

n.a.

0

0

0

0

6

69

65

69

82

11

27

17

13

17

0

0

62

73

0

0

6

0

1

77

30

85

100

0

0

0

4

15

54

44

31

36

0

0

0

0

1

39

22

54

45

0

5

0

2

0 1

n.a.

0

44

69

72

0

0

3

0

Reconnect backwaters

n.a.

8

35

23

55

0

0

0

0

0

Re-meander the stream channel Promote rain water infiltration in the uplands Reduce water extraction Remove barriers and wiers/restore connectivity Disconnect or redirect agricultural side-streams Install bank protection

n.a.

77

61

77

100

0

9

14

15

16

54

26

39

36

0

0

3

0

0

15

30

0

18

0

0

3

0

1

62

39

69

91

0

0

0

4

6

0

0

15

45

0

0

0

0

1

n.a.

0

4

0

0

11

9

6

8

7

Remove bank fixation

n.a.

39

9

46

91

0

0

3

2

6

Re-profile stream banks Dig isolated pools in the stream valley (habitat amphibians) Develop a near-natuiral riparian zone (forest, wooded bank) Dig one-side connected backwaters

n.a.

62

35

85

82

0

0

3

0

2

77

52

69

73

0

0

0

0

2

0

4

62

64

0

0

0

0

1

0

0

31

27

0

0

0

0

0

0

30

46

82

0

0

0

0

0

31

22

46

55

0

5

0

0

1

77

44

85

100

0

0

0

0

0

0

0

4

100

33

9

17

27

15

8

30

23

64

22

14

14

27

18

0

17

23

18

22

5

3

10

14

31

30

15

64

11

0

3

2

6

0

0

0

0

0

0

0

0

1

54

52

69

91

11

18

11

15

13

Construct a two-stage profile Construct bypasses (fish ladders), e.g. around dams, wiers Enhance in-stream wood debris retention or add large wood Install in-stream structures, like sand banks and stones Restore pool sequences or poolriffle units Initiate micromeanders (add deflectors) Stimulate vegetation development on sand bars Stimulate riparian vegetation development

n.a. n.a. n.a. n.a.

n.a. n.a. n.a.

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

25

CHAPTER 2

n.a.

45

CHAPTER 3

n.a.

39

CHAPTER 4

n.a.

22

CHAPTER 5

n.a.

39

Raise the ground water level

Lower stream banks gradually to create inundation zones/wetlands

Morphology

n.a.

CHAPTER 6

Develop hydrological buffer zones

Publication (%) before 1993- 1999- 2004- 20091993 1998 2003 2008 2015

CHAPTER 7

Hydrology

Restore the histrorical stream network Provide space for inundation / restore wetlands or floodplains Restore the (semi-)natural stream bed Channel re-profiling (shallowing, narrowing, widening) Remove drainage structures in the stream valley

Dutchwater authorities (%) before 1993- 1999- 2004- 20091993 1998 2003 2008 2015

CHAPTER 1

Table 1: Percentage of Dutch water authorities and scientific publications applying stream restoration measures (morphological, hydrological, chemical, biological and societal) per time period (before 1993, 1993-1998, 1999-2003, 2004-2008, 2009-2015).

CHAPTER 1 CHAPTER 2

Chemical water quality

Chapter 2

CHAPTER 4

Biological management

CHAPTER 3 CHAPTER 5 CHAPTER 6

Social and Others

Dutchwater authorities (%)

Publication (%)

before 1993- 1999- 2004- 20091993 1998 2003 2008 2015

before 1993- 1999- 2004- 20091993 1998 2003 2008 2015

Construct horse-shoe wetlands

n.a.

16

4

0

0

0

0

0

0

0

Dredge the stream bottom

n.a.

0

26

0

36

11

5

3

2

3

Construct helophyte filters

n.a.

16

35

23

0

0

0

0

0

0

Construct buffer zones

n.a.

39

35

23

64

0

0

3

0

2

Separate wastewater flows

n.a.

46

26

0

0

0

0

0

0

1

Reduce fertilizer runoff input

n.a.

54

52

39

18

0

0

0

2

1

Reduce the inlet of non-local water

0

17

15

18

0

0

0

0

0

Reduce sewage storm overflows

n.a.

39

44

15

9

0

0

0

0

3

Reduce toxic load

n.a.

39

30

15

9

11

0

0

0

1

Reduce the load of pollutants

n.a.

0

39

8

9

0

0

0

0

3

Improve wastewater treatment

n.a.

15

13

15

9

11

5

0

2

3

Change stream valley land use Introduce large herbivores (grazing of stream banks) Exclude herbivores (fencing) Active biological control (eliminate exotic species) Extensify instream macrophyte maintenance Adjust water management to benefit fish Promote natural water level management Extensify bank vegetation maintenance Re-introduce species Species specific measures to conserve or initiate recovery of populations Recreational and aesthetic measures Best management practices in the catchment Acidification control

n.a.

0

4

54

64

0

0

0

2

1

0

9

54

36

0

0

0

0

0

0

0

0

0

0

0

6

4

2

0

30

8

9

0

0

0

0

1

0

44

85

100

0

0

0

0

0

0

0

8

27

0

0

0

0

0

0

35

39

64

0

0

0

0

0

0

52

77

73

0

0

3

2

1

8

17

8

9

0

0

6

2

2

0

35

46

55

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

22

0

0

0

0

3

2

2

n.a.

0

0

0

0

0

0

0

4

0

Use of models or simulations

n.a.

0

0

0

0

0

0

0

4

11

Eliminate thermal pollution

n.a.

0

0

0

0

0

0

3

0

0

n.a.

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

n.a. n.a. n.a.

CHAPTER 7

6. The scale on which restoration measures were applied The majority of stream restoration projects in the Netherlands (Figure 3A) and in the scientific publications (Figure 3B) considered small scales only. Ecological processes at the catchment scale, such as aquatic organism dispersal and colonization ability and land use effects were rarely mentioned, despite their acknowledged importance for ecological recovery (Schiff et al., 2011; Verdonschot et al. 2012; Kail and Hering, 2009; Stranko et al., 2012; Weigelhofer et al, 2013).

26

The landscape drives the stream A

small scale

80%

CHAPTER 1

large scale

60% 40% 20% 0% before 1993 1993-1998 1999-2003 2004-2008 2009-2015 Period

CHAPTER 3

B 100% 80% 60%

CHAPTER 4

% of publications

CHAPTER 2

% of Dutch restoration projects

100%

40% 20%

Figure 3: The spatial scale considered in stream restoration projects in the Netherlands (A) and in scientific publications (B) per time period (before 1993, 1993-1998, 1999-2003, 2004-2008, 2009-2015).

The limited availability of space for restoration projects, often only available in nature conservation areas, co-directed the selection of sites in the Netherlands, as most of the restored stream trajectories were located in areas designated as nature instead of in agricultural or urban areas. Restoration of stream trajectories in a landscape in a relatively good environmental state, such as forests, have a higher chance of success and may cost less. This connection between conservation and restoration shows that both are still seen as complementary (Ormerod, 2003). The restoration of highly impacted streams in urbanized and agricultural areas is thus often neglected, most probably due to the global model of “economic development�, that does not prioritize natural ecosystem processes nor biodiversity in heavily 27

CHAPTER 7

1

CHAPTER 6

before 1993 1993-1998 1999-2003 2004-2008 2009-2015 Period

CHAPTER 5

0%

Chapter 2

exploited areas (Marques et al., 2019). According to Kail et al. (2009), the problems to restore degraded urban and agricultural streams also arise from a lack of knowledge on how to enhance the quality of systems in such a low ecological state. Examples refer to, amongst others, the technical difficulties to improve wastewater treatment CHAPTER 1

plant effluents and to limit runoff from anthropogenic land uses (Bernhardt and

CHAPTER 2

Over the last 40 years, substantial biological monitoring took place in the

Palmer, 2007; Rhodes et al., 2007; Weigelhofer et al., 2013).

7. Monitoring efforts majority of Dutch stream restoration projects (98% in 1999-2003, 80% in 2004-2008 and 83% in 2009-2015). Macroinvertebrates and macrophytes were monitored most frequently (Figure 4A). Over the studied 40 years’ time period, 99% of the scientific

CHAPTER 3

publications mentioned the monitoring of one or multiple organism groups, mainly fish and macroinvertebrates (Figure 4B).

Although a high percentage of restoration projects were monitored, in both Dutch restoration projects and in the scientific publications little information was

CHAPTER 4

available about the monitoring design (e.g. Before-After or Control-Impact) and duration (e.g. number of years pre- and post-restoration). In Dutch restoration projects information about the application of a before-after monitoring design was available for the period of 2004-2008. For macrophytes, a before-after monitoring

CHAPTER 5

design was used in 69 % of the total number of projects. For fish this percentage was 65 %, for macroinvertebrates 50 % and for algae only 20%. Even if a before-after design was used, monitoring was in most cases not specifically designed for the restoration project of concern. It is common practice to simply use the standard

CHAPTER 6

monitoring sites already present in the streams without taking the potential effects of the measures on the biota into account. Indeed, the majority of Dutch respondents pointed at the lack of proper monitoring (questionnaire of 2009-2015). Also worldwide this has been repeatedly underlined as a key problem in evaluating the

CHAPTER 7

effects of stream restoration (e.g. Kondolf and Michlei, 1995; Wissmar and Beschta, 1998; Downs and Kondolf, 2002; Bash and Ryan, 2002; Palmer et al., 2005; Woolsey et al., 2007; Klein et al., 2007; O’Donnell and Galat, 2008; Densmore and Karle, 2009; Jahnig et al., 2011; Bennett et al., 2016). Often, pre- and post-monitoring is not included at all in the restoration plans, and in those few cases where monitoring took place, a proper design, such as a before-after and impact-control set-up, in combination with a rationale on the choice of biological metrics was rarely considered.

28

The landscape drives the stream

The lack of meaningful monitoring data hampers a proper evaluation of stream restoration projects (Jansson et al., 2005) and, consequently, the actual reason for the observed low success rates remain unknown. In order to improve the design of 2005; Lake et al.,2007) and practical (e.g. Voulvoulis et al., 2017; Birk et al, 2012; Verdonschot and Nijboer, 2002) guidelines should be applied, and more funding to undertake meaningful monitoring must be allocated (Gillilan et al., 2005; Jansson et

CHAPTER 1

the monitoring programs accompanying restoration projects, theoretical (Palmer et al.

8. Future perspectives Over the last 40 years, stream restoration techniques improved and new techniques were introduced, such as the addition of large wood, that has been used to enhance instream habitat quality in many projects around the world (Bernhardt et al., 2005; Feld et al., 2011; Roni et al., 2014). More recently, “rewilding� approaches, such as rehabilitation stream side marshes by reconnecting the stream and its valley and reintroducing beavers have been increasingly used to restore degraded stream 29

CHAPTER 7

Figure 4: Number of restoration projects in the Netherlands (A) and international scientific 1 publications (B) in which monitoring of macrophytes, fish, macroinvertebrates and benthic algae has been carried out per time period (before 1993, 1993-1998, 1999-2003, 2004-2008, 2009-2015).

CHAPTER 6

CHAPTER 5

B

CHAPTER 4

CHAPTER 3

A

CHAPTER 2

al., 2005).

Chapter 2

ecosystems and to increase biodiversity (Baker and Eckerberg, 2016; Hood and Larson, 2015; Roni and Beechie, 2013, dos Reis Oliveira et al., 2019).

While in the past many projects intended to improve the entire stream CHAPTER 1

ecosystem, they in fact solely focused on specific morphological (habitat

CHAPTER 2

habitat heterogeneity increases, so does biological diversity’ (Field of Dreams

improvement) or hydrological (flow conditions) conditions, as was already observed two decades ago (Verdonschot and Nijboer, 2002; Palmer et al., 2010; Palmer et al., 2014). This was and can still be explained by a firm trust in the statement that ‘if Hypothesis; Palmer et al., 1997). Nevertheless, a fully integrative approach, tackling all stressors, but also taking important biological aspects into account, such as colonization (Westveer et al., 2018), dispersal (Engström et al., 2009), distance to

CHAPTER 3

source populations (Brederveld et al., 2011; Stoll et al., 2013), re-introduction of species (Jourdan et al., 2018) and control of invasive species (Scott and Helfman, 2001), are still rare. Moreover, stream restoration practice should also be aware of the ecological risks that can occur after restoration, such as ecological traps when species get more threatened by the novel habitat conditions post restoration in

CHAPTER 4

comparison to the initial conditions (Robertson et al., 2013; Hale et al., 2015), providing opportunities for invasive species (Matsuzaki et al., 2012; Franssen et al., 2015; Merritt and Poff, 2010), introducing non-natural hydrological conditions (Vehanen et al., 2010; Jeffres and Moyle, 2012) and enhancing sediment toxicity to

CHAPTER 5

amphibians (Snodgrass and Stoll, 2008).

Furthermore, many stream restoration projects still consider small scale measures and solutions, and neglect that stream ecosystems are strongly governed by

CHAPTER 6

catchment scale processes (Allan, 2004; Palmer, 2010; Ward, 1998; Wiens, 2002; Sundermann and Stoll, 2011). Several authors have already shown that large scale restoration is crucial for ecological recovery (Schiff et al., 2011; Verdonschot et al., 2012; Kail and Hering, 2009; Stranko et al., 2012; Weigelhofer et al, 2013).

CHAPTER 7

To improve the success rate of stream restoration projects, goals and measures have to match, science-based monitoring should be performed, and the catchment scale has to be considered. In the Netherlands, even 15 years after Verdonschot and Nijboer (2002) proposed to include large scale effects in the guidelines for stream restoration, thus to consider ecological processes that occur at the catchment scale or larger, such as land use impacts and dispersal capacity of

30

The landscape drives the stream

aquatic organisms (in line with Palmer et al., 2014), to date this still remains a challenge.

restoration projects. From their answers it appeared that only half of the water managers took faunal dispersal capacity and colonization processes into account in stream restoration projects, and if they did, it mainly concerned fish (Figure 5A).

Macroinvertebrate dispersal capacity was rarely included in the design and implementation of restoration projects, although this group is one of the key indicators of ecological quality, an essential food source for a number of fish species, and are essential for stream ecosystem recovery through their role in many ecosystem processes. The most commonly used measure to improve dispersal capacity was to connect restored trajectories to the adjacent up- and downstream sections, while the reintroduction of species was the least frequently applied measure

CHAPTER 2

the inclusion of dispersal capacity and land use effects in the design of stream

CHAPTER 3

considered, in the latest questionnaire we asked the Dutch water authorities about

CHAPTER 1

To better understand the reasons why landscape ecology is poorly

depends on, amongst others, habitat quality and food availability (van Puijenbroek et al., 2019). Furthermore, colonization potential depends on the distance to source populations and their densities, both driving the success of colonization (Westveer et

CHAPTER 4

(Figure 5B). While dispersal capacity relates to connectivity, colonization and survival

Tonkin et al., 2014; Winking et al., 2014). Hence, it is concluded that dispersal capacity must be incorporated into the design of restoration projects.

CHAPTER 5

al., 2018), which is generally limited to a distance of about 5 km (Stoll et al., 2013;

CHAPTER 6

A- Is di spersal ca pacity take in account i n the design a nd implementation of ri ver restoration projects?

Yes, fish and macroinvertebrates

CHAPTER 7

Yes, in particular for fish

No

0

25

50

% of respondents B- Whi ch measures are implemented to increase dispersal?

Reintroduction of species

31 Improve terrestrial connectivity

75

100

No

Chapter 2

0

25

50

75

100

75

100

% of respondents B- Whi ch measures are implemented to increase dispersal?

Reintroduction of species

CHAPTER 1

Improve terrestrial connectivity

CHAPTER 2

Improve aquatic connectivity

CHAPTER 3

0

25

50 % of res pondents

discussed, but not implemented

not implemented

implemented

CHAPTER 4

Figure 5: Percentage of water authorities (n = 11) that took the dispersal capacity of aquatic organisms (macroinvertebrates and fish) into account (A). Percentage of water authorities that took measures to increase dispersal potential (B).

All water managers indicated that they took the effects of the land use in the stream valley into account when designing restoration projects, yet the scale

CHAPTER 5

considered differed (Figure 6A). The majority of stream restoration projects in the Netherland only considered small scales, despite that the water authorities were well aware of the major environmental problems, such as increased sedimentation, nutrient and toxic loads, extreme peak floods and droughts, and losses of riparian

CHAPTER 6

woody vegetation (Figure 6B). Yet, these problems can only be tackled at a large scale (Violin et al., 2011; Kail and Wolter, 2011; Weigelhofer et al., 2013). Furthermore, there is no single solution to reduce all land use impacts. Stream restoration measures should therefore identify and tackle catchment specific stressors, relevant for the site

CHAPTER 7

of interest (Palmer et al., 2010). Yet, still little knowledge is available on how the mechanisms behind land use impacts act on the stream ecosystem (dos Reis Oliveira et al., 2018). Therefore, to further improve the number of successful stream restoration projects, catchment specific land use impacts should receive much more attention.

32

The landscape drives the stream

A- Are envi ronmental effects of land use takes i nto account i n the design a nd execution of river restoration projects?

Yes, on a small scale

No

25

0

50 % of res pondents

75

100

75

100

B- Whi ch stressors were posed by the s urronding land use?

CHAPTER 3

Water inlet

CHAPTER 2

CHAPTER 1

Yes, on a large scale

Extreme peak flow/drought

Sediment runoff

Lack of riparian vegetation 0

50

25

% of res pondents

Figure 6: Percentage of water authorities (n = 11) that took land use into account in restoration projects (A). Effects of surrounding land-use observed in restored stream trajectories (B).

In conclusion, over the last 40 years there was a considerable increase in stream restoration efforts motivated by environmental policy, legislation and

CHAPTER 6

Nutrient load

CHAPTER 5

CHAPTER 4

Toxic load

measures, a monitoring deficiency, and restoration plans neglecting large scale catchment wide effects hampered the success of ecological stream restoration. It is therefore recommended to improve the monitoring programs accompanying restoration projects by applying the proper design, matching the relevant spatiotemporal dimensions for the ecosystem under study. This allows to evaluate, over longer time periods, if the measures taken led to the desired results, and secondly to scale up the spatial scale of stream restoration projects from local instream efforts to catchment wide measures.

33

CHAPTER 7

regulations. Yet, a mismatch between biophysical objectives and restoration

Chapter 2

Supplementary material

Scale

CHAPTER 2 CHAPTER 3

Monitoring

CHAPTER 1

Biophysical objectives

Table 1: Categories and respective definitions (parameters or key word) from stream restoration biophysical objectives, scale and monitoring.

Category

Parameter/ key-words

Hydrological

flow, hydraulics, velocity, discharge, flood, drought, retention, turbulence and transport

Morphological

channel configuration, substrate cover, digging, adding structures, habitat, shelter

Chemichal

nutrients load, toxic compounds (metals, pesticides), pH, conductivity, redox, oxygen, water and sediment quality

Biological

Species, population or community recovery, stocking, re-introduction, invasive species control

Societal

ethnology, heritage, aesthetic, recreation

Large Small

entire stream, stream stretch or lateral channel longer than 1500 m, catchment, surrounding land use (> only riparian zone), aquifer and effluents from diffuse source, sewage and WTP stream stretch shorter than 1500 m

Fish

Community, population or specific species

Macroinvertebrate

Community, population or specific species

Macrophyte

Instream aquatic taxonomic groups

Algae

Algae, phytobenthos and periphyton

CHAPTER 4

Literature review Scientific articles from 1975 until 2015 were selected at the search engines Web of Science, Scopus and Google scholar by using the following key-word:

CHAPTER 5 CHAPTER 6

“lowland reach”* OR “lowland channel”* OR “lowland stream”* OR “lowland river”* OR “lowland creek”* OR “lowland ditch”* OR “low gradient reach”* OR “low gradient channel”* OR “low gradient stream”* OR “low gradient river”* OR “low gradient creek”* OR “low gradient ditch”* AND restor* OR recov* OR rehabilit* OR revitali* OR renat* OR enhance* OR mitigate*

CHAPTER 7

Acknowledgements: We would like to thank the Dutch water authorities Waterschap Vallei en Veluwe, Waterschap De Dommel, Waterschap Peel en Maasvallei, Waterschap Vechtstromen, Waterschap Brabantse Delta, Waterschap Aa en Maas, Waterschap Rijn en IJssel, Waterschap Rivierenland, Waterschap Roer en Overmaas, Waterschap Hunze en Aa´s and Waterschap Drents Overijsselse Delta for participating in the survey. PCRO received funding from CNPq Brazil (grant number 200879/2014-6, 2014) and JJW was funded by the Dutch foundation for applied water research (STOWA).

34

Chapter 3

Chapter 3 Sediment composition mediated land use effects on lowland streams ecosystems Paula C. dos Reis Oliveira Michiel H. S. Kraak Harm G. van der Geest Sofia Naranjo Piet F. M. Verdonschot

Published in Science of the Total Environment 631–632 (2018): 459–468

Author contributions: PCRO, PFMV and MK designed the experiment. PCRO and SN conducted the experiment. PCRO analyzed most of the data, and wrote most of the manuscript together with SN, PFMV and MK. PFMV, MK and HG advised on practical issues during the course of the experiment and data processing and contributed to editing and revising draft versions of the manuscript.

The landscape drives the stream

Highlights • Instream deposition zone sediment composition is land use specific.

• Agricultural land use affects streams at the species, community and ecosystem

• Stream deposition zone sediment C/N ratio reflects runoff sediment C/N ratio.

• Agriculture affects stream via altered food quality and sediment oxygen demand.

Abstract Despite the widely acknowledged connection between terrestrial and aquatic

CHAPTER 2

• Agricultural land use effects are linked to lower C/N ratios and higher SOD levels.

CHAPTER 1

level.

deposition zones and the subsequent effects on benthic invertebrates remain poorly understood. The aim of this study was therefore to investigate the mechanisms by which runoff affects sediment composition and macroinvertebrates in deposition

CHAPTER 3

ecosystems, the contribution of runoff to the sediment composition in lowland stream

instream deposition zones from streams with different land use was chemically characterized and the biological effects were assessed at the species, community and ecosystem level. Runoff and deposition zone sediment composition as well as

CHAPTER 4

zones of lowland stream ecosystems. To this end, sediment from runoff and adjacent

stream deposition zone sediment C/N ratio reflected the respective runoff sediment composition. Deposition zones in the forest stream had a higher C/N ratio in comparison to the agricultural streams. Growth of Hyalella azteca and reproduction of

CHAPTER 5

biological responses differed clearly between forest and agricultural streams. The

worms suffered less mortality on the agricultural sediments containing only natural food. The forest stream deposition zones showed higher values for indices indicative of biological integrity and had a lower sediment oxygen demand. We concluded that

CHAPTER 6

Asellus aquaticus were higher on forest stream sediment, whereas chironomids and

species, community and ecosystem level via altered food quality (C/N ratio) and higher oxygen demand of the sediment.

Key words: deposition zone, runoff, C/N ratio, macroinvertebrates, sediment respiration, food quality.

37

CHAPTER 7

agricultural land use affects lowland stream ecosystem deposition zones at the

Chapter 3

1. Introduction The strong connection between terrestrial and aquatic ecosystems is a central issue in understanding ecological processes in freshwater environments (Allan, 2004; Palmer, 2010; Ward, 1998; Wiens, 2002). Stream ecosystems receive CHAPTER 1

allochthonous detritus, wood debris and sediment-bound chemicals from the adjacent terrestrial environment (Cummins and Klug, 1979; Jordan et al., 1997; Schriever and Liess, 2007). These allochthonous materials represent a key source of resources for stream food webs, supporting biodiversity and ecosystem services

CHAPTER 2

(Dodds, 2002; Bunn et al., 1999; Rosi-Marshall et al., 2016; Tank et al., 2010; Vannote et al., 1980; Webster et al., 1999). Yet, intense agricultural activities may lead to a lower input of course particulate organic matter and to increased concentrations of nutrients in the receiving streams (Bernhardt et al., 2017; Collins and Anthony, 2008).

CHAPTER 3

This may cause changes in instream detritus and sediment quality (Allan, 2004; Ekholm and Krogerus, 2003; MacDonald et al., 2001; Rabení et al., 2005), which is posing pressure on freshwater ecosystems worldwide (Leal et al., 2016; Wood et al., 2005).

CHAPTER 4

Once allochthonous material reaches a stream, it may partly accumulate in deposition zones (Callisto and Graça, 2013; Pusch et al., 1998; Haan et al., 1994; Golladay, 1987). Previous studies argued that alterations in the input of fine particles in stream deposition zones often lead to changes in the amount and type of organic

CHAPTER 5

matter, nutrient dynamics (Jordan et al., 1997; Stelzer et al., 2014), oxygen concentration (Jones et al. a, 2012) and the presence of potentially toxic substances (Jones et al. a, 2012; Larsen and Ormerod, 2010). Due to these changes, organisms inhabiting sediment deposition zone, such as benthic invertebrates, are confronted

CHAPTER 6

with altered food quality (Graham, 1990; Jones et al. a, 2012; Lenat and Crawford, 1994; Parkhill and Gulliver, 2002; Rowe and Dean, 1998), and physico-chemical conditions, such as oxygen concentration (Larsen and Ormerod, 2010; McDonald et al., 1991; Zweig and Rabeni, 2001; Von Bertrab et al., 2013).

CHAPTER 7

Despite the well documented qualitative effects of land use on stream ecosystem structure and functioning (Jones et al. a, 2012; Rabení et al., 2005; Schriever and Liess, 2007), the contribution of altered runoff to sediment composition in deposition zones and the subsequent effects on benthic invertebrates still remains poorly understood (Bernhardt et al., 2017; Larsen et al., 2009; (Kefford et al., 2010); Larsen and Ormerod, 2010; Von Bertrab et al., 2013; Zweig and Rabeni, 2001; Allan et al., 1997). This knowledge gap is even greater in lowland streams, where the runoff 38

The landscape drives the stream

from the surrounding land may be less frequent, but more intense due to the accumulation of high amounts of nutrients on the upper layer of the soil in flat areas (Stieglitz et al., 2003), leading to accumulation of contaminated material in stream by which runoff affects sediment composition and macroinvertebrates in deposition zones of lowland stream ecosystems. We hypothesized that land use specific runoff substantially affects deposition zone sediment composition and benthic ecosystem

CHAPTER 1

deposition zones. The aim of this study was therefore to investigate the mechanisms

hypothesis, sediment from runoff and adjacent instream deposition zones from streams with different land use was characterized chemically and the biological effects were assessed at the species (whole sediment bioassay), community (macroinvertebrate community composition) and ecosystem level (sediment oxygen

CHAPTER 3

demand).

CHAPTER 2

structure and functioning by changing food quality and oxygen availability. To test this

2. Materials and methods

This study was conducted in three tributaries of the Hierden stream (52° 23′ N, 5° 41′ O) in the Netherlands, (Fig. 1). The Hierdense stream catchment is characterized by sandy soils and a slope of 1.3 m/km (Klein and Koelmans, 2011). The

CHAPTER 4

2.1 Study area

downstream. The three selected stream are no more than four kilometers apart from each other, maintaining similar climatic and geological conditions. However, the intense human occupation in this relatively small catchment created a patchy

CHAPTER 5

headwater is surrounded by agricultural areas followed by a forested area

using the topographic map from the Kadaster (https://www.kadaster.nl) and confirmed in the field (Table 1). The catchment of the forest stream was dominated by deciduous and coniferous forest (98%); the grass stream was surrounded mainly by fertilized grasslands used for animal grazing (50%) and urban areas (31%); and the crop stream was surrounded by non-perennial fertilized crop fields (36%) and urban areas (31%) (Table 1).

39

CHAPTER 7

For each stream, the cover percentages of land use types were estimated

CHAPTER 6

landscape formed by diverse land uses.

Chapter 3

CHAPTER 1 CHAPTER 2 CHAPTER 3 CHAPTER 4 CHAPTER 5

Figure 1: The Hierden stream catchment and the sampling sites, based on the topographic map of the Kadaster [1:25.000 scale] at RD new projection, created using ArcMapR. Forest, grass and crop are the tree studied streams catchments.

CHAPTER 6 CHAPTER 7 40

The landscape drives the stream Table 1: Surface cover (Km2) and percentage of the major land use types in each of the three catchments.

0.00

0.00

0.01 (2%)

0.70

0.09 (4%)

1.01 (50%)

0.30 (15%)

0.64 (31%)

2.03

Crop

0.01 (4%)

0.12 (30%)

0.14 (36%)

0.12 (31%)

0.39

In each of the three lowland streams (flow velocity and depth, respectively in: forest 0.097 m/s ± 0.08 m/s, 11cm ±3; grass 0.111 m/s ±0.005 m/s, 24 ±3; and crop 0.091 m/s ± 0.003 m/s, 12 cm ±1) a downstream sampling site was selected (Fig. 1) to collect sediment from runoff and instream deposition zones. The runoff was sampled adjacent to the stream in the forest, the grasslands and the crop fields respectively, representing the dominant land use surrounding the sample site (Table 1). In each stream, a 15-meter-long stretch was selected in order to estimate substrate cover percentages according to Hering et al. (2003) (Table 2). Additionally, deposition zones were identified, defined as deeper areas where current velocity was low and where fine particulate organic matter (FPOM) accumulated, quantified based on Hering et al.

(2003).

Table 2: Substrate cover percentage estimates per sampling site over a 15-meters long stretch.

Psammal Sample Akal Submerged Emergent Xylal (sand, Algae CPOM FPOM site (gravel) macrophytes macrophytes (wood) mud) Forest

9

25

0

0

1

15

10

50

Grass

1

3

40

45

0

0

1

10

Crop

4

10

33

5

30

0

3

15

2.2 Runoff and deposition zone sediment composition Sediment from runoff was collected simulating soil erosion by wash (Bryan, 1974), flushing the soil with demineralized water (5 to 6 L) over an area of 283 cm 2 by pouring water from a container vertically on the soil of the river bank. Per site, five replicate runoff sediment samples were taken. Water and sediment were collected in 3L glass bottles and stored in a refrigerator at 4°C for about 15 hours, decanted and the remaining particles were analyzed.

From each stream deposition zone, the 2-cm top layer of the sediment was sampled using an acrylic core and a scaled core-cutter (Uwitec). Five replicate 41

CHAPTER 2

0.69 (98%)

Grass

CHAPTER 3

Forest

CHAPTER 4

Total (Km2)

CHAPTER 5

Urban (Km2)

CHAPTER 6

Crop (Km2)

CHAPTER 7

Grass (Km2)

CHAPTER 1

Land use Forest (Km2)

Stream

Chapter 3

sediment samples were collected per site for chemical analysis, freeze-dried, sieved over a 2 mm sieve and ball-milled for five minutes at 400 RPM. For the bioassays, five replicate sediment samples per site were first frozen at -20°C for two days and thawed at 4°C for a period of three to four days.

CHAPTER 1

2.2.1 Chemical analyses Carbon (C) and nitrogen (N) concentrations were determined using an elemental analyzer (Elementar Vario EL, Hanau, Germany). Phosphorus was

CHAPTER 2

determined by first igniting one to two grams of sediment at 500°C for 16h, after which the remaining sediment was extracted with 0.5M sulfuric acid and finally, total orthophosphate content was determined by the colorimetric molybdenum blue method (Murphy and Riley, 1962). The inorganic phosphorus (IP) corresponds to the

CHAPTER 3

orthophosphate fraction determined from unburned samples, according to the method described by Murphy and Riley (1962). Organic phosphorus (OP) was calculated by subtracting inorganic from total orthophosphate. The organic matter (OM) content of the sediment was measured by loss-on-ignition. After overnight drying at 105 °C, the sediment was weighted using a precision scale (0.1 mg) before

CHAPTER 4

and after burning at 550°C for 16 hours.

2.3 Biological analyses

CHAPTER 5

2.3.1 Sediment bioassays To measure the chronic (sub)lethal biological effects of the sediment samples at the species level, five benthic invertebrate species, Asellus aquaticus, Chironomus riparius, Hyalella azteca, Lumbriculus variegatus and Sericostoma personatum were

CHAPTER 6

tested in a series of whole sediment bioassays. There were five replicates per treatment, each replicate consisting of a 150 ml jar containing a ratio of 4:1 local stream water to sediment. The experiments were started by introducing ten (five for S. personatum) specimens of a single test species per replicate. The experiments were started with juvenile A. aquaticus (<2.5 mm), first instar (aged ≤24h) C. riparius larvae

CHAPTER 7

and juvenile H. azteca (<3.3 mm). Lumbriculus variegatus (0.3 mg ± 0.07 mg dry weight) consisted of juvenile individuals of similar size, and S. personatum larvae (12.6 mg ± 3.6 mg dry weight) were similar sized individuals of unknown instar. The test species originated from the University of Amsterdam's in-house laboratory cultures, except for S. personatum that was collected from a reference site (Springendal stream) and acclimatized for one week to laboratory conditions. The test jars were kept at 20ºC, continuously aerated and maintained under a 16:8 light:dark regime for

42

The landscape drives the stream

a period of 28 days in a climate room. The controls contained artificial sediment made according to OECD guideline 218 (OECD, 2004), modified by Marinković et al. (2011).

The bioassay with C. riparius was fed according to Marinković et al. (2011); for S. stream water) and 0.5 mg fish food/larva/day for a period of 28 days (mixture of Trouvit - Trouw, Fontaine-les-Vervins, France and Tetraphyll - Tetrawerke, Melle, Germany in a ratio of 20:1) were added at the onset of the experiment. Seven days

CHAPTER 1

personatum, approximately 1.5 g incubated wet oak leaves (12 days incubation in

natural sediments, the bioassay with L. variegatus and an additional test with C. riparius did not receive food. Conductivity, dissolved oxygen, pH and temperature were checked prior to the experiment, and measurements were repeated weekly.

Ammonia levels were checked at the beginning and at the end of the experiment.

After 28 days, the bioassays were terminated and the sediment was sieved (mesh size 500 mm). The end-points were survival and emergence for C. riparius; survival, growth and reproduction for A. aquaticus and H. azteca; survival for L. variegatus; and survival and growth for S. personatum. Survival was defined as the percentage of alive individuals per jar; emergence was the percentage of adult midges per jar; reproduction was the mean number of juveniles per jar; and, finally, growth was the individual final length or weight subtracted from the initial average length or weight per jar.

2.3.2 Community analysis Macroinvertebrates were sampled from stream deposition zones by a Surber sampler (625 cm2; mesh size: 0.25 mm). The collected organisms were sorted within

CHAPTER 3

to each jar at the onset of the experiment. To evaluate the carrying capacity of the

CHAPTER 4

experiment. For H. azteca, 5% of sediment dry weight ground Urtica dioica was added

CHAPTER 5

administrating approximately 1.5 g incubated oak leaves at the onset of the

CHAPTER 6

mg fish food/larva/day for a period of 14 days. A. aquaticus were fed by

CHAPTER 2

after the start of the test 1.5 g incubated oak leaves were added and after 14 days 0.5

(number of taxa), Shannon–Wiener diversity index and the percentage of Ephemeroptera, Plectoptera and Trichoptera (EPT) individuals and the SPEAR index (Liess and Von Der Ohe, 2005) were calculated. Additionally, the saprobity and the relative abundance of functional feeding groups (Moog, 1995) were derived from the autecological database for freshwater organisms, version 7.0, accessed on 28.03.2017 (www.freshwaterecology.info).

43

CHAPTER 7

48 hours and preserved in 70% ethanol for later identification. Species richness

Chapter 3

2.3.3 Ecosystem level At the ecosystem level, the sediment oxygen demand (SOD) was measured.

SOD of five replicate sediment cores per site was determined as described by Belanger (1980), with slight modifications: the undisturbed sediment cores were kept CHAPTER 1

at 20ºC in dark and saturated with air immediately after sampling. Next, the dissolved oxygen concentrations were measured after 1, 2, 9 and 24 hours with a portable meter (HQ440d HACH). Finally, SOD was calculated according to Rong et al. (2016).

CHAPTER 2

2.4 Statistics Deposition zone sediment composition, biological effects and runoff sediment composition non-transformed data were tested separately using one-way analysis of variance (ANOVA), followed by a Tukey post hoc test (R-package stats). In

CHAPTER 3

the cases where the conditions of data normality (Shapiro–Wilk test) and homogeneity of variances (Levene’s test) were violated, differences between means were calculated using the non-parametric Kruskal–Wallis test, followed by a MannWhitney pairwise comparisons (Bonferroni corrected: 0.05/2, a = 0.025) to compare the 3 streams (R-package multcompView).

CHAPTER 4

The effect of environmental variables on macroinvertebrate communities was analyzed by using a Canonical Correspondence Analyses (CCA), CANOCO for Windows version 4.55 (ter Braak and Smilauer, 2002). All nine sediment chemical

CHAPTER 5

parameters measured in both the deposition zone and the runoff were included in the analysis. The significance of the relation between the macroinvertebrates and the environmental parameters was evaluated using a Monte Carlo permutation test (999 permutations, p<0.05). In the bioassays, the laboratory control treatments performed

CHAPTER 6

for test validation (OECD, 2004) were not included in the statistical test.

3. Results 3.1 Runoff sediment composition

CHAPTER 7

In runoff sediment, organic matter percentage decreased significantly (p<0.05) from forest (62% ± 11%) to grasslands (44% ± 2%) to crop fields (25% ± 8%) (Fig. 2A). C/N ratio was significantly (p<0.05) higher in forest runoff sediment (17 ± 1) than in the runoff sediment from the two agricultural sites (14 ± 0.5 and 14 ± 1, grass and crop respectively) (Fig. 2B). Inorganic phosphorus (IP) was significantly (p<0.05) higher in crop runoff (19 mmol/Kg ± 5 mmol/Kg) than in grass (10 mmol/Kg ± 6 mmol/Kg) and forest runoff (3 mmol/Kg ± 0.5 mmol/Kg) (Fig. 2C). Organic phosphorus (OP) was not significantly (p<0.05) different between sampling sites (Fig. 2D).

44

The landscape drives the stream

The OP concentration (15 mmol/Kg ± 9 mmol/Kg) was significantly (p<0.05) higher than the IP concentration (3 mmol/Kg ± 0.5 mmol/Kg) in forest runoff, but the opposite was observed in crop runoff, where the OP concentration was significantly mmol/Kg).

A

B

a

a

b

b c

b

C

D

CHAPTER 3

CHAPTER 2

b

CHAPTER 1

(p<0.05) lower (8 mmol/Kg ± 2 mmol/Kg) than the IP concentration (19 mmol/Kg ± 5

Figure 2: Runoff sediment composition: particulate organic matter percentage (OM %) (A), carbon/ nitrogen ratio (C/N ratio) (B); Inorganic phosphorus (IP) (C) and organic phosphorus (OP) (D). The boxes indicate the first to third quartile. The bottom, middle and top line indicate the minimum, median and maximum values. Treatments labelled with different letters indicate a significant difference between the means (p<0.05, analyses of variance followed by multiple comparison test).

3.2 Deposition zone sediment composition Percentage of organic matter in sediment deposition zones did not differ significantly (p>0.05) between forest and agricultural streams. The C/N ratio was significantly (p<0.05) higher in forest stream sediment (17.5 ± 0.4) compared to both agricultural sites (15.2 ± 0.3 and 14.6 ± 1, respectively) (Fig. 3B), fully reflecting the runoff sediment composition. Organic and inorganic phosphorus did not differ significantly (p>0.05) between sampling sites (Fig. 3C, D). Finally, the IP concentration was higher in runoff (4.1 ± 3.9; 5.9 ± 1.3; 2.1 ± 2.1, forest, grass and crop respectively) 45

CHAPTER 5

a a

CHAPTER 6

a

CHAPTER 7

a

CHAPTER 4

ab

Chapter 3

than in deposition zones (3.1 ± 0.5; 12.6 ± 8.6; 17.4 ± 3.6, forest, grass and crop respectively), except for forest.

A

B

a

CHAPTER 1

b

CHAPTER 2

a

a

b

a

C

D

CHAPTER 3

a a a

a

a

a

CHAPTER 4 CHAPTER 5

Figure 3: Deposition zone sediment composition: particulate organic matter percentage (OM %) (A), carbon/nitrogen ratio (C/N ratio) (B), Inorganic phosphorus (IP) (C) and organic phosphorus (OP) (D). The boxes indicate the first to third quartile. The bottom, middle and top line indicate the minimum, median and maximum values. Treatments labelled with different letters indicate a significant difference between the means (p<0.05, analyses of variance followed by multiple comparison test).

3.3 Biological effects CHAPTER 6

3.3.1 Bioassays Control survival for A. aquaticus, H. azteca, S. personatum and C. riparius was higher than 80%, meeting the validity criteria of the tests (OECD, 2004) (Table 3).

CHAPTER 7

Moreover, there was no treatment-related effect on survival. Control survival of C. riparius and L. variegatus without additional food was obviously very low due to starvation. These experiments did show, however, that both the chironomid and the worm suffered significantly (p<0.05) less mortality on the agricultural sediments than on the forest sediment.

Considering the chronic sublethal end points, growth of H. Azteca and reproduction of A. aquaticus was significantly (p<0.05) higher on the forest stream 46

The landscape drives the stream

sediment than on the two agricultural sediments. In contrast, emergence of C. riparius in the treatment without additional food was significantly (p<0.05) higher on the two

Table 3: Survival (%), growth (mm or mg), reproduction (number of offspring) and emergence (number of individuals) of benthic invertebrate species. Different letters indicate a significant difference between the means in landscape types (p<0.05, analyses of variance followed by multiple comparison test).

Forest

Grass

Crop

Laboratory control

Asellus aquaticus

76 (±11)

84 (±13)

80 (±7)

82 (±24)

Hyalella azteca

94(±9)

86 (±15)

84 (±11)

90 (±10)

Sericostoma personatum

96(±9)

100(±0)

96(±9)

100 (±0)

Chironomus riparius

90.9 (±13)

69 (±40)

82 (±29)

92.7 (±16)

Chironomus riparius _no food

54 (±11) a

67 (±15) b

74 (±34) b

CHAPTER 1

agricultural sediments than on the forest sediment.

Asellus aquaticus (mm)

6.4 (±0.7)

6.4 (±1.2)

6.1 (±0.8)

4.8 (±0.5)

Hyalella azteca (mm)

4.6 (±1.7)a

2.2 (±0.4) b

2.4 (±0.4) b

3.8 (±0.4)

Sericostoma personatum (mg)

20 (±3.4)

19.4 (±3)

17 (±1.6)

16 (±2.4)

Asellus aquaticus

17.4 (±18) a

2.2 (±5) b

0 (±0) b

0 (±0)

Hyalella azteca

1 (±1)

0.5 (±0.5)

0 (±0)

1.2 (±0.4)

Chironomus riparius

91 (±13)

69 (±40)

82 (±29)

93 (±16)

Chironomus riparius _no food

0 (±0) a

24 (±15) b

16 (±12) a

0 (±0)

Reproduction (number of offspring)

Emergence (number of individuals)

3.3.2 Macroinvertebrate community composition Macroinvertebrate community composition differed strongly between land use type (Fig. 4A) in terms of richness, functional feeding groups (FFG) and saprobity categories.

All indices of good ecological quality scored higher for forest (Table 4).

Richness and diversity were significantly (p<0.05) higher in the forest stream community than in the agricultural streams communities. EPT individuals as well as sensitive species according to the SPEAR classification were present only in the forest stream.

47

CHAPTER 3

24 (±32)

Growth

CHAPTER 4

114(±21)

2 (±4)

CHAPTER 5

100 (±58)

b

CHAPTER 6

24 (±32)

b

CHAPTER 7

Lumbriculus variegatus_no food

a

CHAPTER 2

Survival (%)

Chapter 3 Table 4: Mean (n=5) ± standard deviation (sd) of macroinvertebrate community indices. EPT is the relative abundance of Ephemeroptera, Plecoptera and Trichoptera individuals; SPEAR is the number of species that are classified as “at risk” (Liess and Von Der Ohe, 2005). Different letters indicate a significant difference between the means (n=5 ± sd) (p<0.05, analyses of variance followed by multiple comparison test).

CHAPTER 1 CHAPTER 2

Richness

Forest 17 (±6) a

Grass 9 (±5) b

Crop 10 (±2) b

EPT (%)

12 (±0.1) a

0b

0b

2.03 (±0.3) a

1.4 (±0.74)ab

1.4 (±0.4)b

0b

0.2 (±0.4)b

34.02 (±25.6) a

38.8 (±7.6) a

Shannon-Winner diversity

a

SPEAR

2.2 (±1.6)

Alpha and polysaprobic (%)

23.1 (±3.7) a

For community composition, the similarity (Jaccard index) between grass and

CHAPTER 3

forest was 26%, but only 12% for crop and forest. Even between the two agricultural sites, similarity was low (22%). In forest, the evenness among different species was higher than grass, dominated by Chironomus sp., and crop dominated by Proasellus banyulensis and Stylaria lacustris. All FFG and saprobity categories were present at the

CHAPTER 4

three locations, but in different proportions and therefore the Jaccard index was not applied. Macroinvertebrate species indicative of a high level of saprobity (alpha and polysaprobic) and a lower diversity and evenness of functional feeding groups occurred in the agricultural streams (Fig. 4B, C). Active filter feeders were more common and parasites occurred only in the forest stream.

CHAPTER 5 CHAPTER 6 CHAPTER 7 48

Figure 4: Relative abundance of macroinvertebrate taxa (A), functional feeding groups (B) and saprobity categories (C) at the three sampling sites.

CHAPTER 6

CHAPTER 5

CHAPTER 4

CHAPTER 3

CHAPTER 2

CHAPTER 1

The landscape drives the stream

Sediment oxygen demand was significantly (p<0.05) lower in the deposition zones in the forest stream compared to both agricultural sites (Figure 5).

49

CHAPTER 7

3.3.3 Sediment oxygen demand

Chapter 3

b b

CHAPTER 1

a

CHAPTER 2 CHAPTER 3

Figure 5: Sediment oxygen demand over 24 hours. The boxes indicate the first to third quartile.

The bottom, middle and top line indicate the minimum, median and maximum values.

Treatments labelled with different letters indicate a significant difference between the means (p<0.05, analyses of variance followed by multiple comparison test).

3.3.4 Canonical correspondence analysis The CCA of macroinvertebrate community composition and environmental

CHAPTER 4

parameters shows that axis 1 accounted for 31.2% of the variation explained and axis 2 for another 19.1%, while the first four CCA axes jointly accounted for 74.6%. The CCA ordination plot shows that macroinvertebrate species in agricultural streams, were separated from those in forest streams (Fig. 6A). Both agricultural sites were

CHAPTER 5

positively related with a higher SOD, while streams in grassland also related to higher concentrations of inorganic phosphorus in deposition zones and streams in cropland to higher concentrations of inorganic phosphorus in runoff particles. Conversely, streams in forest related to higher C/N ratioâ&#x20AC;&#x2122;s and percentage of organic matter in

CHAPTER 6

both runoff particles and deposited material.

The CCA of macroinvertebrate FFG and environmental parameters shows that axis 1 accounted for 47.9% of the variation explained, axis 2 for another 34.2%

CHAPTER 7

and the first four CCA axes jointly for 98.5%. The FFG CCA ordination plot (Fig 6B) is similar compared to the community composition plot (Fig. 6A). The major difference is that the sites in cropland are positioned in the diagram apart from those in grassland and forest. Here the streams in cropland are related to high SOD and concentrations of inorganic phosphorus in runoff particles.

The ordination analyses confirmed the results described above for C/N ratio, IP, SOD and macroinvertebrate community composition, where the forest stream was clearly distinct from the agricultural sites.

50

A

CHAPTER 7

CHAPTER 5

CHAPTER 4

-1.5 2.5

51

CHAPTER 3

31.2 %

CHAPTER 6

-2.0

CHAPTER 2

CHAPTER 1

19 %

3.0

The landscape drives the stream

1.0

34.2 %

Chapter 3

CHAPTER 1 CHAPTER 2 CHAPTER 4

-0.4

CHAPTER 3

47.9 %

-0.6

1.0

CHAPTER 5

Figure 6: CCA biplots for data ordination of environmental variables with macroinvertebrates species (A) and functional feeding group (B) in forest, grass and crop streams.

CHAPTER 6

4. Discussion Our results showed that the composition of runoff and instream deposition zone sediment is land use specific and that agricultural activities affect stream ecosystems at the species, community and ecosystem level. To evaluate the mechanisms by which runoff affects sediment composition and therewith

CHAPTER 7

macroinvertebrates in lowland streams, below we discuss deposition zone sediment characteristics and the corresponding biological effects.

4.1 The contribution of runoff to deposition zone sediment composition Several authors attributed shifts in OM composition in streams to storm water runoff (e.g. Imberger et al., 2014; Wang et al., 2001; Withers and Jarvie, 2008).

This is especially the case in agricultural catchments (Allan et al., 1997; Burcher and Benfield, 2006), because the nutrients and pollutants concentrated in the upper 52

The landscape drives the stream

horizons of the soils can be easily washed off from land to streams by runoff (Cai et al., 2015; Lewis and Grimm, 2007; Vidon et al., 2010). Our analyses of the terrestrial runoff contribution to the sediment composition in the deposition zones of the terms of OM percentage, C/N ratio and IP. Forest runoff sediment contained the highest OM percentage and C/N ratio and the lowest IP concentration, due to the input of forest tree leaves (Vidon et al., 2010; Withers and Jarvie, 2008). The

CHAPTER 1

streams demonstrated that runoff sediment showed a land use specific signature in

sediment. Focusing on orthophosphate, we showed that IP was indeed much higher in agricultural runoff, especially in the crop field, which was to be expected in agricultural systems with artificial fertilizer inputs (Ekholm and Krogerus, 2003; Oyewumi et al., 2017; Withers and Jarvie, 2008). Yet, for IP there was no deposition zone-runoff relationship, which may be explained by the rapid P uptake, turnover and regeneration times in streams (Mulholland et al., 1997, 1985), as a result of a combination of biotic and abiotic assimilation processes during downstream transport (Wetzel, 2001; Withers and Jarvie, 2008).

OM percentage was fifteen to nineteen times higher in runoff than in

CHAPTER 3

al., 1999), in contrast to phosphorus in the orthophosphate form, bound to runoff

CHAPTER 4

well established (e.g. Meyer and Likens, 1979; Wetzel, 2001; Lijklema, 1993; Reddy et

CHAPTER 2

importance of land use for dissolved and pore water phosphorus concentrations is

deposited in instream sediment are not representative of the substances washed in from the surrounding land (McCorkle et al., 2016) and because OM in deposition zones may be altered by temperature, light, upstream particle influx and

CHAPTER 5

deposition zone sediments in all studied streams, demonstrating that the materials

results showed no one to one correlation between deposition zones and runoff sediment composition, except for C/N ratio.

C/N ratio was higher in forest compared to agricultural runoff, indicating the higher carbon and lower nitrogen influx in forest streams. In all studied streams, the C/N ratio in deposition zones was very similar to that in runoff sediment. C/N ratio was therefore the only stream sediment parameter that fully reflected runoff sediment composition, in agreement with McCorkle et al. (2016), suggesting that runoff sediment might play an import role as a source of carbon and nitrogen in deposition zones.

53

CHAPTER 7

Thus, although Golladay (1987) reported significant FPOM inputs during storms, our

CHAPTER 6

decomposition (Imberger et al., 2014; McCorkle et al., 2016; Mulholland et al., 1985).

Chapter 3

Overall, the present study thus showed that the contribution of runoff to deposition zone sediment composition is parameter-specific (C, N, OM, IP). C/N ratio may represent a good finger print from terrestrial input in lowland streams (Bunn et al., 1999; Hamilton et al., 1992), which could be further improved by particle size CHAPTER 1

determination.

CHAPTER 2

differed specifically in OM content and C/N ratio. In the forest stream, OM percentage

4.2 Deposition zone characteristics The sediment composition in the deposition zones of the studied streams and C/N ratio were higher than in the agricultural streams. Several studies have suggested that lower C/N ratios indicate the influx of autochthonous material, whereas higher values are related to allochthonous-derived carbon (Wetzel, 2001;

CHAPTER 3

Hunt et al., 2012; Kendall et al., 2001; Leigh et al., 2010). This could well be the case in the present study, where the forest stream received more allochthonous carbon, such as wood and deciduous tree leaves (Bilby, 1981; Meyer et al., 1998), while the agricultural streams were characterized by the predominance of autochthonous carbon from instream sources such as algae and macrophytes. We concluded that

CHAPTER 4

instream deposition zone sediment composition is land use specific and that the C/N ratio showed the most pronounced differences between forest and agricultural sites.

4.3 Biological effects

CHAPTER 5

Agricultural land use was not only reflected by a lower C/N ratio, but also by higher SOD levels. According to Imberger et al. (2014) and Pusch et al. (1998) alterations in C/N ratios and microbial detritus processing have the potential to impact ecosystem respiration, nutrient processing and water quality. The SOD in the

CHAPTER 6

agricultural streams was comparable to that in eutrophic water bodies (Sommaruga, 1991) and in water with low dissolved oxygen concentrations (Chau, 2002; Liu and Chen, 2012; Rong et al., 2016) and showed that the respiration rate in agricultural stream sediments was higher than in the forest sediment. Moreover, it has been

CHAPTER 7

documented that SOD strongly influences the dissolved oxygen budgets in the overlying water (e.g. Boynton and Kemp, 1985; Liu and Chen, 2012; Matlock et al., 2003), potentially affecting the benthic community (Larsen et al., 2011). The present study showed that land use affected benthic community composition and induced species-specific responses in bioassays. The forest stream showed higher values for all indices indicative of biological integrity than the agriculture sites, in agreement with e.g. Allan et al. (1997); Lammert and Allan (1999); Wang et al. (2001). The higher richness, biodiversity and EPT index in the forest stream deposition zones was related 54

The landscape drives the stream

to the higher C/N ratio and lower SOD. Von Bertrab et al. (2013) also reported a higher occurrence of EPT species at sites with a high C/N ratio, which, together with

quality, we also analysed functional feeding group composition (FFG). We observed that the FFG diversity and evenness was higher in the forest stream, in agreement with Von Bertrab et al. (2013), who showed that a lower food quality affected active filter feeders and grazers most. Moreover, higher diversity of FFG allows differential energy flows through the benthic food web, which may lead to higher food web stability (Rooney and McCann, 2012).

CHAPTER 2

Since the substantial differences in C/N ratio hint at differences in food

CHAPTER 1

oxygen availability, explained benthic invertebrate community composition.

especially during the night. Therefore, the differences in SOD between the forest and the agricultural sites suggest that community composition may also be explained by species specific sensitivities to oxygen demand in the sediment. Analysing the relative

CHAPTER 3

Higher SOD may decrease the dissolved oxygen concentration in the water,

than one quarter of macroinvertebrate taxa present at the agricultural sites are resistant to low oxygen concentrations (alpha and polysaprobic), in line with the higher sediment oxygen demand at these sites. In contrast, the EPT species, generally

CHAPTER 4

abundance of macroinvertebrates according to saprobity levels showed that more

were only present in the forest stream with the lower SOD. The differences in community composition between sites matched very well

CHAPTER 5

sensitive to low oxygen concentrations (Collier et al., 1998; Von Bertrab et al., 2013)

higher, whereas L. variegatus and C. riparius survived better on the agricultural sediment containing only natural food with a low C/N ratio. This result can likely be explained by the variance in food intake and digestion efficiency between macroinvertebrate species (Cammen, 1980; Cummins and Klug, 1979). H. azteca and A. aquaticus are selective feeders with preferences toward a higher food quality (Cammen, 1980; Graรงa et al., 1993; Wang et al., 2004). In contrast, L. variegatus and C. riparius can ingest bacteria at high rate (Brinkhurst and Chua, 1969; Baker and Bradnam, 1976) and have the ability to compensate for reduced food quality by increasing ingestion rate (Cammen, 1980; Cummins and Klug, 1979). In conclusion, the present study demonstrated that agricultural land use affected benthic species growth and reproduction, as well as macroinvertebrate community composition via 55

CHAPTER 7

the forest stream sediment growth of H. azteca and reproduction of A. aquaticus was

CHAPTER 6

with the species specific responses in the whole sediment bioassays, showing that in

Chapter 3

altered food quality and oxygen demand in the sediment. These effects are partly driven by the C/N ratio (food quality), and partly by the degradability of the runoff sediment (sediment oxygen demand), both contributing to the observed biological effects. Thus, the present study indicated that agricultural land use affects lowland CHAPTER 1

stream ecosystems via altered food quality and oxygen demand in the sediment.

CHAPTER 2

Acknowledgements: First and most we thank the students Tom Theirlynck, Toon Driessen, Joana Postal Pasqualini. We thank professor Erik Cammeraat for his advices in sampling runoff; laboratory technicians Chiara, Joke, Leo, Rick; and the water manager Christian for field work logistic help.

CHAPTER 3 CHAPTER 4 CHAPTER 5 CHAPTER 6 CHAPTER 7 56

Chapter 4

Chapter 4 Land use affects lowland stream ecosystems through dissolved oxygen regimes Paula C. dos Reis Oliveira Harm G. van der Geest Michiel H. S. Kraak Piet F. M. Verdonschot

Scientific Reports, under review

Author Contributions: PCRO, PFMV, HG and MK designed the experiment. PCRO conducted the experiment. PCRO and HG analysed most of the data,and wrote most of the manuscript together with PFMV and MK. PFMV and MK advised on practical issues during the course of the experiment and data processing and contributed to editing and revising draft versions of the manuscript.

58

The landscape drives the stream

Abstract To disentangle the land use specific effects of fine sediment input on lowland stream ecosystems and to unravel the underlying mechanisms the aim of the present functioning of lowland stream ecosystems. To this purpose, twenty streams surrounded by five different land use types were selected and sediment and water quality parameters were measured, diel dissolved oxygen regimes were recorded, and

CHAPTER 1

study was to assess the impact of catchment land use on the structure and

macrophytes or FPOM, while woody debris and CPOM were only found in forest streams. The temporal variation in oxygen concentrations followed the natural lightdark regime in forest and grassland streams, with the highest fluctuations in grassland streams where also the highest GPP was observed. Particularly in WWTP streams, an irregular oxygen pattern and a high sediment oxygen demand was observed, related to the fluctuating discharge of WWTP effluent. Concerning macroinvertebrate community composition, there was a dominance of Chironomus sp., Oligochaeta and Gastropoda in cropland and WWTP streams, while Plecoptera and most Trichoptera only occurred in forest and extensive grassland streams. These results show that anthropogenic catchment land use type alters fine particulate organic matter substrate cover, sediment organic matter content and sediment nutrient concentrations. Subsequently, this impacted instream metabolic processes, such as primary production and respiration and sediment oxygen demand, leading to highly

CHAPTER 3

higher in forest streams. In impacted streams, the substrates were covered by

CHAPTER 4

concentrations were higher in agricultural streams, and the sediment C/N ratio was

CHAPTER 5

concentrations were higher in WWTP streams, water turbidity and chlorophyll

CHAPTER 2

macroinvertebrate community composition was determined. Dissolved nutrient

differences in macroinvertebrate community composition. We therefore argue that land use specific impacts on lowland streams, exerted via fine sediment accumulation in deposition zones, stress the importance of including the catchment scale in

CHAPTER 6

different oxygen regimes in the streams, which in turn were reflected by large

Key words: Catchment land use; ecosystem functioning; stream metabolism; SOD; deposition zones; sedimentation; macroinvertebrates

59

CHAPTER 7

ecological stream quality assessments.

Chapter 4

1. Introduction Catchment land use strongly defines the ecological functioning of stream ecosystems (Castro et al., 2018; Englert et al., 2015; Frainer and McKie, 2015; Hladyz et al., 2011; Masese et al., 2017; Riipinen et al., 2010). The most studied land use CHAPTER 1

impacts on stream ecosystems are related to effects on hydromorphology (Feld, 2004; Hering et al., 2004; Kail et al., 2009; Turunen et al., 2016; Verdonschot, 2009; Villeneuve et al., 2018), water quality (Dahm et al., 2013; Jarvie et al., 2008; Johnson et al., 2006; Niyogi et al., 2004) and riparian habitats (Ferreira et al., 2014; Hering et

CHAPTER 2

al., 2006; Schmera et al., 2012; Turunen et al., 2018), especially in high gradient streams. However, lowland streams might be even more affected by catchment land use type, because alluvial plains have been historically impacted by agricultural activities and urbanization worldwide.

CHAPTER 3

One of the important stressors in the terrestrial-aquatic interaction is the input of fine sediment into streams (Guan et al., 2017). These fine sediments accumulate in deposition zones like stream bed depressions and pools (James, 2010; Zhang et al., 2017), especially in streams with low current velocities such as lowland

CHAPTER 4

streams (Naden et al., 2016). Fine sediments increase turbidity (Sutherland et al., 2002), decrease underwater light availability for primary producers (Quinn et al., 1992) and reduce available streambed habitats for aquatic invertebrates (Burdon et al., 2013; Larsen et al., 2011; Ramezani et al., 2014; Wood and Armitage, 1997). In addition, changes in the physicochemical conditions of the streambed may lead to

CHAPTER 5

changes in nutrient dynamics (Weigelhofer et al., 2018), oxygen concentrations (Teufl et al., 2013) and biofilm assemblages (Battin et al., 2016; Johnson et al., 2009; Lear et al., 2013). Since land use determines the origin and nature of the inflowing material (Kellner and Hubbart, 2019) and the deposited particles (dos Reis Oliveira et al., 2018;

CHAPTER 6

Kronvang et al., 2013; Phillips, 1991), it is expected that the effects on stream functioning depend on the land use specific amount and composition of fine particles and nutrients entering the stream (FuĂ&#x; et al., 2017; Larson et al., 2019).To disentangle the land use specific effects of fine sediment input on lowland stream ecosystems and

CHAPTER 7

to unravel the underlying mechanisms, the analysis of key functional processes such as dissolved oxygen regime and stream metabolism (Bernot et al., 2010; Boulton et al., 1997; Odum, 1956; Triska et al., 1993; Williamson et al., 2008) should be combined with the study of structural parameters such as sediment and macroinvertebrate community composition (Buendia et al., 2013; Young et al., 2008), since the dissolved oxygen concentration directly affects the survival and fitness of aquatic organisms (Calapez et al., 2018; Fox and Taylor, 1955; Leitner et al., 2017; Pearson and Connolly, 2000). Moreover, the metabolic functioning of streams strongly 60

The landscape drives the stream

depends on the energy influx from the catchment, and also determines the downstream energy transport and export, thereby integrating ecological processes occurring at different scales (McTammany et al., 2007). macroinvertebrates (Connolly et al., 2004; Ding et al., 2016; Fox and Taylor, 1955) as well as the relationships between macroinvertebrate community composition and land use specific effects of the input of fine sediment have been well documented

CHAPTER 1

Although the impact of low dissolved oxygen concentrations on

characteristics, stream metabolism and macroinvertebrate community composition.

We hypothesised that different land use types result in differences in substrate composition and related physicochemical characteristics of stream deposition zones.

These changes in streambed characteristics were expected to affect stream metabolism and therewith diel dissolved oxygen regimes, which in turn affect macroinvertebrate assemblages. To test this hypothesis, twenty streams draining catchments characterized by five different land use types were selected and diel dissolved oxygen concentrations were recorded, sediment and water quality parameters were measured, and macroinvertebrate community composition was determined.

2. Material and methods 2.1 Study sites The present study was conducted under late summer conditions from September 20th until October 15th 2017, in twenty lowland streams in the Netherlands

CHAPTER 3

three complementary pillars by assessing water and sediment physico-chemical

CHAPTER 4

structure and functioning of lowland stream ecosystems. We based our study on

CHAPTER 5

the present study was therefore to assess the impact of catchment land use on the

CHAPTER 6

underlying these relationships remain poorly described (Allan et al., 2012). The aim of

CHAPTER 2

(Allan et al., 2012; Dahm et al., 2013; dos Reis Oliveira et al., 2018), the mechanisms

type, four replicate streams with similar morphological characteristics were selected (supplementary table S1). The land use types included forest areas, serving as natural reference sites (hereafter referred to as forest) and streams in areas with nonfertilized pasture (extensive grassland (EG)), fertilized pasture (intensive grassland (IG)), arable field (cropland) and streams receiving wastewater treatment plant effluent about every 15 minutes (WWTP). The selection criteria for the streams in the forest, grassland and cropland catchments were based on the percentage of surface covered (> 2/3) by the selected land use type, as indicated on the national Dutch land 61

CHAPTER 7

representing five common land use types (supplementary table S1). For each land use

Chapter 4

use map (LGN5) (Hazeu et al., 2011). WWTP streams were selected based on the presence of a sewage treatment plant (~50.000 people) outflow, no more than 250 m away from the selected stream stretch.

Stream width and depth were measured in a 20 m stretch in each replicate CHAPTER 1

stream. Mean width was calculated by measuring width every 2 m. Means stream depth and mean current velocity (electromagnetic current meter Valeport model 802) were measured and discharge was calculated at five points equally distributed along a transect, in three transects (upstream, middle and downstream) along the selected 20

CHAPTER 2

m stream stretch.

The field experiment lasted 48 h at each site, but because of logistic limitations, 25 days in total were needed to run the entire study. Each time that the 48 h oxygen measurements in the field were completed, water, sediment and

CHAPTER 3

invertebrate samples were taken before the field experiment was uninstalled. Below the methods are described in more detail.

2.2 Stream water quality In each stream, a water sample (1L) was collected in plastic bottles and

CHAPTER 4

stored at -20ºC just after sampling. Conductivity, pH (HQ440d HACH, portable multi sensor meter) and turbidity (Hach 2100Q meter) of all samples were measured in the laboratory at 20°C. A filtered (0.2 µm GFC filter) subsample was taken for ammonium (NH4), nitrate (NO3), nitrite (NO2) and phosphorus (PO4) measurements, analysed

CHAPTER 5

with a Skalar SAN++ segmented flow analyser packed with a 1074 twin needle autosampler, and software Flow Access v3. Dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) were analysed with a TOC-analyzer (Total Organic Carbon; Shimadzu, Japan).

CHAPTER 6

2.3 Sediment characteristics and substrate cover In each stream deposition zones were identified, defined as deeper areas where current velocity was lower (measured with electromagnetic current meter Valeport model 802) and where fine particulate organic matter (FPOM) accumulated,

CHAPTER 7

identified according Hering et al. (2003). In each stream, a sediment sample was taken from representative deposition zones by sampling the top 2 cm layer using an acrylic core. All samples were freeze-dried (CoolSafe 55-9 Pro) directly after sampling and subsequently analysed for sediment characteristics. Grain size distribution (Phi) was measured according to NEN 5753 (2006) and analysed following Wentworth (1922) and Blott and Pye (2001). Per stream a sediment subsample was ball-milled for organic matter content (OM), total carbon (TC), total nitrogen (TN), total phosphorus 62

The landscape drives the stream

(TP), organic phosphor (OP), inorganic phosphor (IP) concentrations and chlorophyll-a content (Chla) measurements. TC and TN were measured using an elemental analyzer (Elementar Vario EL, Hanau, Germany) and OM by loss of weight-on ignition of oven sets of roughly 0.80 g of ball-milled sediment per sample and igniting one of the duplicate samples at 500˚C for 16 hours. Afterwards, both burnt and unburnt samples were extracted using 0.5M of sulfuric acid from which the total phosphorus content

CHAPTER 1

dried (105°C) material at 550 °C for 16 hours. TP was determined by first weighing 2

(Murphy and Riley, 1962). Organic phosphorous (OP) was calculated by subtracting inorganic from total phosphorus. Sediment chlorophyll–a concentrations were quantified according to Porra et al. (1989) and Brito et al. (2009), and the respective concentrations were calculated using Lorenzen’s equation (Lorenzen, 1967). In each stream, substrate cover was estimated according to Hering et al (2003) in a twenty m stream stretch.

CHAPTER 3

corresponded to the phosphorus fraction determined from unburned samples

CHAPTER 2

was determined according to Murphy and Riley (1962). Inorganic phosphorous (IP)

In each stream, six Hobo U26-001 oxygen probes (Onset Computer Corporation) were installed just above the stream bed for continuous oxygen concentration and temperature measurements every five minutes over a period of 48

CHAPTER 4

2.4 Dissolved oxygen regime

installed twenty meters apart in the main stream, while four replicate probes were installed at the deposition zones (Supplementary Figure S1). Oxygen probes were installed in four replicate streams for a given land use type at the same day; after two

CHAPTER 5

h as recommended by Siders (2017) and Bott (2007). Two replicate probes were

measured. All oxygen probes were calibrated before installation in the laboratory using the air-saturation water approach according to the calibration tool in HOBOware®, and checked after retrieval in the laboratory by placing all probes at the

CHAPTER 6

days they were moved to the next land use type until all twenty streams were

the oxygen probes, acrylic plates (2 m length; 0.5 m height; 3 mm width) were installed parallel to the main flow path to better separate deposition zones from the main flow path. Small patches of macrophytes were removed when growing too close to the probe. In addition, to avoid drifting macrophyte parts and filamentous algae accumulating on the oxygen sensors, bamboo sticks were placed 30-50 cm upstream of the probes. Dissolved oxygen concentrations were converted to oxygen saturation percentages correcting for water temperature according to Wetzel and Likens (2000), to avoid variation in the oxygen regime measurement due to temperature differences 63

CHAPTER 7

same time in 100% saturated water for 3 hours. Three days prior to the installation of

Chapter 4

during the 25 days of the field experiment. From the oxygen time series, the daily fluctuations and average oxygen concentration per stream per land use type were calculated. In addition, cumulative frequency distributions of the oxygen saturation classes from zero to 180 percent (in steps of 5%) were calculated.

CHAPTER 1

2.5 Sediment oxygen demand For the determination of the sediment oxygen demand (SOD), four replicate undisturbed sediment acrylic cores (6 cm diameter) per stream were taken by digging

CHAPTER 2

about 10 cm of the sediment in the deposition zones and topping off the core completely with stream water. The sediment cores were kept at 20 °C in the dark (covered in aluminum folium) and the overlaying water was saturated with air immediately after sampling and closed. Next, dissolved oxygen concentrations were measured directly, after 24 hours and at least two more times during these 24 hours

CHAPTER 3

with a multi-channel fiber optic meter (Oxy-4 PreSens Precision Sensing GmbH, Regensburg, Germany). From the decline in oxygen concentration over time, SOD was calculated according to Rong et al. (2016).

CHAPTER 4

2.6 Stream metabolism To estimate stream metabolism, oxygen measurements were complemented with continuous (every 5 minutes) light intensity measurements using 1 HOBO Pendant™ probe per stream installed next to one of the oxygen probes. The 48 hours

CHAPTER 5

continuous measurements of oxygen concentrations in mg/l, temperature and light intensities were entered into a Bayesian Single-Station Estimation model (BASE) (Grace et al., 2015), using one bar atmospheric pressure (sea level), zero salinity (freshwater) and measured light intensity (Song et al., 2016) for the 1-station models

CHAPTER 6

(R-package BASEmetab, version 3) and adjusted for mean stream depth to calculate gross primary production (GPP) and ecosystem respiration (ER) rates. The default options of the BASEmetab package was used, which include the assumption made in Grace et al. (2015) and Song et al. (2016). R-squared values were used to assess the quality of the model output. The GPP and ER ratio (P/R) and net ecosystem production

CHAPTER 7

(NEP) (GPP – ER) were calculated.

Per land use type, 40 oxygen measurements were taken in total: 8 in the main flow path (1 average of main flow path probe x 4 streams x 2 days) and 32 in the deposition zones (4 probes x 4 streams x 2 days).

2.7 Macroinvertebrate community composition In each stream four replicate macroinvertebrates samples were taken from the deposition zones using a Surber sampler (625 cm2; mesh size: 0.5 mm). The 64

The landscape drives the stream

collected organisms were kept cold and within 48 hours sorted and identified to genus level. Total abundance and species richness were calculated (Supplementary table S2,

2.8 Statistics Differences in substrate cover (log transformed data), water and sediment quality parameters and mean oxygen concentrations between land use types and between the main flow path and the deposition zones were tested separately using

CHAPTER 1

sup. material).

stats). In those cases where the conditions of data normality (Shapiro–Wilk test) and homogeneity of variances (Levene’s test) were violated, differences between means were calculated using the non-parametric Kruskal–Wallis test, followed by a Mann-

CHAPTER 2

one-way analysis of variance (ANOVA), followed by a Tukey post hoc test (R-package

In order to consider the multiple streams and multiple probes per stream in the statistical analyses, the differences in metabolism (GPP and ER rates) were tested using a linear mixed effect model with land use type and within stream location as

CHAPTER 3

Whitney pairwise comparison test (R-package multcompView).

lmertest and emmeans) (Kuznetsova et al., 2017; Lenth, 2019). To test metabolism rates differences between main flow and deposition zone per land use type, T-tests were used.

CHAPTER 4

fixed effect and replicate stream, probe and day as random effects (R-packages

(from 51 % to 100 %) and supersaturation (above 100%) to the water and sediment quality parameters, log-transformed data from all replicate streams were included in

CHAPTER 5

To relate the frequency of oxygen saturation classes categorized as low saturation (below 20 %), medium saturation (from 21 % to 50 %), high saturation

2002).

To analyse differences in macroinvertebrate community composition among streams, a nonmetric multidimensional scaling (NMDS) was performed with log

CHAPTER 6

a PCA, performed in CANOCO for Windows version 5.12 (ter Braak and Smilauer,

differences between sites (R-package Vegan) (Oksanen et al., 2019). The fitting of environmental variables to the ordination plot was performed with vegan and the significance was obtained with a 1000 permutations test. Tested parameters were water quality (conductivity, turbidity, NO2, NO3, NH4, PO4, DOC and DIC), sediment characteristics (Chla, OM, C, N, C/N, IP, OP, TP and phi), substrate cover (wood debris, sand, macrophytes, FPOM and CPOM) and oxygen (frequency of occurrence of oxygen saturation classes below 20 %, from 21 % to 50 %, from 51 % to 100 % and above 100%).

65

CHAPTER 7

transformed abundance data followed by an analysis of similarities (ANOSIM) to test

Chapter 4

Moreover, to identify specific taxonomic shifts associated with the effect of land-use on macroinvertebrate community composition, an indicator species analysis was performed (R-package indicspecies) (De Caceres and Legendre, 2009).

CHAPTER 1

3. Results 3.1 Water quality pH and nitrate concentrations were similar in all streams. Turbidity,

CHAPTER 2

conductivity and nitrite, ammonium and total phosphorus concentrations differed significantly (p < 0.05) between land use types (Table 1). Turbidity was significantly (p < 0.05) higher in cropland streams than in all other streams. Conductivity was significantly (p < 0.05) higher in WWTP streams than in all other streams, except cropland streams. Conductivity was also significantly (p < 0.05) higher in IG and

CHAPTER 3

cropland streams than in forest and IG streams. Nitrite concentrations were highest in WWTP streams, but only significantly (p < 0.05) different from forest and EG streams.

Ammonium concentrations in forest streams were significantly (p < 0.05) lower than in cropland streams. Total phosphorus concentrations were highest in WWTP streams,

CHAPTER 4

but only significantly (p < 0.05) different from EG and cropland streams.

3.2 Sediment characteristics Chemical composition of the sediment in the deposition zones differed

CHAPTER 5

between land use types in organic matter content, chlorophyll-a concentrations and C/N ratios (Table 1). Organic matter content was significantly (p < 0.05) lower in sediments from WWTP streams than in sediments from EG, IG and cropland streams.

Sediment chlorophyll-a concentrations were significantly (p < 0.05) higher in intensive

CHAPTER 6

grassland streams than in all other streams, except from cropland streams. The sediment C/N ratio was significantly higher in forest streams than in cropland and WWTP streams.

3.3 Substrate cover

CHAPTER 7

Substrate cover differed between the streams depending on land use type (Table 1). Algae were only found in IG streams, while macrophytes were found in all streams except from forest streams. Woody debris and CPOM were only found in forest streams. Gravel was found in low coverage percentages in forest and WWTP streams, while sand was found in forest, IG and WWTP streams. FPOM was found in relatively high (> 25%) coverage percentages in all streams.

66

7.4 (0.3)

Turbidity (NTU)

21.5 (16.5)ab

27.3 (12.9)ab

15.7 (4.7)ab

51.8 (20.4)b

10.1 (6.3)a

EC (µS/cm)

184 (65)a

206 (43)a

295 (47)b

421 (100)bc

602 (76)c

NO2 (µM)

0.6 (0.7)a

0.4 (0.3)a

1.2 (0.7)ab

1.3 (0.5)ab

82.7 (70.1)

NH4 (µM)

5.5 (6)a

86.9 (127.7) 10.1 (4.8)ab

(0.5)abc

0.3

(0.1)b

58.6 (39.4)

a

18.3 (8.2)ab

154.9 (147.4)b

61.3 (74.6)ab 2.5 (1.5)cd

0.6

DOC (mM)

0.56 (0.63) a

1.31 (1.0) a

0.77 (0.16) a

1.31 (0.29) a

0.68 (0.12) a

DIC (mM)

0.49 (0.25)a

0.70 (0.22)a

0.78 (0.18)ab

1.13 (0.61)b

1.0 (0.22)ab

Grain size (Phi)

2.01 (0.31) a

2.63 (0.07) a

2.82 (0.15) a

2.94 (0.18) a

2.63 (0.28) a

(0.3) a

(2.5) a

(3.2) a

(5.2) a

1.3

OM (%)

3.0 (0.6)ab

7.7 (5.2)a

7.9 (6.3)a

14.4 (11.5)a

1.4 (0.3)b

TP (mmol/kg)

10.0 (1.9) a

37.1 (19.9) a

18.6 (10.8) a

146.2 (226.1) a

12.1 (4.4) a

OP (mmol/kg)

3.1 (0.1) a

8.7 (8.5) a

5.3 (4.7) a

61.4 (102.7) a

4.1 (1.4) a

IP (mmol/kg)

6.9(2) a

28.4

TN (mol/kg)

0.06 (0.01) a

0.20 (0.14) a

0.20 (0.14) a

0.39 (0.32) a

0.05 (0.01) a

Chla (mg/g)

6.7 (7.9)a

5.6 (2.1)a

41.1 (30)b

9.2 (9)ab

5.9 (5.2)a

(12.3) a

ab

13.3

6.5

0.7 (0.1) a

TC (mol/kg)

a

3.8

0.3

(0.1)b

175.0 (34.4) a

PO4 (µM)

3.5

1.4

(1.2)c

205.6 (195.3)

3.5 (3)b a

(6.9) a

ab

84.8

(123.6) a

bc

8 (3.3) a

C/N

20.4 (2.6)

17.8 (1.5)

17.9 (2.8)

16.6 (1.1)

13.9 (1.3)c

Algae (%)

0 (0)

0 (0)

8.8 (17.5)

0 (0)

0 (0)

Macrophytes (%)

0 (0)

52.1 (30.6)

8.7 (8.0)

27.4 (29.0)

34.4 (28.9)

Wood debris (%)

6.6 (2.8)

0 (0)

0 (0)

0 (0)

0 (0)

Gravel (%)

0.3 (0.5)

0 (0)

0 (0)

0 (0)

3.8 (6.4)

Sand (%)

29.2 (21.2)

0 (0)

35.8 (15.3)

0 (0)

32.9 (31.3)

CPOM (%)

38.8 (23.1)

0 (0)

0 (0)

0 (0)

0 (0)

FPOM (%)

25.4 (11.9)

46.7 (29.6)

46.7 (19.7)

72.9 (29.6)

27.1 (34.2)

3.2 Dissolved oxygen regime No significant differences (p > 0.05 ) between the main flow path and the deposition zones were observed. Large temporal variations in oxygen concentrations 67

CHAPTER 3

NO3 (µM)

a

7.5 (0.5)

7.5 (0.3) a

pH

a

7.9 (0.09)

WWTP

a

CHAPTER 4

7.5(0.02)

cropland a

CHAPTER 5

IG a

CHAPTER 6

EG a

CHAPTER 7

Substrate cover

Sediment quality

Water quality

forest

CHAPTER 2

Table 1. Physico-chemical characteristics of the selected streams. Water quality parameters (pH, turbidity, conductivity (EC), nitrite (NO2), nitrate (NO3), ammonium (NH4), phosphorus (PO4), dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) concentrations), sediment characteristics of the deposition zones (grain size, total carbon content (TC), organic matter content (OM %), total/organic/inorganic phosphorus content (TP/OP/IP), total nitrogen (N) content, chlorophyll–a (chla), content carbon/nitrogen ratio (C:N)) and substrate cover (in % estimated according to Hering et al. 2003) are given as means per land use type (n = 4 replicate streams). Standard deviations are given between brackets. Letters indicate a significant difference (p < 0.05) between land use types (Forest, EG – extensive grassland, IG – intensive grassland, cropland and WWTP – wastewater treatment plant) based on analyses of variance followed by multiple comparison test.

CHAPTER 1

The landscape drives the stream

Chapter 4

were observed, ranging from 27 to 56 % difference between maximum and minimum DO concentration in the forest streams and EG streams, respectively (Figure 1 left panels). In one of the replicate cropland streams, 117 % difference between the maximum and minimum concentrations was observed. In all forest, EG, IG and two of CHAPTER 1

the replicate cropland streams, the observed temporal variation coincided with the natural light-dark regime (Supplementary Figure S2). In the other cropland streams and in all WWTP streams, fluctuations in dissolved oxygen concentrations showed an irregular pattern with a high frequency of changes, not related to natural variations in

CHAPTER 2

the daily light regime (Figure 1).

The analysis of the cumulative frequency distributions shows which dissolved oxygen saturation classes were more frequently recorded per land use type. More than half of the dissolved oxygen measurements in cropland streams were below 15

CHAPTER 3

% air saturation for both the main flow path and the deposition zones (Figure 1, right panels). In contrast, in forest, intensive grassland and WWTP streams, more than half of the dissolved oxygen measurements were above 60 %.

CHAPTER 4 CHAPTER 5 CHAPTER 6 CHAPTER 7 68

3.3 Sediment oxygen demand and stream metabolism The average sediment oxygen demand in WWTP streams (0.6 g O2/m2/day) was significantly (p < 0.05 ) higher than in forest, cropland and both types of grassland streams (around 0.3 mg O2/m2/day) (Figure 2a).

The metabolism measurement goodness of fit decreased from IG (mean R 2 0.88, ± 0.11), EG (mean R2 0.72, ± 0.26) and Forest (mean R2 0.67, ± 0.28) to Crop 69

CHAPTER 7

Figure 1: Dissolved oxygen concentrations (left panels; in % air saturation) and corresponding cumulative frequency distributions of the concentrations (right panels) measured during 48 hours in the main flow path of the stream (blue lines) and in the deposition zones (red lines) in 4 replicate streams per land use type.

CHAPTER 6

CHAPTER 5

CHAPTER 4

CHAPTER 3

CHAPTER 2

CHAPTER 1

The landscape drives the stream

Chapter 4 (mean R2 0.59, ± 0.30) and WWTP (mean R2 0.32, ± 0.18). Comparing land use types, the gross primary production was significantly (p < 0.05) lower in forest and WWTP streams compared to all other streams (Figure 2b). Ecosystem respiration rates were significantly (p < 0.05) lower in forest and cropland streams than in EG and WWTP CHAPTER 1

streams (Figure 2c). Within streams, significant (p < 0.05) differences between measurements in the main flow path of the streams and in the deposition zones were only found for WWTP streams respiration rates and NEP. Higher respiration rates were measured in the deposition zones (T-test results in supplementary table S3).

CHAPTER 2 CHAPTER 3 CHAPTER 4 CHAPTER 5

Figure 2: Sediment oxygen demand (SOD) (n=4 replicate streams) (A) measured in sediment samples. Gross primary production (GPP) (B) and ecosystem respiration rates (ER) (C) based on BASEmetab model calculations in streams surrounded by different land use types. Because no significant differences per land use were found when the main flow path and the deposition zones were analysed separately, all GPP and ER measurements (n=40 per land use type) were combined. Letters indicate a significant difference between land use types (p < 0.05).

CHAPTER 6

3.4 Relationship between environmental conditions and oxygen concentrations In Figure 3, streams from different land use types were ordinated based on the frequency of oxygen saturation classes categorized as in low saturation (below 20 %), medium saturation (from 21 % to 50 %), high saturation (from 51 % to 100 %) and

CHAPTER 7

supersaturation (above 100%) (data from Figure 1, right panels) and environmental variables. The PCA explained 91,3% of the variation. The first axis that explained almost half of the total variation clearly separated clusters based on low and high DO concentrations and related to the differences in land use type. The ‘low DO cluster’ related to three of the four cropland and all extensive grassland streams and was significantly (p < 0.05) related to turbidity, substrate cover of fine particulate organic matter, sediment organic matter content and sediment nutrient (N, P, C). The ‘high DO cluster’ was related to one cropland and all forest, intensive grassland and WWTP 70

The landscape drives the stream

streams, significantly (p < 0.05) related to a high substrate cover with sand. The second axis separated streams (forest and EG) with a higher sediment C/N from

3.5 Macroinvertebrate community composition All

streams

were

characterized

by

a

typical

lowland

stream

macroinvertebrate community (Supplementary table S1). The average abundance varied from 224 individuals per sample in the streams surrounded by extensive grasslands to 743 in the WWTP streams. No large differences in number of taxa (16-19 taxa) were observed between streams. However, there was a dominance of Chironomus sp., Oligochaeta and Gastropoda in cropland and WWTP streams, while Plecoptera and most Trichoptera only occurred in forest and extensive grassland 71

CHAPTER 7

Figure 3: Principal Component Analysis (PCA) biplot for ordination of dissolved oxygen concentrations (based on frequency distributions of the concentrations in figure 1), sediment characteristics and water quality in 20 lowland streams with five different land use types (Forest, EG- extensive grassland, IG â&#x20AC;&#x201C; intensive grassland, Crop- cropland and WWTP).

CHAPTER 6

CHAPTER 5

CHAPTER 4

44.2 %

CHAPTER 3

CHAPTER 2

CHAPTER 1

15.2 %

streams (WWTP) with high concentration of dissolved nutrients.

Chapter 4

streams (Supplementary table S1). The non-metric multidimensional scaling (NMDS diagram) clearly separated the macroinvertebrate communities between land use types. Only the communities from extensive grassland streams showed large variations between replicates (Figure 4, ANOSIM: r = 0.2; p = 0.03). Forest streams CHAPTER 1

were located on the left side of the graph, better correlated with high oxygen saturation levels, a high C/N ratio in the sediment and woody debris and CPOM substrate cover. On the opposite site, the macroinvertebrate community composition in cropland and WWPT better related to low oxygen saturation levels, a high

CHAPTER 2

concentration of DIC and DOC, a high conductivity and small grain size (high phi).

Considering specific taxa contributing to the observed site grouping, two Trichoptera taxa were indicator species for forest streams, Ostracoda for intensive grassland streams, while for WWTP streams indicators species were Valvata sp., Stylaria

CHAPTER 3

lacustris, Chironomus sp. and Helobdella stagnalis (Supplementary table S4).

CHAPTER 4 CHAPTER 5 CHAPTER 6 CHAPTER 7

Figure 4: Non Metric Multidimensional Scaling (NMDS) ordination of macroinvertebrate communities (stress = 0.19; two dimensions; non-metric fit R2=0.96; linear fit R2=0.8). Contour polygons group the assemblages per land uses type (package Vegan; metaMDS; bray distance; monoMDS). The arrows correspond to the significant (p < 0.05) environmental variables measured in the stream deposition zones (data in table 1).

4. Discussion We have shown that differences in catchment land use determine physicochemical stream characteristics, ecosystem functioning and macroinvertebrate

72

The landscape drives the stream

community composition in lowland streams. By measuring these interrelated components of ecosystem structure and function simultaneously, we identified the sequence of events by which large scale impacts affect microhabitat conditions and

4.1 Physico-chemical stream characteristics When compared to natural lowland streams surrounded by forests, differences in substrate cover (e.g. FPOM dominance), sediment organic matter content (e.g. higher nutrient concentrations) and some water quality parameters (e.g. turbidity and dissolved nutrient concentrations) were observed in streams running through the catchments dominated by human impacts. These differences are most likely related to the human activities in the catchment, such as the use of fertilizers, ploughing, and the presence of livestock in the agricultural fields (Molina et al., 2017), or the treatment of wastewaters (Walsh et al., 2005). Substrate cover was affected in

CHAPTER 2

on macroinvertebrates community composition, as discussed below.

CHAPTER 3

also contributed to unravelling the underlying mechanisms of land use specific effects

CHAPTER 1

biological responses in terms of oxygen related stress. Moreover, the present study

an increase in fine particulate organic matter and/or an increase in the presences of aquatic macrophytes when compared to the forest streams. Although not directly reflected by the nutrient concentrations in this study, it could indeed be expected that

CHAPTER 4

all human impacted streams (grassland, cropland and WWTP), in particular shown by

and nutrients are not limiting, resulting in the enhanced growth of macrophytes (Haggard et al., 2005). Also an increase in sediment organic matter content and sediment chlorophyll concentrations was found in streams surrounded by agricultural

CHAPTER 5

especially in streams surrounded by open fertilized agricultural grasslands both light

quality was most affected in the WWTP streams as a direct result from the input of discharge from the wastewater treatment plants. Similar impacts of land use have been shown previously by e.g. Peterson et al. (1993); Wood and Armitage (1997);

CHAPTER 6

fields, pointing to the input of nutrient rich organic particles from these fields. Water

4.2 Ecosystem functioning The observed differences in physico-chemical stream characteristics coincided with clear differences in oxygen regimes and stream metabolism rates. The low productivity/respiration ratios (< 1 in this study) indicate that all studied lowland streams, regardless of land use type, depended on energy input from the catchment (Hoellein et al., 2013), hence being predominantly fuelled by allochthonous organic matter and nutrient inputs from the adjacent land (Bernhardt et al., 2018). As 73

CHAPTER 7

Walsh et al. (2005).

Chapter 4

indicated by the present principal component analysis, this terrestrial input of particles and nutrients subsequently resulted in differences in oxygen concentrations, varying with land use type. Moreover, besides the impact on the average dissolved oxygen concentrations, also strong differences in daily variations in oxygen CHAPTER 1

concentrations were found in streams surrounded by different land use types. In streams surrounded by croplands, the long periods of low oxygen concentrations are possibly linked to the influx of organic particles from the adjacent field, as indicated by the high turbidity and a high percentage of FPOM substrate cover. The high FPOM

CHAPTER 2

substrate cover and water turbidity hamper the development of primary producers, as observed by Jones et al. (2014) and Vermaat and Bruyne (1993), and therefore diminishing oxygen concentrations in the water column. In contrast, in streams surrounded by grasslands, the relatively strong daily oxygen fluctuations coinciding

CHAPTER 3

with the light-dark cycle were most likely caused by the macrophytes growing in the nutrient rich deposition zones. As a result, these streams also showed the highest ecosystem production rates. These findings corroborate previous studies by e.g. Finlay (2011) and Bernot et al. (2010), who reported that streams located in open fields such

CHAPTER 4

as agricultural grasslands showed a higher primary production than forest streams. In contrast, fluctuations in oxygen concentrations in the WWTP streams were not related to the natural daily variations in light and primary production, but instead showed an irregular, fast fluctuating pattern, which was most likely caused by the frequent and fluctuating discharge of effluent from the nearby sewage treatment

CHAPTER 5

plants. WWTPs can cause typical increased hydrologic flashiness in the effluent receiving streams (Meyer et al., 2005; Walsh et al., 2005), causing disruption of natural dissolved oxygen concentrations. Although the average oxygen concentration in the water was quite high, the oxygen availability in the sediment is expected to be

CHAPTER 6

low, as a result of the presently observed high sediment oxygen demands and high respiration rates in the WWTP streams. This high benthic metabolic activity observed in the studied WWTP streams coincided with the continuous input of nitrate, phosphorus and oxygen into the water column, likely stimulating the microbial

CHAPTER 7

community growing on the top sediment layer of the wastewater impacted streams (Bernhardt and Likens, 2002; Bernot et al., 2006; Paul and Meyer, 2001; Stewart and Franklin, 2008; Walsh et al., 2005). The observed effects on oxygen regimes in streams surrounded by human impacted land use types are in agreement with Young et al.

(2008), who suggested that impacted streams deviate from natural forest streams in terms of gross primary production and community respiration. Moreover, the differences between oxygen regimes in streams surrounded by agricultural fields (influenced by the presence of macrophytes) and WWTP streams (with high sediment 74

The landscape drives the stream

respiration rates) found in this study give insight into the underlying mechanisms by showing the link between land use type and the relative importance of the autotrophic and heterotrophic processes underlying the observed effects on stream in line with e.g. Battin et al. (2016) and Lear et al. (2013), who argued that fundamental ecosystem processes were driven by metabolic activities from the microbial community growing on top of the sediment.

CHAPTER 1

metabolism, as previously suggested by Johnson et al. (2009). These observations are

documented land use specific stream metabolism. Yet, we also observed that the BASEmetab model could not deal very well with the artificial daily variation in oxygen regime as observed in WWTP streams, affecting the reliability of the stream metabolism results.

4.3 Macroinvertebrate community composition Ultimately, the differences in physico-chemical stream characteristics and

CHAPTER 3

metabolic processes reduces natural inter-regional variability. Here we also

CHAPTER 2

According to Bernot et al. (2010), the strong influence of land use on

reflected by differences in macroinvertebrate community structure. The difference in oxygen demand for survival and fitness between the individual species (Fox and Taylor, 1955) seems to be an important ecological driver behind the observed

CHAPTER 4

oxygen regimes in the streams surrounded by different land use types were also

taxa responded to the oxygen concentration. While the long period of low dissolved oxygen concentrations in the water column may explain the difference in community composition in cropland streams compared to forest streams, in WWTP streams it was

CHAPTER 5

patterns, in line with Berger et al. (2018) who observed that most macroinvertebrate

affected community composition (Boulton et al., 1997). In cropland and WWTP streams, the low oxygen availability and fine sediment limited the occurrence of EPT (Ephemeroptera, Plecoptera and Trichoptera) species (Angradi, 1999; Connolly et al.,

CHAPTER 6

mainly the expected low oxygen concentrations in the sediment that might have

such as Chironomus sp., worms and gastropods, dominated the macroinvertebrate communities (Berger et al., 2018; Ding et al., 2016; Justus et al., 2014; Manfrin et al., 2018; Pardo and GarcĂ­a, 2016). In the grassland streams, the oxygen concentration regimes did not seem to be a limiting factor for the macroinvertebrates, since long periods of high concentrations were observed in these streams at least during daytime. Yet, the low oxygen concentrations during the night may have caused these communities to take a position in between the forest streams and the heavily impacted cropland and WWTP streams. We acknowledge however, that effects on 75

CHAPTER 7

2004), while taxa that can compensate frequent low dissolved oxygen concentrations,

Chapter 4

macroinvertebrate communities arising from other land use related stress, such as habitat homogeneity (Westveer et al., 2017), hydrologic disturbance (Burns et al., 2015) and contaminant loads (Schwarzenbach et al., 2006) might also occur.

CHAPTER 1

5. Synthesis and conclusions The present study provided important information on stream metabolism and oxygen regime in lowland streams, since most of the classical work was conducted in forested headwater streams with relatively steep gradients (AcunĂŁ et al.,

CHAPTER 2

2004; Bunn et al., 1999; Houser and Mulholland, 2005; Young and Huryn, 1999).

Streams receiving forest inputs (leaves and woody debris) sustained a relatively stable oxygen regime and a diverse macroinvertebrate community.

Grassland streams were driven by nutrients, strengthening primary producers,

CHAPTER 3

resulting

in

highly

fluctuating

oxygen

regimes

with

clear

effects

on

macroinvertebrates, but mechanistically unexplained. Silt driven cropland streams were characterized by low oxygen concentrations and high abundances of taxa tolerant to low dissolved oxygen. Streams receiving WWTP effluents showed high

CHAPTER 4

heterotrophic microbial community activity, high sediment oxygen demands and macroinvertebrate communities indicative of deteriorated conditions. However, these inputs might change over time as a result of seasonal land use management, especially in agricultural fields.

We have thus shown that differences in catchment land use type determine

CHAPTER 5

physicochemical stream characteristics, ecosystem functioning and macroinvertebrate community structure in lowland streams. Different inputs of terrestrial organic particles impacted instream metabolic processes, such as primary production and respiration, and subsequently resulted in highly different oxygen diel regimes in the

CHAPTER 6

streams surrounded by different land use types, which in turn were reflected by large differences in macroinvertebrate community composition. Therefore, we argue that land use specific impacts on lowland streams were exerted via fine sediment accumulation in deposition zones, affecting oxygen regimes, sediment oxygen

CHAPTER 7

demand and stream metabolism, ultimately changing macroinvertebrate community composition. This study supports the importance of including the catchment scale and multiple interconnected parameters in ecological stream quality assessments.

76

The landscape drives the stream

Supplementary material

Light sensor Oxygen sensor in the stream main flow Oxygen sensor in the deposition zone Acrylic plate Water flow

CHAPTER 7

CHAPTER 6

CHAPTER 5

Figure S1: Installation of oxygen and light sensors in each studied stream.

CHAPTER 3

Deposition zone

CHAPTER 4

Legend:

CHAPTER 2

CHAPTER 1

20 m stream reach

77

Chapter 4

Table S1: Mean water temperature (℃), depth (m); width (m), velocity (m/s) and catchment area (n = 4 replicate stream), GPS coordinates (decimal degrees) and the percentage occurrence of each land use type present in the catchment, per land use type (Forest, EG – extensive grassland, IG – intensive grassland, cropland and WWTP – wastewater treatment plant).

CHAPTER 1

Water temperature (℃)

forest

EG

12.6 (1.0)

12.4 (0.4)

(±0.08)a

(±0.15)a

12.8 (0.1)

WWTP

14.7 (0.5)

15.9 (0.8) 0.26 (±0.07)a

CHAPTER 2 CHAPTER 3

Width (m)

2.0 (±0.3) a

2.2 (±1.2) a

Velocity (m/s)

0.099 (±0.02)ab

0.069 (±0.08)a

Discharge (m3/s)

0.004 (±0.002)a

0.003 (±0.002)a

0.118 (±0.03)ab 0.010 (±0.006)ab

1.2 (± 0.8)

2.9 (± 1.6)

2.5 (± 1.3)

2.1 (±0.6)

52.305007, 5.726070 52.288031, 5.915494 52.3698969, 6.0065093 52.340030, 5.929707

52.332772, 5.937832 52.322866, 5.944421 52.9364721, 6.6275572 52.9592017, 6.571805

51.995054, 5.653381 52.3874072, 5.730138 52.389585, 5.733787 52.382086, 5.711314

53.026983, 6.698200 52.9422384, 7.0401342 52.8947691, 6.7682192 53.025835, 6.860144

52.343681, 6.001478 53.014682, 6.774243 51.995914, 5.653480 52.089662, 5.446765

forest (%)

92 (±9.3)

1.8 (±1.9)

0 (±0)

2 (±3)

n.a.

EG (%)

9.4 (±13.3)

88.1 (±8.9)

5 (±5.1)

0 (±0)

n.a.

IG (%)

0 (±0.4)

9.3 (±9.7)

88.9 (±2.9)

25.4 (±5.7)

n.a.

cropland (%)

1.6 (±0.8)

0.8 (±1.6)

2.8 (± 2.9)

72.6 (±3.3)

n.a.

urban (%)

0 (±3.7)

0 (±0)

3.2 (±2.2)

0 (±0)

n.a.

replicate 2 replicate 3

CHAPTER 4

replicate 4

2.4 (±0.8) a

0.35

(±0.1)a

0.13

replicate 1

0.22

(±0.02)a

cropland

Depth (m)

Total catchment area (km2) GPS coordinates (DD)

0.27

IG

2.9 (±1.2) a 0.022 (±0.01)a 0.004 (±0.004)a

2.8 (±0.7)a 0.192 (±0.05)b 0.022 (±0.012)b

Land use type

CHAPTER 5 CHAPTER 6 CHAPTER 7

78

Table S2: Mean abundance and standard deviation (sd) (n = 4) of macroinvertebrate taxa per sample (625 cm2), per land use (Forest, EG – extensive grassland, IG – intensive grassland, cropland and WWTP – wastewater treatment plant). forest

EG

IG

cropland

WWTP

mean

sd

mean

sd

mean

sd

mean

sd

mean

sd

Asellus aquaticus

5.9

10.9

9.3

9.4

50.3

62.8

14.5

12.7

32.4

38.8

Proasellus sp.

0.1

0.1

0.3

0.6

2.4

3.5

0.2

0.4

14.8

28.8

Pisidium sp.

5.6

1.8

34.3

28.6

10.5

11.0

23.2

17.9

0.1

0.3

Sphaerium sp.

0.0

0.0

1.8

3.1

0.0

0.0

11.8

16.2

0.8

1.3

Asselidae

Bivalvea

79

CHAPTER 7

Figure S2: Light in photosynthetically active radiation (PAR) measured during 48 hours in the main flow path of the stream in 4 replicate streams per land use type.

CHAPTER 6

CHAPTER 5

CHAPTER 4

CHAPTER 3

CHAPTER 2

CHAPTER 1

The landscape drives the stream

Chapter 4

forest

EG

IG

cropland

WWTP

mean

sd

mean

sd

mean

sd

mean

sd

mean

sd

Apsectrotanypus trifascipennis Chironomus sp.

4.4

7.4

1.0

1.7

10.8

8.3

0.0

0.0

0.0

0.0

0.8

0.7

1.6

2.8

0.6

0.7

7.7

8.6

33.3

48.5

Cladopelma sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.1

Cladotanytarsus sp.

0.1

0.1

0.0

0.0

4.4

8.4

0.0

0.0

0.0

0.0

Clinotanypus nervosus Conchapelopia sp.

0.0

0.0

0.1

0.3

2.4

3.1

1.1

1.9

0.8

1.3

0.6

0.5

0.1

0.1

0.6

0.8

0.1

0.1

0.1

0.1

Corynoneura sp.

0.3

0.2

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

Cricotopus sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.3

0.3

Cryptochironomus sp.

Dicrotendipes sp.

0.1

0.3

0.0

0.0

1.4

1.8

0.1

0.3

0.4

0.5

0.0

0.0

0.0

0.0

0.0

0.0

0.2

0.4

0.0

0.0

Endochironomus sp.

Epoicocladius sp.

0.0

0.0

0.1

0.1

0.1

0.3

0.6

0.7

1.6

3.3

0.4

0.9

0.3

0.5

0.0

0.0

0.0

0.0

0.0

0.0

Eukiefferiella sp.

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Glyptotendipes sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.3

0.0

0.0

Heterotrissocladius sp.

Macropelopia sp.

0.2

0.4

0.0

0.0

0.0

0.0

0.3

0.5

0.0

0.0

2.1

4.0

0.2

0.4

0.8

0.7

0.4

0.8

0.0

0.0

Micropsectra sp.

172.8

340.0

0.8

1.2

16.5

12.7

0.0

0.0

0.0

0.0

Microtendipes sp.

0.0

0.0

0.0

0.0

0.1

0.3

0.1

0.1

5.4

9.9

Parachironomus sp.

Paratendipes sp.

0.0

0.0

0.1

0.1

0.1

0.1

0.1

0.3

0.4

0.8

8.4

15.8

0.1

0.1

3.2

1.9

0.1

0.1

0.0

0.0

Phaenospectra sp.

3.5

3.8

0.1

0.1

0.0

0.0

0.3

0.6

0.8

1.3

Polypedilum sp.

5.9

7.8

0.6

0.7

0.4

0.6

0.4

0.8

0.1

0.1

Procladius sp.

0.9

1.3

0.8

0.5

7.2

2.9

6.0

11.0

0.0

0.0

Prodiamesa rufovittata Prodiamesa olivacea Psectrotanypus varius Rheotanytarsus sp.

0.1

0.3

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

4.1

2.8

0.4

0.6

1.8

2.2

0.0

0.0

0.8

1.1

0.0

0.0

9.7

18.7

0.4

0.3

11.5

13.8

0.3

0.5

0.2

0.4

0.3

0.6

0.1

0.3

0.0

0.0

0.1

0.1

Schineriella schineri

0.3

0.4

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Stempelinella sp.

0.3

0.5

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Stichochironomus sp.

5.8

6.7

0.0

0.0

4.1

6.1

0.3

0.6

0.0

0.0

Chironomidae

CHAPTER 1 CHAPTER 2 CHAPTER 3 CHAPTER 4 CHAPTER 5 CHAPTER 6 CHAPTER 7

80

The landscape drives the stream

mean

sd

mean

sd

mean

sd

mean

sd

1.2

0.1

0.3

0.2

0.2

0.3

0.6

0.2

0.2

Xenopelopia sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.6

1.3

0.0

0.0

Zavrelimyia sp.

1.1

1.2

0.0

0.0

0.1

0.3

0.0

0.0

0.0

0.0

Agabus sp.

0.4

0.3

0.0

0.0

0.1

0.1

0.1

0.1

0.0

0.0

Brychius sp.

0.0

0.0

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

Colymbetes sp.

0.0

0.0

0.1

0.1

0.0

0.0

0.1

0.1

0.0

0.0

Cyphon sp.

0.0

0.0

0.1

0.3

0.0

0.0

0.0

0.0

0.0

0.0

Donaciinae

0.0

0.0

0.4

0.8

0.0

0.0

0.0

0.0

0.0

0.0

Dryops sp.

0.0

0.0

0.0

0.0

0.1

0.1

0.0

0.0

0.1

0.3

Dysticus sp.

0.4

0.9

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Elmidae

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.1

Graptodytes sp.

0.0

0.0

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

Gyrinus sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.3

0.6

0.2

0.2

Haliplus sp.

0.0

0.0

1.9

3.8

0.8

0.7

0.2

0.2

0.3

0.2

Hydroporus sp.

0.2

0.4

0.7

0.8

0.3

0.3

0.5

0.8

0.0

0.0

Hygrobia hermanni

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

Hygrotus sp.

0.0

0.0

0.3

0.4

0.2

0.4

0.0

0.0

0.1

0.1

Hyphydrus ovatus

0.0

0.0

0.8

1.3

0.1

0.1

0.0

0.0

0.0

0.0

Ilybius sp.

0.2

0.4

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Platambus maculatus Porhydrus sp.

1.2

1.5

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.2

0.4

0.0

0.0

0.0

0.0

0.0

0.0

Ceratopogonidae

0.3

0.3

0.3

0.5

1.7

1.1

0.4

0.7

0.6

1.0

Chaoboridae

0.0

0.0

0.3

0.6

0.0

0.0

0.0

0.0

0.0

0.0

Culicidae

0.1

0.1

0.0

0.0

0.0

0.0

0.1

0.1

0.0

0.0

Dicranota

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Dixella sp.

0.0

0.0

0.1

0.1

0.0

0.0

0.1

0.1

0.0

0.0

Elodes sp.

0.2

0.4

0.6

1.3

0.0

0.0

0.0

0.0

0.0

0.0

Eloeophila sp.

1.6

1.9

0.1

0.1

0.0

0.0

0.0

0.0

0.1

0.1

Empididae

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.1

Ephydridae

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.6

1.0

Erioptera sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.3

0.5

0.0

0.0

Euphylidoea sp.

0.1

0.1

3.6

7.3

0.0

0.0

0.0

0.0

0.0

0.0

Hexatoma sp.

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Neolimnomyia sp.

0.3

0.4

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Pilaria sp.

0.8

0.9

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Coleoptera

(other) Diptera

81

CHAPTER 2

sd

0.7

CHAPTER 3

mean Tanytarsus sp.

CHAPTER 1

WWTP

CHAPTER 4

cropland

CHAPTER 5

IG

CHAPTER 6

EG

CHAPTER 7

forest

Chapter 4

forest

EG

IG

cropland

WWTP

CHAPTER 1 CHAPTER 2 CHAPTER 3 CHAPTER 4 CHAPTER 5 CHAPTER 6 CHAPTER 7

mean

sd

mean

sd

mean

sd

mean

sd

mean

sd

Ptychopteridae

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Simuliidae

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.1

Stratiomyidae

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.4

0.7

Tabanidae

1.0

1.2

0.1

0.1

0.2

0.4

0.0

0.0

0.1

0.1

Tipulidae

0.0

0.0

0.0

0.0

0.3

0.4

0.4

0.8

0.3

0.4

Baetis sp.

0.0

0.0

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

Caenis sp.

0.0

0.0

0.1

0.1

0.1

0.1

1.2

2.4

0.1

0.1

Cloeon dipterum

0.5

1.0

10.6

13.7

1.3

1.1

66.8

104.6

0.3

0.2

Leptophlebia sp.

11.6

23.1

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Procloeon bifidum

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

Ephemera danica

5.3

9.2

2.5

5.0

0.0

0.0

0.0

0.0

0.0

0.0

Crangonix sp.

0.0

0.0

0.9

1.4

0.0

0.0

0.6

1.3

10.5

21.0

Gammarus roeselli

1.7

3.4

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Gammarus sp.

27.9

35.2

76.7

145.6

21.7

17.7

1.6

3.3

31.8

52.1

Anisus sp.

0.3

0.5

0.9

1.1

3.6

3.3

5.9

6.9

1.8

3.5

Bathyomphalus contortus Bithynia sp.

0.0

0.0

0.3

0.5

1.7

1.1

1.5

2.5

0.1

0.3

0.0

0.0

5.1

7.2

3.8

7.1

12.3

23.5

2.3

2.2

Galba truncatula

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.1

0.3

Gyraulus sp.

0.0

0.0

0.2

0.2

0.3

0.2

2.4

4.8

8.6

15.0

Hippeutis complanate Lymnaea stagnalis

0.0

0.0

0.2

0.4

0.0

0.0

0.7

0.6

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.3

0.5

0.4

0.8

Physa sp.

0.0

0.0

0.9

1.6

1.8

2.3

0.4

0.3

1.4

1.6

Physella acuta

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.3

0.5

Planorbarius corneus Planorbis sp.

0.0

0.0

1.4

1.1

0.1

0.1

1.8

2.0

0.5

0.8

0.0

0.0

1.5

3.0

0.9

1.6

0.2

0.4

0.4

0.8

Potamopyrgus antipodarum Radix sp.

0.1

0.1

0.0

0.0

1.3

2.1

0.0

0.0

224.2

443.1

0.0

0.0

0.4

0.5

1.5

2.7

0.3

0.3

0.6

1.0

Stagnicola sp.

0.0

0.0

0.6

1.3

0.1

0.1

0.1

0.1

0.3

0.3

Valvata sp.

0.0

0.0

3.3

4.4

9.3

7.5

18.4

31.1

12.5

16.6

Cymatia sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.1

0.0

0.0

Notonecta sp.

0.0

0.0

0.5

0.7

0.0

0.0

0.1

0.1

0.0

0.0

Ephemeroptera

Gammaridae

Gastropoda

Hemiptera

82

The landscape drives the stream

mean

sd

mean

sd

mean

sd

mean

sd

0.0

0.1

0.1

0.0

0.0

0.2

0.4

0.0

0.0

Sigara sp.

0.0

0.0

0.3

0.3

4.8

8.6

0.4

0.4

0.4

0.9

Hydracarina

4.8

8.3

2.1

1.5

13.7

4.3

0.6

0.6

0.1

0.1

Alboglossiphonia sp.

Erpobdella sp.

0.1

0.1

0.1

0.1

0.1

0.1

0.3

0.5

0.8

1.5

0.8

0.9

0.3

0.2

1.4

1.3

0.6

0.6

8.5

7.1

Glossiphonia sp.

0.8

1.2

0.4

0.5

0.9

1.5

0.3

0.4

1.6

1.9

Helobdella stagnalis Theromyzon sp.

0.0

0.0

0.0

0.0

0.8

1.3

0.8

1.3

28.5

55.7

0.1

0.3

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.1

Eleophila nymphaeata Megaloptera

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.1

0.0

0.0

Sialis fuliginosa

1.8

3.6

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Sialis lutaria

0.4

0.5

3.5

2.3

5.4

3.8

5.2

8.7

0.0

0.0

Aeshna sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Calopterix sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.4

0.9

Coenagrionidae

0.0

0.0

0.6

1.1

0.1

0.1

1.3

2.3

0.3

0.4

Hesperocorixa sp.

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

Libellula depressa

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.3

0.0

0.0

Oligochaeta

86.9

149.3

20.4

14.7

52.3

33.3

95.8

158.2

294.2

250.0

Stylaria lacustris

0.0

0.0

0.1

0.1

4.3

4.7

0.4

0.9

2.4

2.2

Ostracoda

0.0

0.0

0.4

0.6

29.6

28.0

0.0

0.0

0.2

0.2

Dendrocoelum lacteum Dugesia lugubis

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.6

0.7

Planaria torva

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.4

0.8

Polycelis hepta

0.0

0.0

0.1

0.3

0.0

0.0

0.1

0.3

0.1

0.3

Nemoura sp.

3.5

5.5

0.1

0.3

0.0

0.0

0.1

0.1

0.0

0.0

Porifera

0.0

0.0

0.0

0.0

0.1

0.1

0.1

0.1

0.0

0.0

Adicella reducta

0.0

0.0

0.2

0.2

0.0

0.0

0.0

0.0

0.0

0.0

Agrypnia sp.

0.0

0.0

0.0

0.0

0.1

0.1

0.1

0.1

0.0

0.0

Hirudinea

Lepdoptera

Odonata

Oligochaeta

Platelminty

Plecoptera

Trichoptera

83

CHAPTER 2

sd

0.0

CHAPTER 3

mean Plea minutissima

CHAPTER 1

WWTP

CHAPTER 4

cropland

CHAPTER 5

IG

CHAPTER 6

EG

CHAPTER 7

forest

Chapter 4

forest

EG

IG

cropland

WWTP

CHAPTER 1 CHAPTER 2 CHAPTER 3 CHAPTER 4 CHAPTER 5

mean

sd

mean

sd

mean

sd

mean

sd

mean

sd

Athripsodes sp.

0.1

0.3

0.1

0.3

0.0

0.0

3.1

6.1

0.0

0.0

Beraeodes minutus

8.5

17.0

7.7

15.4

0.3

0.5

0.1

0.3

0.0

0.0

Ecnomus tenellus

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.3

Glyphotaelius pellucidus Halesus radiatus

2.4

1.8

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.3

0.0

0.0

0.0

0.0

0.0

0.0

Holocentropus sp.

0.0

0.0

0.2

0.2

0.0

0.0

0.0

0.0

0.0

0.0

Hydroptila sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.3

0.6

Hydropsyche sp.

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.6

1.0

Limnephilus sp.

6.3

8.6

1.4

2.7

0.1

0.1

0.0

0.0

0.5

1.0

Mystacides sp.

0.1

0.3

0.1

0.1

0.0

0.0

0.0

0.0

1.6

3.3

Notidobia ciliaris

1.6

2.6

1.6

1.9

0.1

0.1

0.0

0.0

0.0

0.0

Oxyethira sp.

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Phryganeidae

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.3

Plectrocnemia sp.

0.1

0.1

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

Polycentropidae

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Potamophylax rotundipennes Sericostoma personatum Silo nigricornis

3.4

4.7

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.3

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Triaenodes bicolor

0.0

0.0

0.0

0.0

0.0

0.0

0.4

0.9

0.1

0.1

CHAPTER 6 CHAPTER 7 84

CHAPTER 7

CHAPTER 6

CHAPTER 5

CHAPTER 4

CHAPTER 3

CHAPTER 2

CHAPTER 1

The landscape drives the stream

85

Chapter 4 Table S4: Indicator taxa per land use (Forest, EG – extensive grassland, IG – intensive grassland, cropland and WWTP – wastewater treatment plant) and respective p-values (package indicspecies; multipatt). forest

EG

IG

cropland

WWTP

stat

p.value

CHAPTER 1 CHAPTER 2 CHAPTER 3

Micropsectra sp.

x

0.95

0.05

Pilaria sp.

x

0.87

0.01

Potamophylax rotundipennes

x

0.87

0.02

Glyphotaelius pellucidus

x

0.86

0.01

Corynoneura sp.

x

0.78

0.03

Apsectrotanypus trifascipennis

x

x

0.97

0.00

Paratendipes sp.

x

x

0.93

0.01

Hydracarina

x

x

x

0.98

0.01

Pisidium sp.

x

x

x

1.00

0.00

Gammarus sp.

x

x

x

0.96

0.05

0.99

0.00

x

0.88

0.05 0.01

Ostrachoda

x

Anisus sp.

x

x x

CHAPTER 4 CHAPTER 5

Procladius sp.

x

x

x

0.97

Sialis lutaria

x

x

x

0.90

0.01

x

x

x

0.92

0.03

x

0.90

0.01

x

0.97

0.04

x

0.98

0.03

Valvata sp.

Stylaria lacustris

x

Chironomus sp.

x

Helobdella stagnalis

Acknowledgements: We would like to thank the water authorities Hunze en Aa’s and CHAPTER 6

Vallei en Veluwe and João Lotufo for their help in the field. Thijs de Boer for helping with GIS, and Dorine Dekkers for her help in macroinvertebrate identification. We thank laboratory technicians Mariska Beekman and Merijn Schuurmans. PCRO received funding from CNPq Brazil (grant number 200879/2014-6, 2014).

CHAPTER 7 86

Chapter 5

Chapter 5 Responses of macroinvertebrate communities to land use specific sediment characteristics in lowland streams

Paula C. dos Reis Oliveira Michiel H. S. Kraak Michelle Pena-Ortiz Harm G. van der Geest Piet F. M. Verdonschot

Science of the Total Environment, under review

Author Contributions: PCRO, PFMV, HG and MK designed the experiment. PCRO and MPO conducted the experiment. PCRO and MPO analysed most of the data, and wrote most of the manuscript together with PFMV, HG and MK. PFMV, HG and MK advised on practical issues during the course of the experiment and data processing and contributed to editing and revising draft versions of the manuscript.

The landscape drives the stream

Highlights • Lowland stream sediment characteristics were land use specific.

• Macroinvertebrate community composition was also land use specific.

• Shannon-Wiener diversity was best explained by fatty acids origin, and • Oligochaeta and Chironomus sp. by low sediment C/N ratio.

CHAPTER 1

• EPT richness was positively related to the presence of woody debris.

impact sediment characteristics in terms of food resources and habitat structure, resulting in differences in macroinvertebrate community composition. Therefore, we investigated to what extent land use specific sediment characteristics structure macroinvertebrate communities. To this purpose linear multiple regression models were constructed, in which macroinvertebrate biotic indices were considered as response variables and sediment characteristics as predictor variables, analysed in 20

CHAPTER 3

The input of land use specific organic matter into lowland streams may

CHAPTER 2

Abstract

explained by fatty acids origin, such as in grassland streams, where a higher relative content of plant derived fatty acids related to a higher macroinvertebrate diversity. In cropland and WWTP streams with a low C/N ratio and dominated by microbial derived fatty acids, higher abundances of Oligochaeta and Chironomus sp. were observed. EPT richness was positively related to woody debris substrate cover, which only occurred in forest streams. Hence, macroinvertebrate community composition was influenced by the origin of the organic material, being either allochthonous or autochthonous and when autochthonous being either autotrophic or heterotrophic. Yet, in spite of the observed relation between sediment characteristics and macroinvertebrate community composition, this is obviously not the only driver of community composition. But, if the minimum requirements of the other ecological parameters such as oxygen, habitat heterogeneity and stream velocity are fulfilled, sediment characteristics can certainly be considered as a key ecological filter.

Key words: food resource, C:N ratio, substrate cover, fatty acids, macroinvertebrate indices, GLM

89

CHAPTER 5

macroinvertebrate community composition. Shannon-Wiener diversity was better

CHAPTER 6

C/N ratio, woody debris substrate cover and the origin of fatty acids influenced

CHAPTER 7

characteristics and macroinvertebrate community composition were land use specific.

CHAPTER 4

stream stretches running through five different land use types. Sediment

Chapter 5

1. Introduction Catchment land use strongly defines the structure and functioning of stream ecosystems, urging for a better understanding of the connection between terrestrial and aquatic ecosystems (Allan, 2004; Bunn et al., 1999; Palmer et al., 2014; Sponseller CHAPTER 1

and Benfield, 2001). Impacts from different land use types on benthic ecosystems and macroinvertebrate community structure have been reported (Lu et al., 2014; Meyer et al., 1998; Niyogi et al., 2007; Niyogi et al., 2004; Quinn et al., 1997), but the key environmental variables driving land use specific benthic community composition

CHAPTER 2

remain unclear. The input of terrestrial fine sediment may influence the sediment characteristics in streams (Burcher and Benfield, 2006; Kominoski and Pringle, 2009), particularly in deposition zones, where allochthonous materials, woody debris, and nutrients accumulate (Golladay et al., 1987; Pusch et al., 1998). Since the composition

CHAPTER 3

of allochthonous material differs between land use types (e.g. Matthaei et al., 2010), impacts on stream sediment characteristics are expected to be land use specific as well (De Haas et al., 2002; dos Reis Oliveira et al., 2018), differently affecting local macroinvertebrate communities (Callisto and Graรงa, 2013; Wood and Armitage, 1999)

CHAPTER 4

and aquatic food webs (Cummins and Klug, 1979; Tank et al., 2010). Laboratory studies have indeed shown that macroinvertebrate species respond to differences in sediment characteristics, each preferring a specific sediment food quality (Chung and Suberkropp, 2009; De Haas et al., 2002; dos Reis Oliveira et al., 2018; Vonk et al., 2016). Yet, it remains poorly known whether sediment characteristics in terms of food

CHAPTER 5

resources and habitat structure are key ecological filters driving macroinvertebrate community composition to the same extent as for example oxygen (e.g. Jacobsen, 2008), habitat heterogeneity (Burdon et al., 2013; Whatley et al., 2014) and stream velocity (e.g. White et al., 2017) do. Therefore, the aim of this study was to determine

CHAPTER 6

if lowland stream sediment characteristics are land use specific and if they do structure macroinvertebrate communities. To this purpose linear multiple regression models were constructed, in which macroinvertebrate biotic indices were considered as response variables and sediment characteristics as predictor variables. To this end

CHAPTER 7

four replicate streams running through five different land use types were sampled, where substrate cover, sediment organic matter composition and the origin of fatty acids, being either microbial or plant derived, were analysed.

90

The landscape drives the stream

2. Material and methods 2.1 Study area streams in the Netherlands representing five common land use types. For each land use type, four replicate streams with similar morphological characteristics were selected (mean depth 0.13–0.35 m; width 2.0–2.9 m; current velocity 0.02–0.19 m/s; discharge 0.004–0.022 m3/s). The land use types included forest, serving as natural

CHAPTER 1

This study was conducted in October and November 2017, in 20 lowland

fertilized pasture (extensive grassland (EG)), fertilized pasture (intensive grassland (IG)), arable field (cropland) and waste water treatment plants (WWTP). The streams in the forested areas served as natural reference sites. The selection criteria for the

CHAPTER 2

reference sites (hereafter referred to as forest) and streams in areas with non-

percentage of surface covered (> 2/3) by the selected land use type, as indicated on the national Dutch land use map (LGN5) (Hazeu et al., 2011). WWTP effluent receiving streams were selected based on the presence of a sewage treatment plant outflow

CHAPTER 3

streams in the forest, grasslands and cropland catchments were based on the

2.2 Sediment sampling In each of the 20 streams deposition zones were identified in a 20 m stretch,

CHAPTER 4

(~50.000 people).

particulate organic matter (FPOM) accumulated. A sediment sample was taken from representative deposition zones by sampling the top 2 cm layer using an acrylic core several times until 500 g sample was collected to perform all analyses. The samples

CHAPTER 5

defined as deeper instream areas where current velocity was low and where fine

2.3 Sediment characteristics In the present study, sediment characteristics included substrate cover, sediment composition and the origin of fatty acids. Substrate cover and sediment composition data were obtained from a parallel study in the same streams (dos Reis Oliveira et al., submitted). Substrate cover was determined by the relative amount of woody debris, macrophytes, CPOM (coarse particulate organic matter) and FPOM (fine particulate organic matter) on the sediment, estimated according to Hering et al.

(2003) in a 20 m stream stretch.

To determine sediment composition, a subsample of ball-milled sediment was taken for organic matter content (OM), total carbon (C), total nitrogen (N) and 91

CHAPTER 7

analysed for sediment characteristics.

CHAPTER 6

were freeze-dried (CoolSafe 55-9 Pro) directly after sampling and subsequently

Chapter 5

chlorophyll-a content (Chla) measurements in each stream. TC and TN were measured using an elemental analyzer (Elementar Vario EL, Hanau, Germany) and OM by loss of weight-on ignition of oven dried (105°C) material at 550 °C for 16 hours. Sediment chlorophyll–a concentrations were quantified according to Porra et al. (1989) and CHAPTER 1

Brito et al. (2009), and the respective concentrations were calculated using Lorenzen’s

CHAPTER 2

extracted

equation (Lorenzen, 1967).

Fatty acids origin was determined by first weighing 2 sets of 1 g sediment, by

accelerated

solvent

extraction

(ASE)

and analysed by gas

chromatography-mass spectrometry (GC/MS), performed on a ThermoQuest Trace GC 2000 gas chromatograph connected to a Finnigan Trace MS quadrupole mass spectrometer, according to Jansen et al. (2006). Peak areas for individual fatty acids

CHAPTER 3

were identified and quantified using the Xcalibur program (version 1.0.0.1). The origin of fatty acids from various organisms can be identified by the carbon chain length and by the level of unsaturation. Firstly, fatty acids from microbial origin (FA micro) were categorized as the sum of the short carbon chain fatty acids (C14 to C18) (Napolitano, 1999; Bianchi and Canuel, 2011), while plant derived fatty acids (FA plant) were

CHAPTER 4

considered to be the sum of the long carbon chains (C22 to C32) (Meyers and Ishiwatari, 1993; Bianchi and Canuel, 2011). Secondly, the autotrophic or heterotrophic nature of the microbial fatty acids was determined (Whatley et al., 2014). Here, heterotrophic microbial fatty acids were identified by summing the

CHAPTER 5

saturated and branched fatty acids, while fatty acids originating from autotrophic microbes were categorized as the sum of monounsaturated and polyunsaturated fatty acids. Subsequently, the ratio between heterotrophic/autotrophic microbial fatty acids (SB/MP) was calculated per stream.

CHAPTER 6

2.4 Macroinvertebrate community composition In each stream, four replicate macroinvertebrate samples were taken from deposition zones using a Surber sampler (surface area: 625 cm2; mesh size: 0.5 mm).

CHAPTER 7

Within 48 hours, the collected organisms were sorted and identified to the genus level. Species richness (number of taxa), Shannon–Wiener diversity index, relative abundance of Ephemeroptera, Plectoptera and Trichoptera (EPT) individuals, EPT richness, the relative abundance of Oligochaete individuals (O), the sum of the relative abundance of Oligochaeta and Chironomidae individuals (O + Ch) and the total number of Chironomus sp. individuals divided by the total number of Chironomidae (C/Ch) were calculated. In addition, all individuals were classified according to their functional feeding traits according to the autecological database for freshwater 92

The landscape drives the stream

organisms, version 7.0, accessed on 01.02.2019 (www.freshwaterecology.info), and subsequently the relative abundances of the different functional feeding groups

To evaluate whether sediment characteristics were land use specific, logtransformed data of substrate cover of woody debris, macrophytes, CPOM (coarse particulate organic matter) and FPOM (fine particulate organic matter), OM content, C/N ratio, chlorophyll-a, and microbial and plant derived fatty acid content and the SB/MP ratio were included in a PCA, performed in CANOCO for Windows version 5.12 (ter Braak and Smilauer, 2002).

CHAPTER 2

2.5 Data analyses

CHAPTER 1

(Moog, 1995) were calculated.

separately using one-way analysis of variance (ANOVA), followed by a Tukey post hoc test (R-package stats). In the cases where the conditions of data normality (Shapiro– Wilk test) and homogeneity of variances (Levene’s test) were violated, differences

CHAPTER 3

Differences in fatty acid origin between land use types were tested

To test the differences between microbial and plant derived fatty acids content per land use type, T-tests were used.

Differences in macroinvertebrate community indexes and functional feeding groups between land use types were tested using a linear mixed effect model with land use type and within stream location as fixed effects and stream surber replicates

CHAPTER 5

followed by a Mann-Whitney pairwise comparison test (R-package multcompView).

CHAPTER 4

between means were evaluated using the non-parametric Kruskal–Wallis test,

To evaluate how much of the variance in macroinvertebrate community composition was explained by the sediment characteristics, linear models (multiple regression, assuming Gaussian errors) were formulated, fitted and validated according to Burnham and Anderson (2002) using data from the 20 studied streams. The macroinvertebrate biotic indices and functional feeding group classes were considered as response variables, and sediment characteristics as predictor variables.

Predictor variables were categorized as substrate cover (macrophyte, woody debris, CPOM, FPOM), sediment composition (OM content, C/N ratio, chlorophyll-a concentration) and sediment fatty acid origin (microbial, plant and SB/MP). For each group of predictor variables, models were constructed with all possible combination of parameters. The Akaike Information Criterion (AIC) was used to select the best 93

CHAPTER 7

2017).

CHAPTER 6

as random effect (R-packages lmertest and emmeans) (Kuznetsova and Brockhoff,

Chapter 5

statistical models. Models were considered adequate and retained when differing less than 2 AIC from the model with the lowest (best) AIC value. In the resulting model ensemble, the mean of adjusted R2 (R2adj) was determined as a measure to explain the variation of macroinvertebrate community composition according to sediment CHAPTER 1

characteristics. Within each group of sediment characteristics, the importance of the contributing parameters was determined by calculating their relative frequency of occurrence in the model ensembles. All analyses were performed in R (R Core Team 2015), using functions from the packages plyr, reshape, rpart (Wickham, 2007;

CHAPTER 2

Wickham, 2009; Wickham, 2011; Therneau and Atkinson 2018).

3. Results 3.1 Sediment characteristics

CHAPTER 3

In the PCA ordination of the sediment characteristics, the total variance explained was 31.9%, of which 73 % was explained by the first two axis together. On axis 1, all forest streams were grouped, positively related to woody debris, CPOM substrate cover, and C/N ratio. All agricultural and WWTP streams were grouped on

CHAPTER 4

the opposite side of axis 1, related to macrophyte cover. On axis 2, WWTPs were positively related to microbial derived fatty acids. Most of the agricultural streams were clustered on the opposite side of axis 2, related to plant derived fatty acids and FPOM (Figure 1 and Table S1 in sup. material). Overall, axis 1 separated sites where

CHAPTER 5

the organic matter source was either allochthonous or autochthonous, and axis 2 separated sites where the organic matter originated either from autotrophic or from heterotrophic organisms.

CHAPTER 6 CHAPTER 7 94

1.0

The landscape drives the stream

19 %

WWTP2

FA_micro Forest2

WWTP4

Macrophytes Crop1

Forest1

WWTP1

SB_MP

Forest3

EG2 EG1 Crop3

Woody debris CPOM

54 % Crop4

Forest4

CHAPTER 2

EG4

CHAPTER 1

WWTP3

IG3

FA_plant

OM IG1

Clha

FPOM

-1.0

IG4

1.0

-1.0

Figure 1: PCA biplot for ordination of sediment characteristics in 4 replicate streams per land use type (forest, EG - extensive grassland, IG - intensive grassland, Crop - cropland and WWTP).

3.2 Sediment fatty acid origin Microbial derived fatty acids content was significantly (p < 0.05) higher in WWTP streams than in EG and IG streams (Figure 2A). Oppositely, in EG and IG streams, plant derived fatty acids content was significantly (p < 0.05) higher than in

CHAPTER 4

CHAPTER 3

CN

CHAPTER 5

Crop2

IG2

CHAPTER 6

EG3

Microbial derived fatty acid content was significantly higher than plant derived fatty acids content in forest (p < 0.05) and WWTP (p < 0.05) streams, while plant derived fatty acids content was significantly higher than microbial fatty acid content in EG streams (p < 0.05) (Figure 2C). The ratio heterotrophic/autotrophic microbial fatty acids (SB/MP) was higher in WWTP and cropland streams than in forest, EG and IG, but these differences were not significant (Figure 2D).

95

CHAPTER 7

WWTP streams (Figure 2B).

Chapter 5

B

A b

a

ab

ab

a ab

CHAPTER 1

a a ab

CHAPTER 2

b

CHAPTER 3

*

WWTP

WWTP

C

D

*

*

CHAPTER 4 CHAPTER 5

WWTP

WWTP

CHAPTER 6 CHAPTER 7

Figure 2: Mean microbial (A) and plant (B) derived fatty acid contents measured in 4 replicate streams per land use type (forest, extensive grassland - EG, intensive grassland - IG, Crop â&#x20AC;&#x201C; cropland and WWTP), the comparison between microbial and plant derived fatty acid content per land use type (C), and the heterotrophic/autotrophic microbial fatty acids ratio (SB/MP) (D).

Different letters indicate a significant difference between the means per land use type (p < 0.05, analyses of variance followed by multiple comparison test). Asterisks indicate a significant difference between plant and microbial derived fatty acids for each land use type (p < 0.05).

3.3 Macroinvertebrate community composition 3.3.1 Abundances and indices WWTP streams were characterized by a significant (p < 0.05) higher total macroinvertebrate abundances compared to the streams of the other land use types, except for forest. In IG streams, the Shannon-wiener diversity was significantly (p < 96

The landscape drives the stream

0.05) higher than in cropland and WWTP streams. Forest streams showed the highest EPT scores, significantly (p < 0.05) higher than in the IG and WWTP streams, while also EPT richness was highest in forest streams, significantly (p < 0.05) higher than in all

IG

cropland

WWTP

218 (98) a

281 (136) a

307 (149) a

723 (518) b

(6.5) a

(5.4) a

19.2

(7.4) a

19.4

Shannon-Wiener diversity 1.94 (0.44) ab EPT

0.20 (0.25)

EPT richness

6.8 (3.9) a

a

0.12

O + Ch

0.47 (0.24) a 0.01 (0.02)

24.4

1.89 (0.68) ab 0.15 (0.11)

ab

5.3 (2.4) b

(0.04) a

O

C/Ch

(5.8) a

a

0.11

2.33 (0.3) a 0.01 (0.01)

0.24

0.20 (0.11) b

0.02 (0.02)

0.11 (0.19)

a

1.3 (1.5) b

(0.21) a

0.44 (0.26) a

ab

19.3 (10.2) a

1.68 (0.44) bc b

3.3 (1.7) b

(0.05) a

0.12 (0.14)

19.1

a

0.35

0.01 (0.01) b 2.8 (2.2) b

(0.34) a

0.44 (0.32) ab 0.34 (0.09)

1.17 (0.69) c

b

0.51 (0.32) b 0.58 (0.35) a 0.52 (0.44) c

3.3.2 Functional feeding groups The macroinvertebrate functional feeding groups composition differed between land use types. The relative abundance of grazers was significantly (p < 0.05) higher in cropland than in forest and WWTP streams. Shredder numbers were significantly (p < 0.05) higher in EG streams than in cropland streams. Gatherers showed significantly (p < 0.05) lower relative abundances in EG streams. Relative abundances of active filter feeders (AFF) were significantly (p < 0.05) higher in EG streams than in all other streams, except for cropland streams. Passive filter feeder relative abundances (PFF) were significantly (p < 0.05) lower in forest streams than in EG and WWTP streams.

97

CHAPTER 2

EG

400 (581) ab

CHAPTER 3

Total number of taxa

forest

CHAPTER 4

Abundance

CHAPTER 5

Table 1: Mean (n = 4, Âą sd) macroinvertebrate community indices per land use type. EPT is the relative abundance of Ephemeroptera, Plecoptera and Trichoptera individuals; O is the relative abundance of Oligochaete individuals; O + Ch is the relative abundance of Oligochaeta and Chironomidae; C/Ch is the total number of Chironomus sp. individuals divided by the total number of Chironomidae (C/Ch). Different letters indicate a significant difference between the means (p < 0.05, analyses of variance followed by multiple comparison test).

CHAPTER 6

0.05) higher numbers of Chironomus sp. (C/Ch) (Table 1).

CHAPTER 7

abundances of Oligochaeta. cropland and WWTP streams contained significantly (p <

CHAPTER 1

other streams. WWTP streams were characterized significantly (p < 0.05) by higher

Chapter 5 Table 2: Mean (n = 4, ± sd) relative abundance of functional feeding groups. Different letters indicate a significant difference between the means per land use type (p < 0.05, analyses of variance followed by multiple comparison test). forest (4.5) ac

EG

cropland

WWTP 14.8 (4.5) c

CHAPTER 1

miners

0 (0)

0 (0.1)

0 (0)

0 (0.1)

0 (0)

xylophagous

0 (0)

0 (0)

0 (0)

0 (0)

0 (0)

16.4

12

(7.7) ab

24.3

(10.9) b

9.4

(14.9) a

15.1

(4) bc

grazer

(8.4) ab

17.6

IG (13.5) abc

5.6

(4.5) b

12.4 (13.4) ab

CHAPTER 2 CHAPTER 3

shredders

14.7

gatherers/ collectors

52.5 (13.5) a

29.2 (10.9) b

49.7 (12.1) a

45.6 (11.1) a

54.5 (20.1) a

active filter feeders

10.8 (9.2) ac

20.8 (15.7) b

7 (5.3) ac

12.8 (9.6) ab

2.6 (3.6) c

passive filter feeders

0.6 (0.5) a

1.7 (1.1) b

0.9 (0.4) ab

1.3 (0.8) ab

1.5 (1.2) b

predators

11.4 (6.0)

12.4 (8.0)

13.7 (8)

9.2 (5.1)

7.3 (10.3)

parasites

0.5 (1.5)

0.0 (0.1)

0 (0)

0 (0.1)

0.1 (0.2)

other

0.1 (0.2) a

1.9 (3.6) a

1.4 (1.7) a

1.2 (1) a

6.7 ( 8.6) b

3.4 The relationship between sediment characteristics and macroinvertebrate CHAPTER 4

community composition To evaluate the relation between macroinvertebrate community composition and the sediment characteristics in terms of food resources and habitat structure, GLM analyses were performed. One third of the macroinvertebrate community

CHAPTER 5

composition expressed by the Shannon-Wienner diversity index was explained by sediment fatty acids origin (Figure 3A). Fatty acids origin was the response variable that better explained macroinvertebrate community indexes: 32 (±3) % of the Shannon-Wienner diversity, 21 (±1) % of Oligochaeta abundances, 15 (±1) % of the C

CHAPTER 6

/Ch ratio and 16 (±1) % of total richness (Figure 3A). Sediment composition explained worm abundances (24 ±1 %) and the C/Ch ratio (18 ±3 %), where in both cases the C/N ratio occurred in all models (Table 3). Sediment cover better explained EPT richness (20 ±2%) and total richness (18 ±6 %), where for EPT richness the woody

CHAPTER 7

debris substrate cover occurred in all models, while for total richness the FPOM cover occurred in all models (Table 3).

When functional feeding groups were used as response variable, sediment characteristics explained no more than 15% of miners, passive and active filter feeders variation (Figure 3B). The highest R2adj was related to the occurrence of active filter feeding individuals in relation to fatty acid origin of the sediment. Concerning the most abundant functional feeding groups (gatherers, grazers and shredders, Table 1), 98

The landscape drives the stream

only 2% of the occurrence of gatherers was explained by FA. For grazers, sediment composition explained 10%, where C/N ratio was present in all models (Table 3). For shredders, sediment cover explained 7 %, where C/N ratio was present in all models (Table 3, Figure 3B).

Richness

0.25

Shannon-Wiener

0.20

EPT

0.15

EPT_rich

0.10

O + Ch

0.05

C/Ch O

0.00 FA

others

0.35

0.15

passive filter feeders active filter feeders gatherers

0.10

shredders

0.05

miners

0.20

grazer

0.00 Substrate cover

Sediment composition

FA

Figure 3: Mean (n = number of models in Table 3, Âą sd) R 2 adj of the models ensemble for three food composition response variables: substrate cover, sediment composition and fatty acids origin (FA) explaining the macroinvertebrate community composition indeces (a) and functional feeding groups (b) observed in 20 lowland streams.

99

CHAPTER 6

predators

0.25

CHAPTER 5

parasites

0.30

R2adj

CHAPTER 4

Substrate cover Sediment composition

CHAPTER 7

R2 adj

0.30

CHAPTER 2

Abundance

CHAPTER 3

0.35

CHAPTER 1

A

B

Chapter 5 Table 3: Number of models present in the in ensemble (model) and the fraction of the models in which the variables (FA micro, FA plant; sediment composition: C/N, Chla, OM %; and substrate cover: macrophyte, wood, CPOM and FPOM) were present per variable.

Response variable

Predictor variable

CHAPTER 1

Sediment cover

Sediment composition

CHAPTER 3 CHAPTER 4 CHAPTER 5

Functional feeding groups

CHAPTER 2

Macroinvertebrate indices

macromodel phyte wood CPOM FPOM model CN Abundance

7

0.29

Richness

3

0.33

0.29

ShannonWiener

7

0.43

0.43

EPT

3

0.67

1.00

EPT_rich

3

0.33

1.00

O

7

0.29

0.43

O + Ch

7

0.57

0.29

C/Ch

9

0.67

oth

9

0.44

par

4

0.25

0.75

pre

4

1.00

0.25

0.25

pff

4

1.00

0.25

aff

7

0.57

0.29

gat

7

0.29

shr

4

0.50

min

7

gra

5

Fatty acids

Clha OM model Micro Plant

0.29

0.57

3

1.00 0.30 0.30

3

0.50

0.50

0.67

1.00

5

0.40 0.60 0.40

2

0.50

0.50

0.14

0.43

4

0.75 0.50 0.25

2

0.50

0.50

0.33

5

0.40 0.60 0.40

2

0.50

0.50

0.33

5

0.40 0.40 0.60

2

0.50

0.50

0.29

0.43

3

1.00 0.33 0.33

2

0.50

0.50

0.29

0.29

4

0.50 0.75 0.25

2

0.50

0.50

0.44

0.33

0.33

3

1.00 0.33 0.33

2

0.50

0.50

0.33

0.33

0.67

3

1.00 0.33 0.33

2

0.50

0.50

0.50

5

0.40 0.60 0.40

2

0.50

0.50

0.25

5

0.60 0.40 0.40

2

0.50

0.50

0.25

0.25

3

1.00 0.33 0.33

2

0.50

0.50

0.29

0.29

5

0.40 0.40 0.60

2

0.50

0.50

0.29

0.29

0.57

5

0.60 0.40 0.40

2

0.50

0.50

0.50

0.25

1.00

5

0.60 0.40 0.40

2

0.50

0.50

0.29

0.43

0.29

0.43

4

1.00 0.50 0.50

2

0.50

0.50

0.20

0.60

0.20

0.80

3

1.00 0.33 0.33

2

0.50

0.50

4 Discussion

CHAPTER 6

In this study, sediment characteristics in terms of food resources and habitat structure included the categories substrate cover, sediment composition and sediment fatty acid origin. Below, we discuss the differences in sediment characteristics between land use types and evaluate the effects on benthic macroinvertebrate community composition.

CHAPTER 7

4.1 Land use type specific sediment characteristics Land use type determined the characteristics of the sediments in the deposition zones of the studied lowland streams, in line with other studies (Delong and Brusven, 1998; Quinn, 2000; Rosi-Marshall, et al., 2016). In the forest streams, the input of leaves and woody debris from the surrounding terrestrial ecosystem largely determined the sediment characteristics in terms of food resources and habitat structure, composed by microbial derived fatty acids and having a high C/N ratio.

100

The landscape drives the stream

Sediment C/N ratio is a reliable indicator of food quality in benthic ecosystems, as higher ratios are associated with streams in catchments with less anthropogenic impacts, as well as a higher food web stability (dos Reis Oliveira et al., 2018; Lu et al., use types, the composition of the sediments differed, shifting to a prevalence of autochthonous organic matter. In grassland streams, macrophyte-derived food was dominant, as a result of increased nutrient concentrations in the sediment and a high

CHAPTER 1

2014; Rooney and McCann, 2012). In contrast, in the anthropogenically exploited land

development of autotrophic organisms (Jones et al., 2014; Vermaat and de Bruyne, 1993), and heterotrophic microbes served as food source instead. In WWTP streams, the food present in the sediment mainly consisted of heterotrophic microbes growing on top of the sediment, as a result of high concentrations of nutrients released from the WWTP (Battin et al., 2016). Our results are in line with Johnson et al. (2009), who also observed that land-use specific organic matter input determined autotrophic and heterotrophic biofilm development on stream bottom substrates. Therefore, shifts from allochthonous to autochthonous resources in the diets of macroinvertebrates is not only a river continuum effect (Vannote et al., 1980) or seasonal variation (Hunt et al., 2012), but is also determined by anthropogenic activities in a land use type specific way.

4.2 The relationship between sediment characteristics and macroinvertebrate

CHAPTER 3

sediment of the cropland streams, the water turbidity in these streams hampered the

CHAPTER 4

production than forest streams. Despite the high nutrient concentrations in the

CHAPTER 5

streams located in agricultural grasslands were characterized by a higher primary

CHAPTER 2

light incidence. Likewise, Finlay (2011) and Mulholland et al. (2008) also showed that

In line with the differences in sediment characteristics, macroinvertebrate community composition also differed per land use type. Responses of the macroinvertebrate communities to these differences in sediment characteristics were

CHAPTER 6

community composition

food selection, production efficiency, biomass and ultimately population growth rate (Bianchi and Canuel, 2002). Indeed, in the present study the woody debris substrate cover, the C/N ratio and the fatty acid origin all influenced macroinvertebrate community composition. The fatty acids composition better explained the macroinvertebrate Shannon-Wiener diversity giving valuable insights into the food and energy sources available for aquatic invertebrates (Vonk et al., 2016). In contrast to the community metrics, functional feeding groups were barely related to sediment food composition. In spite of the many attempts to categorize macroinvertebrates 101

CHAPTER 7

expected, because consumers react to food composition by changing feeding rates,

Chapter 5

into functional feeding groups, in practice, most macroinvertebrates are omnivores, feeding on different types of food, either fresh or dead organic matter derived from various sources ranging from animals to bacteria (Figueroa et al. 2019). Only in cases of excess food availability the species-specific food preferences may be more CHAPTER 1

pronounced. Below, we discuss the relationship between sediment characteristics and

CHAPTER 2

matter characterized by a high C/N ratio, also more EPT taxa were observed. EPT

macroinvertebrate community composition per land use type.

In forest streams, containing more allochthonous plant derived organic species may take advantage of the presence of the high quality heterogeneous substrates within the wood and CPOM patches, conform Besemer et al. (2009) and Boyero et al. (2011), who argued that heterogeneous substrates support a higher food

CHAPTER 3

resource diversity. Moreover, Von Bertrab et al. (2013) reported that high C/N ratio together with oxygen availability explained the occurrence of EPT taxa. In contrast to the forest areas, in human impacted streams autochthonous organic matter dominated the sediment characteristics. Here, macroinvertebrate community composition varied from a high Shannon-Wiener diversity when the organic matter

CHAPTER 4

was plant derived, such as in the grassland streams, to high abundances of Oligochaeta and Chironomus sp. when the organic matter consisted of heterotrophic microbes with a low C/N ratio, such as in the WWTP and cropland streams. Hence, macroinvertebrate community composition was influenced by the type of organic

CHAPTER 5

matter in the sediment, being either allochthonous or autochthonous and when

CHAPTER 6

characteristics and community composition, sediment characteristics are obviously

autochthonous being either autotrophic or heterotrophic.

Yet, in spite of the presently observed relation between sediment not the only driver of community composition. As a result of the intermingled relationship between oxygen, habitat quality and sediment characteristics, these three key elements probably shape ecosystem structure in concert. In forest streams,

CHAPTER 7

heterogeneous allochthonous organic matter, higher oxygen concentrations and structural habitat availability jointly supported higher numbers of EPT taxa. Yet, the woody debris substrate cover better explained EPT richness, even though no xylophagous species were present. These observations are in strong agreement with Wallace et al. (2015), demonstrating that the addition of physical structures alone in absence of the appropriate detrital food sources did not restore macroinvertebrate communities after anthropogenic disturbance. In the grassland streams the highest Shannon-Wiener diversity was observed. Here, sediment fatty acids were mainly plant 102

The landscape drives the stream

derived, no harsh oxygen conditions occurred (dos Reis Oliveira et al. submitted) and a suitable structural habitat for many macroinvertebrate species was provided by the macrophytes (Whatley et al., 2014), jointly sustaining a high biodiversity. Oligochaeta feeding on heterotrophic microbial derived food. Worms and chironomids however, do not have to feed exclusively on such heterotrophic microbes, but they do survive the low sediment oxygen concentrations caused by the high respiration rate of the

CHAPTER 1

and Chironomus sp. were abundantly present in the WWTP and cropland streams,

and persist under these conditions (dos Reis Oliveira et al. 2018; de Haas et al. 2005).

It is thus argued that oxygen, habitat quality and sediment characteristics shape ecosystem structure in concert. Hence, sediment food quality does not drive macroinvertebrate community composition to the same extent as oxygen (e.g.

Jacobsen, 2008), habitat heterogeneity (Burdon et al., 2013; Whatley et al., 2014) and stream velocity (e.g. White et al., 2017) do, but if the minimum requirements of the other ecological parameters are fulfilled, sediment characteristics can certainly be

CHAPTER 7

CHAPTER 6

CHAPTER 5

CHAPTER 4

considered as a key ecological filter.

CHAPTER 3

excluding many other species. This way they can take advantage of the excess of food

CHAPTER 2

microbial activity in the top layer of the sediments (Stewart and Franklin, 2008),

103

Chapter 5

Supplementary material

Substrate cover

CHAPTER 2 CHAPTER 3

Sediment composition

CHAPTER 1

Table S1: Sediment composition of the deposition zones (organic matter content (OM %), content carbon/nitrogen ratio (C:N), chlorophyll–a (chla)) and substrate cover (in % estimated according to Hering et al. 2003) are given as means per land use type (n = 4 replicate streams).

Standard deviations are given between brackets. Letters indicate a significant difference between land use types (p < 0.05) based on analyses of variance followed by multiple comparison test (dos Reis Oliveira, submitted). forest

EG

IG

cropland

WWTP

Woody debris (%)

6.6 (2.8)

0 (0)

0 (0)

0 (0)

0 (0)

Macrophytes (%)

0 (0)

52.1 (30.6)

8.7 (8.0)

27.4 (29.0)

34.4 (28.9)

CPOM (%)

38.8 (23.1)

0 (0)

0 (0)

0 (0)

0 (0)

FPOM (%)

25.4 (11.9)

46.7 (29.6)

ab

46.7 (19.7)

a

a

72.9 (29.6) a

27.1 (34.2)

OM (%)

3.0 (0.6)

7.7 (5.2)

7.9 (6.3)

14.4 (11.5)

1.4 (0.3)b

C/N

20.4 (2.6)a

17.8 (1.5)ab

17.9 (2.8)ab

16.6 (1.1)bc

13.9 (1.3)c

Chla (mg/g)

6.7 (7.9)a

5.6 (2.1)a

41.1 (30)b

9.2 (9)ab

5.9 (5.2)a

CHAPTER 4

Acknowledgements: We would like to thank the water authorities Hunze en Aa’s and Vallei en Veluwe, João Lotufo and Evan for their help in the field. Thijs de Boer for helping with GIS, and Dorine Dekkers for her help in macroinvertebrate identification.

CHAPTER 5

We thank laboratory technicians Mariska Beekman and Samira Absalah. PCRO received funding from CNPq Brazil (grant number 200879/2014-6, 2014).

CHAPTER 6 CHAPTER 7 104

105

Chapter 6 Lowland stream restoration by sand addition: impact, recovery and beneficial effects on benthic invertebrates Paula C. dos Reis Oliveira Michiel H. S. Kraak Piet F. M. Verdonschot Ralf C. M. Verdonschot

Published in River Research and Applications 3465 (2019): 1-11

Author contributions: PCRO, PFMV and RCMV designed the experiment. PCRO and RCMV conducted the experiment. PCRO analysed most of the data, and wrote most of the manuscript together with PFMV, RCMV and MK. PFMV and RCMV advised on practical issues during the course of the experiment and data processing. MK, PFMV and RCMV contributed to editing and revising draft versions of the manuscript.

The landscape drives the stream

Abstract Up to now, most lowland stream restoration projects were unsuccessful in terms of ecological recovery. Aiming to improve the success of stream restoration channel incision was launched, consisting of the addition of sand to the stream channel in combination with the introduction of coarse woody debris. Yet, it remained unknown whether this novel measure of sand addition is actually effective in terms of

CHAPTER 1

projects, a novel approach to restore sandy-bottom lowland streams degraded by

composition were measured. The response of the macroinvertebrate community composition was determined at different stages during the disturbance and shortterm recovery process. Immediately downstream the sand addition site, transport and sedimentation of the sand was initially intense, until an equilibrium was reached and the physical conditions stabilized. The stream section matured fast as habitat formation took place within a short-term. Macroinvertebrate diversity decreased initially, but recovered rapidly following stabilization. Moreover, an increase in rheophilic taxa was observed in the newly formed habitats. Thus, although sand addition initially disturbed the stream, a relatively fast physical and biological recovery occurred, leading to improved instream conditions for a diverse macroinvertebrate community, including rheophilic taxa. Therefore, we concluded that sand addition is a promising restoration measure for incised lowland streams.

CHAPTER 3

transport, water depth, current velocity, dissolved oxygen dynamics and sediment

CHAPTER 4

leading to an increase in macroinvertebrate biodiversity. To this end, particle

CHAPTER 5

sand addition can improve hydromorphological stream complexity on the short-term

CHAPTER 2

biodiversity improvements. The aim of the present study was therefore to evaluate if

rheophilic species, sand addition, sedimentation 1. Introduction

CHAPTER 6

Key words: channel incision, instream habitat restoration, macroinvertebrates,

profound effect on the natural hydromorphological processes in many streams around the world (Simon, 1989). As a consequence, natural streams became homogenized channels, with high discharge dynamics (floods and droughts) and low substrate loads (Bartley and Rutherfurd, 1999). Particularly in lowland areas, many streams were straightened (Verdonschot and Nijboer, 2002), and the subsequent channelization and water table regulation led to a decrease in sediment supply and an increase in particle transport (Bukaveckas, 2007), jointly causing streambed incision.

This channel incision negatively affects streambed and bank heterogeneity (Lau et al., 107

CHAPTER 7

Channelization, embankment and water table regulation by weirs have a

Chapter 6

2006; Simon and Rinaldi, 2006) and isolates the aquatic from the terrestrial ecosystems (Bartley and Rutherfurd, 1999), resulting in both habitat and biodiversity losses (Downes et al., 1995).

CHAPTER 1

The importance of recovering the natural hydromorphological complexity and land-water connection of channelized streams is widely recognized, leading to the first restoration attempts focusing on small-scale interventions in stream channels and riparian zones (Lake, 2007). It was assumed that due to stream morphology

CHAPTER 2

restoration by physical habitat improvements, species would return and ecological functions would be re-established (Jähnig et al., 2010; Palmer et al., 2005; Pander and Geist, 2013). Yet, despite the diverse options for stream morphology restoring measures (Brookes and Shields, 1996), up to now, most restoration projects were not

CHAPTER 3

very successful in terms of ecological recovery (Palmer et al., 2005).

Aiming to improve the success of stream restoration projects, a novel approach to restore sandy-bottom lowland streams degraded by channel incision was launched by water and nature managers, which consists of the addition of sand to the

CHAPTER 4

stream channel in combination with the introduction of coarse woody debris.

Although sand inputs are generally recognized as a stressor in high-gradient gravelbed streams and rivers (e.g. Rosenfeld et al., 2011), in low-gradient streams sand is the natural dominant substrate. Hence, instead of a posing a threat, the addition of

CHAPTER 5

sand might actually improve the ecological quality of incised lowland streams. Sand addition may increase streambed height and heterogeneity through hydraulic changes, and may restore the link between the stream and the surrounding terrestrial ecosystems by producing a wider and shallower streambed (Lisle, 2008). It is expected

CHAPTER 6

that by decreasing the channel dimensions over a relatively large spatial scale inundation of the stream valley during spates would be stimulated, resulting in less streambed erosion and in turn an increase in instream hydromorphological habitat heterogeneity that sustains a higher biodiversity. By reconnecting the stream to its

CHAPTER 7

valley, it is anticipated that land-water gradients can recover, revitalizing both the stream and the riparian zone (Pilotto et al., 2018). Yet, it is not known whether this novel measure of sand addition is actually effective in terms of biodiversity improvements. The aim of the present study was therefore to evaluate if sand addition can improve hydromorphological stream complexity leading to an increase in macroinvertebrate biodiversity.

108

The landscape drives the stream

Directly after the sand addition, the sand movement disturbs the stream ecosystem, after which physical and biological recovery are expected to take place, improving habitat heterogeneity and macroinvertebrate diversity. Our hypothesis was

To study the short-term instream physical changes induced by sand addition and the effects on the receiving stream ecosystem, sediment traps were installed to measure particle transport. Additional effects on depth, current velocity, sediment composition, and effects on dissolved oxygen were regularly measured. Furthermore, macroinvertebrate community composition was determined at different phases of the sand addition and the short-term recovery processes.

2. Materials and methods

CHAPTER 2

recovery of habitats and macroinvertebrate biodiversity.

CHAPTER 3

therefore our research efforts were concentrated on studying the initial instream

CHAPTER 1

that recovery after the initial disturbance takes place within a short time span and

m/km (0.13 %) (de Klein and Koelmans, 2011). The stream is a typical low-gradient, slow-flowing, sand-bed lowland stream, with an average daily discharge of 0.23 m3.s1 (1994-2018), an approximate width of 4 meters and a maximum depth of 1 meter.

The stream channel is fully shaded by deciduous and coniferous forest. For further description of the studied stream, see Verdonschot et al. (2015).

Historical changes in upstream land use, in which peat marshes were drained and turned into agricultural grassland and cropland, in combination with channelization and regulation of most of the stream has resulted in a channel incision

CHAPTER 5

Hierdense stream catchment, which is characterized by sandy soils and a slope of 1.3

CHAPTER 6

The sand addition experiment took place in the Leuvenumse stream (52°19′08’’N, 5°42′24’’E), the Netherlands. The Leuvenumse stream is part of the

CHAPTER 4

2.1 Study area

CHAPTER 7

up to 1 meter in the downstream forested stretch in which the present study was executed.

2.2 Outline of the study Sand was added at 7 sites along a 3 km stretch (Fig. 1, Fig. A3 in supplementary material). Upstream channelized incised stretches were used as controls, positioned upstream of the sand addition sites.

109

Chapter 6

The sand originated from a nearby drift sand rehabilitation project (Hulshorsterzand), in which the top soil layer was removed to initiate aeolian geomorphic processes. This sand is characterized by a low percentage of organic matter (average 0.4 %) and a small grain size (average phi 2.4). Sand was added on CHAPTER 1

four to seven occasions between 2014 and 2016, by scooping material into the stream channel by an excavator (Fig. 1). On forehand, dead woody debris patches were added to the sand addition sites, as sand retention structures.

CHAPTER 2 CHAPTER 3 CHAPTER 4 CHAPTER 5 CHAPTER 6 CHAPTER 7

Figure 1: Map of the experimental area with the seven sand addition sites (S1â&#x20AC;&#x201C;S7). The total sand added (m3) in 2014â&#x20AC;&#x201C;2016, the number of sand additions to reach this amount (between brackets), and the sampling site per parameter are given.

At each sand addition site, the stream stretch was divided longitudinally into nine plots (Fig 2); four plots upstream (plots I, II, II and IV), four plots downstream (plots VI, VII, VIII and IX) and one plot including the sand entry point (plot V).

110

During the first four weeks after the sand addition, physical stream disturbance was assessed by measuring sediment transport, hydraulic conditions (current velocity, water depth) and proportional substrate cover. After these four

CHAPTER 2

Figure 2: Experimental design at the addition Sites S1â&#x20AC;&#x201C;S7. Each site (approximately 150 m, channel width 4 to 6 m) was divided into nine plots (Iâ&#x20AC;&#x201C;IX).

CHAPTER 1

The landscape drives the stream

percentage organic matter in the deposited sediment were characterized.

Furthermore, oxygen probes were installed to evaluate potential effects of the changed instream conditions on dissolved oxygen saturations. Finally, the response of

CHAPTER 3

weeks, when most of the sand had settled, the nutrient concentrations and

determined.

2.3 Sediment transport, hydraulic conditions and substrate cover

CHAPTER 4

the macroinvertebrate community to the changing instream conditions was

The physical measurements took place in four plots upstream (I, II, III and IV) and four plots downstream of the sand addition site (VI, VII, VIII and IX). Plot V, the actual sand addition site, was not used for measurements, because the huge amount of sand deposited in the stream prevented a proper installation of samplers and measurements.

Each of the eight plots was divided into 33 grid cells of one square meter. In each plot, 14 grid cells were randomly selected: nine for streambed sediment traps (Gordon et al., 2004) and five for suspended sediment traps (Liess et al., 1996) installation. To collect rolling and jumping particles, further indicated as bed-load transport, the streambed sediment traps were placed in such a way that the entrance was at the level of the stream bottom. To collect suspended particles the entrance of the suspended sediment traps was positioned at a height of 15 cm above the stream bottom.

111

CHAPTER 6

measurements, to avoid influencing the other sand addition sites (Figure 1).

CHAPTER 7

most downstream sand addition site (S7) was chosen to perform these

CHAPTER 5

Because the installation of sediment traps disturbed the stream bottom, the

Chapter 6 On July 2, 2015, about 50 m3 of sand was deposited in the stream at site S7 and sediment transport measurements started by opening the pre-installed sediment traps. The exposure time of the sediment traps varied between 18 h and 160 h, in which the exact exposure time depended on the time necessary to collect sufficient CHAPTER 1

particles in the traps to conduct further analyses, but at the same time preventing that the traps would become over-filled with sediment. Measurements were repeated weekly, over a period of four weeks. Current velocity, depth and substrate cover measurements took place weekly as well, just before collecting the sediment traps.

CHAPTER 2

The amount of suspended and bed-load sediment was determined by weighing the amount of sediment collected, after drying at 70ºC to a constant weight.

The data was standardized to grams of particles collected during 24 hours. Particulate

CHAPTER 3

organic matter content of the transported sediment was measured by loss-onignition. After overnight drying at 105°C a standardized 5-g-subsample was taken, burned at 550°C for 16 hours, and weighed again at a precision scale (0.1 mg). Grain size was determined by first wet sieving approximately 20 g of sediment with a 0.063 mm sieve, followed by dry sieving with a set of sieves (1 mm; 0.5 mm; 0.25 mm; 0.125

CHAPTER 4

mm) and weighing the retained material per sieve. Afterwards, the graphic mean was calculated according to Folk (1968).

Discharge was measured daily at a gauging station just downstream of the

CHAPTER 5

sand addition sites in 2014-2016. Current velocity was measured with an electromagnetic sensor (SENSA/ADS, model RC2; v6d) and depth with a ruler. Weekly, substrate composition per plot was estimated visually and the substrate types as defined by Hering at al. (2003) were expressed on a percentage cover scale (0 –

CHAPTER 6

100%).

2.4 Sediment composition and oxygen regime after stabilization of the streambed

CHAPTER 7

Quantification of the sand addition effects on dissolved oxygen regime and deposited sediment organic matter was performed at sand addition site S2, upstream of site S7, to avoid interference with the sediment transport measurements. The site was divided into plots as described in Figure 2 and measurements took place in plots I, IV, V, VI and IX. In August 2015, four weeks after the third sand addition took place, dissolved oxygen concentrations were determined and sediment composition measurements were performed. At this sampling occasion, three replicate sediment samples were 112

The landscape drives the stream

taken from the five plots at site S2, using an acrylic core. The samples were dried at 70ºC, sieved over a 2-mm-sieve and ball-milled for five minutes at 400 RPM. For each sample, sediment composition was measured in duplicate. Particulate organic matter described previously for the transported sediment. Carbon (C), nitrogen (N) and sulphur (S) concentrations were determined using an elemental analyzer (Elementar Vario EL, Hanau, Germany). Total phosphorus (TP) was determined by first igniting

CHAPTER 1

content of the sediment was measured by loss-on-ignition in the same way as

Riley, 1962).

Dissolved oxygen concentration and water temperature were recorded at a 15-minute-interval during three days using Hach LDO dissolved oxygen probes (Hach Company, Loveland, CO, USA), placed just above the streambed in plots I, IV, V, VI and IX of site S2.

2.5 Macroinvertebrate community composition Macroinvertebrates were sampled at five sand addition sites: S1, S2, S3, S4 and S5, in October 2014. The five sites were considered replicates. Four types of plots

CHAPTER 3

was determined by using the colorimetric molybdenum blue method (Murphy and

CHAPTER 4

was extracted with 0.5M sulfuric acid and finally, particulate inorganic phosphorus

CHAPTER 2

one to two grams of sediment at 500°C for 16h, after which the remaining sediment

covered by sand which was slowly moving in downstream direction, representing the initial disturbed situation. 2. Plots just upstream of the sand addition point, where flow obstruction resulting from the sand addition caused siltation. 3. Stabilized plots

CHAPTER 5

were selected at each of the five replicate sand addition sites: 1. Plots recently

From each plot per site, three Surber samples (625 cm2; mesh size: 0.5 mm) were sorted alive in the field (time to scan a sample was standardized to five minutes), identified to family level and pooled. Abundances were estimated using abundance classes (1: 1 individual, 2: 2-5 individuals, 3: 6-25 individuals, 4: 26-100 individuals and 5: >100 individuals). Additionally, species richness (taxa number), Shannon–Wiener diversity index and the Ephemeroptera, Plecoptera and Trichoptera (EPT) richness were calculated. The rheophilic taxa richness was derived using the flow preference classification from the autecological database for freshwater organisms, version 7.0 (Schmidt-Kloiber and Hering., 2015). The size of the autumn species pool for this specific catchment were obtained from Westveer et al. (2018). Based on this 113

CHAPTER 7

ecosystem. 4. Upstream of the five sand addition sites plots were selected as controls.

CHAPTER 6

in the process of habitat formation, representing the recovery phase of the stream

Chapter 6

information, the proportion of the number of rheophilic taxa present in the plots was calculated.

2.6 Statistics CHAPTER 1

Log-transformed data of depth, current velocity, oxygen regime, organic matter, macroinvertebrate abundances and indexes were tested separately using One-way analysis of variance (ANOVA), followed by a Tukey post hoc test (R-package stats). In those cases where the conditions of data normality (Shapiro–Wilk test) and

CHAPTER 2

homogeneity of variances (Levene’s test) were violated, differences between means were calculated using a non-parametric Kruskal–Wallis test, followed by MannWhitney U tests to make pairwise comparisons (Bonferroni corrected) to compare the different plots (R-package multcompView). To evaluate macroinvertebrate community

CHAPTER 3

structure

among

plots

a

multivariate

ordination

procedure,

Non-metric

multidimensional scaling (NMDS), was performed on log-transformed taxonabundance data (R-package Vegan) followed by an analysis of similarities (ANOSIM, Rpackage Vegan) to test differences between sites.

CHAPTER 4

3. Results 3.1 Sediment transport Higher suspended and bed-load sediment transport was observed in the

CHAPTER 5

plots downstream of the sand addition site compared to the upstream plots (Figure 3A, 3B and supplementary Table 1 and 2). During the studied period, there was a tendency of decreasing bed-load sediment transport towards week four in plots VI, VII and VIII, while in plot IX, bed-load sediment transport increased towards week four

CHAPTER 6

(Figure 3B).

In agreement with the lower transport of bed-load sediment upstream, the ratio between bed-load and suspended sediment transport was always lower in the plots upstream to the sand pile (I 1.5 ± 0.8; II 1.7 ± 0.8; III 0.9 ± 0.5; IV 1.5 ± 0.8) in

CHAPTER 7

comparison to the downstream plots (VI 34.7 ± 32.8; VII 13.55 ± 9.1; VIII 10.8 ± 10.9; IX 3.6 ± 3.1; mean and standard deviation were calculated per plot among weeks), where the bed-load transport was at least three times higher than the suspended transport. In the downstream plots (VI, VII, VIII and IX), the contribution of bed-load particles decreased while suspended particles transportation increased gradually towards plot IX.

114

Figure 3: Mean in suspended (a, n = 5) and bedâ&#x20AC;?load (b, n = 9) sediment transport at Site S7.

3.2 Composition of the transported sediment

CHAPTER 3

CHAPTER 2

CHAPTER 1

The landscape drives the stream

the plots upstream of the sand addition site (plots I, II and IV) contained a significantly (p < 0.05) higher organic matter percentage than the sediment transported in the plots positioned downstream of the sand addition site (plots VI, VII, VIII and IX) (Table

CHAPTER 4

Both the suspended sediment and the sediment transported as bed-load in

increased) gradually in the direction of the sand addition site for both suspended and bed-load sediment. The suspended particle grain size was significantly smaller than the bed-load grain size, except in plots VIII and IX, where the suspended and bed-load

CHAPTER 7

CHAPTER 6

grain sizes and organic matter content were similar.

CHAPTER 5

1). In the upstream plots, grain size of the transported material decreased (phi

115

Chapter 6

Table 1: Mean percentage organic matter (OM) and grain size (phi) of suspended (n = 5; Âą 1 sd) and bed-load (n = 9; Âą 1 sd) sediment collected over four weeks after the sand addition. Letters indicate significant differences between the means (p < 0.05).

CHAPTER 1

Plot I

II

III

IV

V

VI

VII

VIII

IX

Suspended

CHAPTER 2

OM %

28.6 (9.7) a 42 (9.8) a

Phi

3.7 (0.7) ab 3.8 (0.5) ab - 4.2 (0.3) a

Grain size very fine classification sand

- 44.3 (6.6) a - 1.3 (0.6) b 1.6 (0.7) b 1.8 (1.3) b 9.5 (13.8) b

very fine sand

Bed-load

- coarse silt -

a

CHAPTER 3

13.1 (8.5)

- 25 (17.3)

Phi

2.2 (0.3) a 2.9 (0.7) ab - 3.5 (0.2) b fine sand -

very fine sand

very fine fine sand fine sand sand

a

OM %

Grain size fine sand classification

23.9 (17)

a

- 3.1 (0.4) ab 3.2 (0.5) ab 2.6 (0.4) b 2.8 (0.2) a

very fine sand

- 1.7 (1.1) b 1.2 (1.5) b 1.5 (2.3) b 8.7 (13.1) ab - 2.5 (0.5) a 2.5 (0.4) a 2.5 (0.2) a 2.8 (0.3) ab - fine sand

fine sand fine sand fine sand

CHAPTER 4

3.3 Hydraulic conditions: discharge, current velocity and water depth The median discharge recorded during the study period (2014-2016) was 0.13 m3.s-1 , ranging from 0.02 to 0.82 m3.s-1 (Figure A1 in supplementary material).

In plots III and IV of site S7, current velocity was always significantly (p < 0.05) lower

CHAPTER 5

(Figure 4A, Table 4 in supplementary material) and depth always significantly (p < 0.05) higher (Figure 4B, Table 5 in supplementary material) than in plot I and all downstream plots, except for plot IX in weeks one and two. Depth decreased significantly (p < 0.05) in the downstream sections (plot VI, VIII and IX) after week one (Figure 4B, Table 5 in supplementary material). In plot IX, the current velocity became

CHAPTER 6

significantly (p < 0.05) higher in week three and four, and depth decreased towards week four (Table 5, supplementary material).

CHAPTER 7 116

3.4 Substrate cover, sediment composition and oxygen regime The proportional substrate cover patterns differed among the plots (Figure 5). Plot I (the upstream control site) deviated from all other plots, having a heterogeneous substrate cover during all four weeks (Figure 5). Substrate cover of plots II-IV (upstream of the sand addition site) was constant as well, but strongly

CHAPTER 6

Figure 4: Current velocity (m/s) (A) and depth (cm) (B) per plot (Iâ&#x20AC;&#x201C;IV upstream and VIâ&#x20AC;&#x201C;IX downstream) at sand addition Site S7 during the first 4 weeks after sand was supplied to the stream channel. The dots represent the sampling points (15 per plot).

CHAPTER 5

CHAPTER 4

CHAPTER 3

CHAPTER 2

CHAPTER 1

The landscape drives the stream

dominated during all four weeks, whilst in plot IX the transition from an organic stream bottom to a sand-dominated situation was observed with sand entering the plot from upstream. Simultaneously, habitat formation took place in plot VI, where the proportional cover of other substrates than sand increased in week four.

After stabilization of the streambed, percentage particulate organic matter, nitrogen, sulphur, carbon and phosphorus concentration and C/N the ratio were all significantly (p<0.05) lower in plots V and VI compared to plot I (Table 3, 117

CHAPTER 7

dominated by FPOM. Plots VI-VIII, downstream of the sand addition site, were sand-

Chapter 6

supplementary material). Dissolved oxygen saturation values were comparable in of these all plots, and were never below 67 % saturation (Figure A2, supplementary material).

CHAPTER 1 CHAPTER 2 CHAPTER 3 CHAPTER 4 CHAPTER 5

Figure 5: Substrate cover (in % evaluated according to Hering et al., 2003) estimated per plot (I‐ IX) over a period of four weeks (W1‐W4) after a sand addition event at site S7.

3.5 Macroinvertebrate community composition The non-metric multidimensional scaling (NMDS) ordination of the

CHAPTER 6

macroinvertebrates

sampled

at

the

5

replicate

sites

showed

that

the

macroinvertebrate community composition of the control and siltation plots were comparable. The plots recently covered by moving sand and those that recovered from the sand addition differed from the control and siltation plots, but also from

CHAPTER 7

each other (Figure 6, ANOSIM: r = 0.54; p = 0.001).

The differences in macroinvertebrate community composition were further expressed by Shannon-Wiener diversity and rheophilic taxa richness. Diversity and total richness were significantly (p < 0.05) lower in the plots recently covered by sand, while rheophilic taxa richness was significantly (p < 0.05) higher in the recovering plots (Figure. 7; Table 6, supplementary material). Moreover, in the recovered plots on average 25.3 % of all rheophilic taxa occurring in the streams’ catchment, and 30% of 118

The landscape drives the stream

the taxa recorded in the stream were collected. These numbers were significantly (p <

CHAPTER 5 CHAPTER 7

CHAPTER 6

Figure 6: Nonmetric multidimensional scaling (NMDS) ordination of macroinvertebrate community (stress = 0.19; two dimensions; nonmetric fit R2 = 0.96; linear fit R2 = 0.81), at Sites S1 to S5. Contour polygons group the assemblages of comparable plots in the ordination. Plot abbreviations: C, control; Rec., recovered stabilized; Sand, recently covered by moving sand; Silt, siltation.

CHAPTER 4

CHAPTER 3

CHAPTER 2

CHAPTER 1

0.05) higher in comparison to the other plot types (Table 6, supplementary material).

119

Chapter 6

a

A

a

b

B

a

a

CHAPTER 1

a b a

CHAPTER 2 CHAPTER 3

a

a

a

C

CHAPTER 4

b

CHAPTER 5

Figure 7: Mean Shannonâ&#x20AC;&#x201C;Wiener diversity (A), rheophilic taxa richness (B), and total richness (C) (n = 5), at Sites S1 to S5. Letters indicate significant differences between the means (p < .05).

CHAPTER 6

4. Discussion Aiming to improve the success of stream restoration projects, a novel approach to restore sandy-bottom lowland streams degraded by channel incision was

CHAPTER 7

launched, but it remained unknown whether this novel measure of sand addition is actually effective in terms of biodiversity improvements. The aim of the present study was therefore to evaluate if sand addition can improve hydromorphological stream complexity on the short-term leading to an increase in macroinvertebrate biodiversity, as discussed below.

120

The landscape drives the stream

4.1 Hydromorphological effects of sand addition As a novel restoration measure, large amounts of sand were added to the presently studied lowland stream. Sand coverage of the streambed and sediment the stream ecosystem. This resulted in a characteristic sequence of instream spatiotemporal hydromorphological changes. As a result of the sand addition, the water flow was partially blocked at the upstream beginning of the sand slug, where

CHAPTER 1

transport initiated immediate disturbance and short-term recovery processes within

leading to the accumulation of fine organic material on the streambed in plots II, III and IV. The sand added to the stream channel formed a sand slug, which moved downstream in a wavelike motion, a dynamic sequence of transport and storage, in a similar way as previously reported by Bartley and Rutherford (1999) and Pryor et al.

(2011). In our study, waves of moving sediment particles resulted in major changes in

CHAPTER 3

observations of Smakhtin (2001), this obstruction resulted in local flow cessation,

CHAPTER 2

the suddenly sloping bed acted as a physical obstruction. In agreement with the

Rutherfurd (2017). This might explain the observed high variability in the amount of trapped sediment among and within traps. Timing, duration and magnitude of the impact of the sand addition on the downstream plots was determined by sediment

CHAPTER 4

substrate and hydrological conditions, in line with James (2010) and Sims and

James (2010). In accordance with other studies (e.g. Bankert and Nelson, 2018; Buendia et al. 2014; Pryor, 2011), we observed that eventually all downstream plots (VI to IX) went through a phase of burial and dynamic sand movement, in which the

CHAPTER 5

and streambed characteristics, as well as by hydraulic parameters, as also reported by

new sandy-bottom condition, in line with Madej et al. (2009). This caused a homogenization of the local channel topography, while the new bottom also contained a lower organic matter percentage and lower nitrogen, carbon and

CHAPTER 6

entire streambed was covered by a layer of sand. The sediment pulses established a

which consisted of drift sand relatively poor in organic matter and nutrients.

In plot V, where the sand was added to the stream channel, the phase of streambed instability was followed by a phase of stabilization. In the plots downstream of the sand addition site, particles settled and a sediment sorting gradient developed. Fine grains were washed out or transported as bed-load and accumulated downstream, whilst the coarser material remained in position.

121

CHAPTER 7

phosphorus concentrations, which is not surprising given the origin of the material,

Chapter 6

At same time, instream and terrestrial derived fine and coarse particulate organic matter and dead woody debris were deposited on the streambed, increasing substrate heterogeneity further. These changes initiated the recovery of the stream ecosystem. It is expected that the introduced coarse woody debris patches will retain CHAPTER 1

the sand and prevents further downstream migration of the sand sludge, promoting faster bed modification. Together with a gradual accumulation of coarse organic material and dead woody debris from the adjacent terrestrial environment, the fine particulate organic matter from the upstream plot (IV) and the new hydraulic

CHAPTER 2

conditions resulted in a habitat recovery gradient starting at plot V. This habitat formation processes is in line with the observations made by Phillips (2009), Cummins and Klug, (1979) and Jordan et al. (1997).

CHAPTER 3

The upstream and downstream effects of the sand addition on the hydraulic conditions led to the prediction of impacts on ecosystem processes such as decomposition, sediment oxygen demand and therefore differences in dissolved oxygen regimes (Jones et al., 2012). Nevertheless, four weeks after the sand addition, dissolved oxygen regime showed no variation among plots, all showing relatively high

CHAPTER 4

dissolved oxygen concentrations. This may be explained by the continuous inflow of oxygen rich water from upstream and the low organic matter content, decreasing the influence of bottom respiration (Verdonschot et al., 2015).

CHAPTER 5

4.2 Effects on macroinvertebrate community composition Sand addition led to an initial decrease in macroinvertebrate richness. This was expected given the detrimental effects of sedimentation previously observed in other studies (e.g. Larsen et al., 2011; Murphy et al., 2015). Nonetheless, the adverse

CHAPTER 6

effects of the sand addition were followed by a rapid recovery in terms of richness, diversity and representation of EPT taxa, and an increase in the number of rheophilic taxa. This fast colonization is in line with observations of Westveer et al. (2018), who studied the colonisation of reconnected former channels in the same stream in

CHAPTER 7

autumn. In the recovered plots the increased habitat heterogeneity appeared to have provided suitable habitat and flow conditions for the arriving colonists (Astudillo et al., 2016; Eros and Grant, 2015; Matthaei et al., 2006; Muehlbauer et al., 2014; Rolls et al., 2018) which might have opened a â&#x20AC;&#x2DC;window of opportunitiesâ&#x20AC;&#x2122; (sensu Balke et al., 2014) for the rheophilic species present in the catchment.

This increased occurrence of rheophilic taxa showed the importance of longitudinal connectivity in recovery processes (Lake et al., 2007). Pilotto et al. (2018) 122

The landscape drives the stream

pointed out that the positive responses of aquatic organisms to restoration projects might be related to a combination of local and regional-scale approaches. By tackling local hydromorphological improvements in a stream stretch and at the same time

eventually all downstream impacted plots were expected to recover in a similar way as we observed in the plot closest to the initial sand addition. Additionally, we observed that taxa present in the unimpacted parts of the catchment colonized the stabilized stretches, indicating that within this catchment dispersal limitation does not hamper recovery, as often observed in restoration projects (Sarremejane et al., 2017; Sundermann and Stoll, 2011; Westveer et al., 2018). Such a fast biotic recovery suggests a high resilience of lowland stream ecosystems, an important condition to make restoration projects successful (Palmer et al., 2005).

CHAPTER 2

Although our study only recorded the short-term effects of sand addition,

CHAPTER 3

populations, streams may benefit most from restoration efforts.

CHAPTER 1

connecting restored sites to sites with high quality macroinvertebrate source

As a practical recommendation, the sand addition technique should be used only under specific conditions: in low gradient streams; gradually applied over time; spatially distributed along the stream interspersed with treatment-free stretches for

CHAPTER 4

5. Recommendations for sand addition restoration projects

upstream catchment; in stream stretches constrained by dead woody debris patches to limit further sand sludge dispersion; and in a suitable landscape matrix, allowing input of terrestrial coarse organic matter, essential for the increase in habitat

CHAPTER 5

maintaining instream organic matter and invertebrate source population in the

zone reconnection, stream valley rewetting and improvements on ecosystem structures and processes.

6. Conclusions The evident hydromorphological differences among downstream and upstream plots showed that the stream channel had undergone major changes after the sand addition. In the downstream plots raising the streambed quickly led to new hydrological conditions characterized by a sandy bottom in a shallow stream with a higher current velocity. These characteristics are commonly described as negative side effects of sand waves in studies of catchment erosion, but in the present case they

123

CHAPTER 7

validate the expected aquatic-terrestrial changes from sand addition, such as riparian

CHAPTER 6

patchiness. Furthermore, long-term and larger scale monitoring is suggested to

Chapter 6

were counteracting the negative effects of channel incision by elevating the stream bed and improving flow conditions.

In conclusion, this study confirmed the hypothesis that sand addition initially CHAPTER 1

disturbed the stream ecosystem, but this was followed by a fast recovery leading to

CHAPTER 2

within the macroinvertebrate community. Already on a short term, the negative

increased substrate heterogeneity and improved flow conditions. Lowland macroinvertebrate assemblages benefited from the habitat changes induced by the sand addition, amongst others reflected by an increasing proportion of rheophilic taxa effects of the sand addition started to become outweighed by the positive effects, indicating that sand addition could be a promising restoration measure for incised low gradient streams.

CHAPTER 3 CHAPTER 4 CHAPTER 5 CHAPTER 6 CHAPTER 7 124

The landscape drives the stream

Supplementary material

Week

Table 1: Mean suspended sediment transport (g/day) (n = 5; ±1sd) per plot per week. Different letters indicate significant (p < 0.05) differences among plots per week.

3 4

1 (1) a 3 (3)a

15

6 (1) a

4 (2) a

2 (0) a

4 (2) a

5 (4) a

16

V -

4 (0) a

-

4 (2) a

-

11 (10) a

VI

VII

82 (43)

a

45

VIII

(21) a

266

IX

(459) a

123 (214) a

11 (8) a

154 (106) a

247 (210) a

540 (732) a

43 (21) a

78(70) a

41 (33) a

381 (529) a

117 (72) a

132 (137) a

24 (21) a

Table 2: Mean bed-load sediment transport (g/day) (n = 9; ±1sd) per plot per week. Different letters a, b and c indicate significant (p < 0.05) differences among plots per week.

Week

Plot I

II

III

1

4 (3) a

10 (13)a

7 (5) a

2 3 4

4 (6) a 1 (2) a 7 (7) a

8 (7) ab

IV

VI

8 (4) a

4 (3) a

5 (5) ab

V -

7 (6) ab

6 (5)ab

11 (10)a

-

5 (3) a

-

29 (15)ab

VII 1070 (641)

VIII

IX

1032 (676) ab

b

1352 (363) ab

400 (679) ab

942 (588) abc

925 (610) c

1129 (224) c

474 (655) abc

1048 (394) cb

835 (568) b

1114 (257) b

830 (696) ab

743 (446) ab

1058 (472) ab

442 (432) b

Table 3: Mean (±1sd) deposited sediment composition nutrient concentrations and OM percentage in plots I, IV, V, VI and IX (n = 3). Letters indicate significant differences between the means (p<0.05).

Plot I

IV a

0.09 (0.03)

VI b

0.76 (0.42) a

0.78 (0.8)

N (g/Kg)

3.97 (4.08) a

1.02 (0.43) c

0.19 (0.04) b

0.16 (0.07) b

2.49 (1.41) a

C (g/Kg)

71.7 (74.9) a

16.93 (8.3) a

2.62 (0.65) b

2.24 (1.70) b

44.7 (23.59) a

17.85 (0.77) ab

16.32 (1.1) abc

14.21 (1.14) c

12.47 (3.87) ac

18.19 (0.7) b

P (g/Kg)

2.90 (2.8) a

0.93 (0.33) a

0.06 (0.01) b

0.05 (0.02) b

1.89 (1.17) a

S (g/Kg)

1.38 (1.34) a

0.32 (0.10) c

0.03 (0.03) b

0.01 (0.01) b

0.80 (0.46) a

125

0.06 (0.01)

IX b

OM (%)

C:N

2.20 (0.7)

V a

CHAPTER 2

3 (3) a

(9) a

CHAPTER 3

2

13

IV

(9) a

CHAPTER 4

7

III

(9) a

CHAPTER 5

1

II

CHAPTER 6

(1)a

CHAPTER 7

I

CHAPTER 1

Plot

Chapter 6

CHAPTER 1

CHAPTER 2

CHAPTER 3

CHAPTER 4

CHAPTER 5

CHAPTER 6

CHAPTER 7

126

The landscape drives the stream Table 6: Mean (n=5) Âą standard deviation (sd) of macroinvertebrate community indices. EPT is the is the relative abundance of Ephemeroptera, Plecoptera and Trichoptera individuals; Abd is total abundance; Rheo is the richness of rheophilic taxa; Rheo_catchment is the percentage of species found in the entire catchment and Rheo_stream in Leuvene stream . Letters indicate a significant difference between the means (p <0.05).

Richness

12.8

Abd

93.6 (30.8) a (0.2) a

Silt

Sand

15.6

(1.5) a

6.8

(1.1) b

Recovery 15.6 (2.6) a

89.6 (16.4) a

39.6 (11.9) b

73 (21) ab

(0.1) a

(0.1) b

2.0 (0.1) a

2

2.2

1.4

EPT (%)

57 (9) a

38 (16) a

43 (23) a

38 (1.5) a

Rheo

1.8 (0.8) a

2.2 (1.3) a

1 (0) a

4.6 (0.9)b

Rheo_catchment (%)

9.5 (4.4) a

11.6 (6.9) a

12.6 (4.7) a

25.3 (4.4) b

Rheo_stream (%)

11.3 (5.2) a

13.8 (8.1) a

15 (5.6) a

30 (5.2) b

CHAPTER 7

CHAPTER 6

CHAPTER 5

CHAPTER 4

CHAPTER 3

Shannon-Winner diversity

CHAPTER 1

(2.8)a

CHAPTER 2

Control

Figure A1: Continuous measurements of DO saturation in five zones during 3 days of measurement, and discharge (Q).

127

Chapter 6

CHAPTER 1 CHAPTER 2 CHAPTER 3 CHAPTER 4

Figure A2: Daily discharge measured from 2014 to 2016, at a gauging station just downstream of the last sand addition site.

CHAPTER 5 CHAPTER 6 CHAPTER 7 128

CHAPTER 7

CHAPTER 6

CHAPTER 5

S2 CHAPTER 4

CHAPTER 3

CHAPTER 2

CHAPTER 1

The landscape drives the stream

S1

129

Chapter 6

S3

CHAPTER 1

CHAPTER 2

CHAPTER 3

CHAPTER 4

S4

CHAPTER 5

CHAPTER 6

CHAPTER 7

130

CHAPTER 7

CHAPTER 6

S6 CHAPTER 5

CHAPTER 4

CHAPTER 3

CHAPTER 2

CHAPTER 1

The landscape drives the stream

S5

131

Chapter 6

S7

CHAPTER 1 CHAPTER 2 CHAPTER 3 CHAPTER 4 CHAPTER 5

Figure A3: Pictures of sand addition sites S1 to S7.

Acknowledgements: We would like to thank Natuurmonumenten and Waterschap CHAPTER 6

Vallei and Veluwe for providing the opportunity to study the sand additions in the Leuvenumse stream, Maarten Veldhuis for providing the picture of the sand addition, Thijs de Boer for helping with GIS and JoĂŁo Lotufo, Dorine Dekkers and Mariska

CHAPTER 7

Beekman for their help in the field. We thank laboratory technicians Chiara Cerli, Joke Westerveld and Leo Hoitinga. PCRO received funding from CNPq Brazil (grant number 200879/2014-6, 2014), RCMV was funded by Waterschap Vallei en Veluwe, Programma Lumbricus, and the Dutch ministry of Agriculture, Nature and Food Quality (project KB-24-001-007).

132

Chapter 7 Synthesis

The landscape drives the stream

The influence of surrounding land use on stream ecosystems is scaleâ&#x20AC;?dependent (Frissell et al., 1986), whereby instream habitat structure and organic matter inputs are determined primarily by local conditions such as vegetation cover, whereas by regional conditions, including landscape features and land use types at some distance upstream and lateral to each specific site (e.g., Allan et al., 1997). Yet, the underlying mechanisms linking adverse in stream ecological effects to stream valley

CHAPTER 1

nutrient supply, sediment input, hydrology and channel characteristics are influenced

can affect stream ecosystems (e.g. Burcher et al., 2007; Maloney and Weller, 2011), including the input of land use specific terrestrial particles into the stream, the focus of the present thesis.

In the present thesis we showed that allochthonous particulate matter, either organic or mineral (silt) entered the lowland streams and deposited in stream deposition zones. This material changed the natural substrate cover and sediment characteristics (chapter 3, Wood and Armitage, 1999). These changes altered both stream ecosystem structure (e.g., macroinvertebrate community composition) and functioning (e.g., oxygen regime and metabolism) (chapter 4, Buendia et al., 2013).

CHAPTER 3

stream ecosystems. There are several potential mechanisms by which land use type

CHAPTER 4

the mechanisms by which land use affects structure and functioning of lowland

CHAPTER 2

land use are still not fully understood. The aim of this thesis was therefore to unravel

environmental conditions in the deposition zones (chapters 3, 4, 5 and 6). These findings are in line with, amongst others Chutter (1969), Ryan (1991), Rabeni et al.

(2005) and Von Bertrab et al. (2013). The present thesis thus contributed to a better

CHAPTER 5

The macroinvertebrate community composition in turn responded to the changed

(chapters 3 and 4) and habitat structure and food resources (chapters 3 and 5).

Moreover, the ecological key factors oxygen, habitat structure and food resources were shown to interact (chapter 5) shaping lowland stream ecosystems (e.g. Hunt et

CHAPTER 6

understanding of the effects of land use on stream metabolism and oxygen availability

interrelated ecological key factors was presented.

To both better understand land use specific stressor-response pathways and to support restoration practices, below we elaborated a framework integrating the results obtained from the previous chapters. To this purpose the elements of the framework that describe the effects of land use on lowland stream macroinvertebrate communities were described as land use pressure, stress, disturbance of ecological key parameters and abiotic and biotic responses, analogous to the DPSIR framework 135

CHAPTER 7

al, 2012; Wallace et al., 2015). In chapter 6 an experimental attempt to restore these

Chapter 7

(driver, pressure, state, impact and response) (see van Puijenbroek, 2019).

Subsequently, the framework was applied per land use type, aiming to design a land use specific effect framework.

CHAPTER 1

1. The effects of land use on lowland stream macroinvertebrate communities 1.1 Land use induced stress Human activities in the landscape, such as the use of fertilizers, ploughing, the

CHAPTER 2

presence of livestock (e.g. Jarvie et al., 2010), forestry (Moore et al., 2006) and the treatment of wastewaters (Walsh et al., 2005) change the nature and composition of dissolved substances and fine particulate material input into the streams. These dissolved substances (mainly nutrients and pollutants) and organic and mineral particles, further indicated as sediment, are easily washed off from the terrestrial

CHAPTER 3

surrounding into stream ecosystems by diffuse runoff (Chapter 3, Cai et al., 2015; Vidon et al., 2010). Wastewater treatment plants (WWTP) are point sources of nutrients and fine organic particles (e.g. Carey and Migliaccio, 2009). Input of nutrients and sediment from the adjacent land is a dominant fuel for lowland streams

CHAPTER 4

that depend on energy input from the surrounding valley and catchment (Hoellein et al., 2013; Bernhardt et al., 2018). Consequently, anthropogenic land use will affect lowland stream ecosystem structure and function, as it changes the fuel provided to the system (e.g., Allan, 2004; Castro et al., 2018; Englert et al., 2015; Frainer and

CHAPTER 5

McKie, 2015; Hladyz et al., 2011; Masese et al., 2017; Riipinen et al., 2010).

Lowland stream valleys covered by forest provide large amounts of allochthonous material, such as woody debris, tree leaves and coarse, fine and dissolved organic

CHAPTER 6

matter to the stream (Bilby, 1981; Meyer et al., 1998). However, when the land use in the valley is changed, the load of dissolved substances, substrate cover and sediment composition may also change dramatically. For example, runoff from agricultural areas may contain microbial pathogenic organisms, nutrients, potentially toxic substances (e.g., pesticides), metabolic substrates (e.g., labile organic carbon) and fine

CHAPTER 7

mineral and organic grains (Khaleel et al., 1980; Jordan et al., 1997; Edwards et al., 2008). Grassland in comparison to cropland will, to a certain extent, limit sediment runoff and will retain more sediment and sediment-bound pollutants (Souchère et al., 2003; Burcher and Benfield, 2006; Withers and Jarvie, 2008). WWPTs discharge high loads of dissolved nutrients into streams (Gßcker et al., 2006; Imberger et al., 2014).

In conclusion, land use can have strong effects on lowland stream structure and functioning and is considered to be therefore a major stressor (Pozo et al., 1997; 136

The landscape drives the stream

Lambert et al., 2017). To improve our understanding of the underlying mechanisms as aimed in the present thesis, the land use - stream ecosystem interaction was put in a conceptual framework (Figure 1). Four major land use types, each providing different debris and coarse organic matter, like branches, twigs and leaves) runoff; 2- Grassland with nutrient-rich organic particles runoff; 3- Cropland with fine sediment runoff; 4WWTP with point discharge of dissolved nutrients (Figure 1). The input types 2-4 were

CHAPTER 1

inputs into the receiving streams were distinguished: 1- Forest with CPOM (woody

the morphological and physico-chemical instream characteristics, and changes for example oxygen and nutrient concentrations, grain size and metabolic rates (e.g.

Young et al., 2008), therewith disturbing the ecological key factors. Figure 1 illustrates the ecological key parameters that can be changed by land use stress.

CHAPTER 3

1.2 Disturbance of ecological key factors The discharge of dissolved substances and sediment into the streams influences

CHAPTER 2

considered to be a major stressor for lowland stream ecosystems.

ecosystem respiration, respectively, together defining the whole stream metabolism.

These changes result, amongst others, in changes in oxygen concentration and diel oxygen regimes. Moreover, increases in sediment input can lead to a lower

CHAPTER 4

Dissolved nutrients and organic sediment change primary production and

growth of algae and macrophytes and lower primary production and related oxygen availability. Higher organic sediment input causes higher turbidity and increased decomposition rates. Such a cascade of events underlines the importance of

CHAPTER 5

transparency (poorer light conditions) in the water column. Less light causes less

Johnson et al. (2009), Battin et al. (2016), Lear et al. (2013), Price et al. (2018), Hunt et al. (2012), Kendall et al. (2001) and Leigh et al. (2010).

CHAPTER 6

autotrophic and heterotrophic metabolic processes, as previously suggested by

growth of macrophytes due to nutrient input will both change the instream flow patterns (e.g. Jones et al., 2012a) and habitat structures (e.g. Schoelynck et al. 2012).

1.3 Abiotic responses and subsequent changes in macroinvertebrate community composition The macroinvertebrate community composition is influenced by the type of organic matter in the sediment as major food source, being either allochthonous (e.g., wood, CPOM, FPOM) or autochthonous and when autochthonous being either 137

CHAPTER 7

Input of coarse organic matter (e.g. woody debris) from forested riparian zones or

Chapter 7

autotrophic (e.g. macrophytes and algae) or heterotrophic (e.g. bacteria and fungi) (e.g., Cummins and Klug 1979; Wallace and Webster 1996; Johnson et al., 2009). So, macroinvertebrate community composition is expected to change when changes in food quality occur (Cammen, 1980; Cummins and Klug, 1979). Species belonging to CHAPTER 1

the Ephemeroptera, Plecoptera and Trichoptera (EPT-species) may take advantage of the presence of allochthonous material, like CPOM and FPOM which have high C/N ratios (Besemer et al., 2009; Boyero et al., 2011; Von Bertrab et al., 2013).

Furthermore, changes in the stream structure by woody debris, leaf packages, FPOM

CHAPTER 2

depositions and macrophytes will alter the habitat structure and therewith the composition of the macroinvertebrate communities (Brown, 2003; de Brouwer et al., 2019).

CHAPTER 3

Oxygen is a key ecological driver for macroinvertebrates (Boulton et al., 1997; Fox and Taylor, 1955). Low oxygen concentrations in either the water column or the sediment limit the occurrence of many EPT-species (Connolly et al., 2004; Collier et al., 1998; Von Bertrab et al., 2013). Other species that tolerate low dissolved oxygen concentrations, such as Chironomus sp., Oligochaeta and some Gastropoda can

CHAPTER 4

dominate under disturbed oxygen conditions (Ding et al., 2016; Justus et al., 2014; Pardo and GarcĂ­a, 2016).

It is concluded that stress-induced land use specific changes in ecological key

CHAPTER 5

parameters may induce abiotic responses of the system, concerning food quality, oxygen availability and habitat structure (Figure 1). This undoubtedly has consequences for the macroinvertebrate community composition.

CHAPTER 6 CHAPTER 7 138

2.1 Introduction Each land use type has specific multiple impacts on stream ecosystems. To facilitate the study of the complex relationships between stressors (land use type) and biotic responses (macroinvertebrate community composition), the major pathways have to be identified (e.g. Grace et al., 2010; Allan et al., 2012; Villeneuve et al., 2018).

To do so, I designed the conceptual framework depicted in Figure 1. This framework is composed of four main layers including (1) land use stressors, (2) disturbances of ecological key parameters, (3) abiotic response and (4) biotic responses, respectively (Figure 1). Below, the building blocks of the framework were connected by positive and negative pathways running from land use type (stressor) to lowland stream ecosystem response (macroinvertebrate community composition).

139

CHAPTER 5 CHAPTER 6

2. Towards a land use specific effect framework

CHAPTER 7

Figure 1: General pressure (land use) - response (macroinvertebrates) framework. Rectangles in color represent the terrestrial input, dashed rectangles show the ecological key parameters that may bedisturbed and circles symbolize abiotic responses in terms of oxygen, food and habitat structure and biotic responses in terms of macroinvertebrate community composition.

CHAPTER 4

CHAPTER 3

CHAPTER 2

CHAPTER 1

The landscape drives the stream

Chapter 7

2.2 Forest - C(F)POM input (reference condition) In forests and forested riparian zones, the allochthonous input of coarse and fine particulate organic material (C(F)POM) controls lowland stream ecosystem structure and functioning (e.g. Lange et al., 2011). In the stream channel, CPOM CHAPTER 1

creates heterogeneous substrate mosaics and diversifies flow patterns, creating conditions favorable for rheophilic and EPT species (chapter 6). Moreover, CPOM and FPOM largely determine the sediment characteristics in terms of food resources, being composed of microbial derived fatty acids and characterized by a high C/N ratio

CHAPTER 2

(chapter 5). Furthermore, shading that lowers metabolism and flow that increases reoxygenation jointly result in relatively high and constant dissolved oxygen concentrations and low sediment oxygen demands. These conditions offer opportunities for xenosaprobic and oxyphilic macroinvertebrates species (Figure 2).

CHAPTER 3 CHAPTER 4 CHAPTER 5 CHAPTER 6 CHAPTER 7

Figure 2: Forest (reference) pressure-response framework. Rectangles in color represent the terrestrial input, dashed rectangles show the influence on ecological key parameters and circles symbolize abiotic responses in terms of oxygen, food and habitat structure and biotic responses in terms of macroinvertebrate community composition. Pathways are illustrated by positive (+ solid line) and negative (- dashed line) connecting arrows.

140

The landscape drives the stream

2.3 Grassland - nutrient-rich sediment input Streams surrounded by grasslands receive light, nutrients and organic sediment (chapter 3 and 4). The nutrients enhance the growth of macrophytes (Haggard et al., Macrophytes structure the stream channel (Jones et al., 2012a), and together with the algae increase primary production rates (Finlay, 2011; Bernot et al., 2010; Mulholland et al., 2008). Plant production increases plant biomass and the decaying plants do

CHAPTER 1

2005) and algae, the latter increasing the chlorophyll concentrations in the sediment.

regime. Most of the time, oxygen concentrations do not fall below 2 mg/l and are not limiting the occurrence of most macroinvertebrates. Only some sensitive species, like

Figure 3: Grassland pressure-response framework. Rectangles in color represent the terrestrial input, dashed rectangles show the disturbed ecological key parameters and circles symbolize abiotic responses in terms of oxygen, food and habitat structure and biotic responses in terms of macroinvertebrate community composition. Pathways are illustrated by positive (+ solid line) and negative (- dashed line) connecting arrows.

141

CHAPTER 7

CHAPTER 6

CHAPTER 5

CHAPTER 4

CHAPTER 3

the oxybionts and the xenosaprobic ones, may disappear (Figure 3).

CHAPTER 2

increase respiration rates. Productivity and respiration together affect the diel oxygen

Chapter 7

2.4 Arable cropland - fine sediment input Cropland runoff containing high loads of nutrient rich organic and mineral sediment (silt) do increase water turbidity and silt cover, especially in deposition zones. High water turbidity hampers the development of autotrophic organisms CHAPTER 1

(Jones et al., 2012a; Vermaat and de Bruyne, 1993), despite the high nutrient concentrations, while at the same time heterotrophic microorganisms flourish (Stewart and Franklin, 2008). These processes affect the whole stream metabolism and decrease oxygen concentrations. The low oxygen availability limits the occurrence

CHAPTER 2

of oxyphilic species (Connolly et al., 2004), while tolerant taxa such as Chironomus sp., Oligochaeta and Gastropoda (Ding et al., 2016; Justus et al., 2014; Pardo and GarcĂ­a, 2016) take advantage of heterotrophic microbial derived food (de Haas et al., 2005; chapter 4) (Figure 4). Moreover, fine sediment (silt) covers most of the stream bottom

CHAPTER 3

and limits the habitat availability for many macroinvertebrates and may even cause physical effects on macroinvertebrates such as disruption of organ function by clogging (Jones et al., 2012b).

CHAPTER 4 CHAPTER 5 CHAPTER 6 CHAPTER 7 Figure 4: Cropland pressure-response framework. Rectangles in color represent the terrestrial input, dashed rectangles show the disturbed ecological key parameters and circles symbolize abiotic responses in terms of oxygen, food and habitat structure and biotic responses in terms of macroinvertebrate community composition. Pathways are illustrated by positive (+ solid line) and negative (- dashed line) connecting arrows.

142

The landscape drives the stream

2.5 Wastewater treatment plant - dissolved nutrients input Wastewater treatment plants discharge high nutrient loads into the receiving stream (e.g., Peterson et al., 1993; Wood and Armitage, 1997; Walsh et al., 2005). et al., 2005). The continuous input of nitrate, orthophosphate and oxygen into the water column stimulates the microbial community growing on the top sediment layer (Bernhardt and Likens, 2002; Bernot et al., 2006; Stewart and Franklin, 2008; Battin et

CHAPTER 1

Moreover, WWTPs can cause typical hydrologic flashiness (Meyer et al., 2005; Walsh

availability in the sediment is expected to be low, which in turn affects the macroinvertebrate community composition (chapter 4). Sensitive taxa are limited due to the low oxygen availability, and tolerant taxa (often Oligochaeta and Chironomus

Figure 5: WWTP pressure-response framework. Rectangles in color represent the terrestrial input, dashed rectangles show the disturbed ecological key parameters and circles symbolize abiotic responses in terms of oxygen, food and habitat structure and biotic responses in terms of macroinvertebrate community composition. Pathways are illustrated by positive (+ solid line) and negative (- dashed line) connecting arrows.

143

CHAPTER 7

CHAPTER 6

CHAPTER 5

CHAPTER 4

CHAPTER 3

sp.) are abundantly present (Figure 5).

CHAPTER 2

al., 2016) and increase the benthic metabolic activity. Consequently, the oxygen

Chapter 7

2.6 Patchy landscapes In patchy landscapes with multiple land use types, common to the mosaic like landscapes of deltas harboring lowland streams, the relationships between pressures-stressors-disturbances-responses are expected to be even more CHAPTER 1

complex (Figure 6). In such cases it is crucial to identify the main pressures and related stressors per stream stretch and in turn relate these to the disturbances of the ecological key parameters and the abiotic responses affecting macroinvertebrate community composition (e.g. de Vries et al., 2019). This way, environmental problems

CHAPTER 2

can better be identified and tackled, resulting in a more effective set of measures to combat aquatic ecosystem degradation and to restore biodiversity.

CHAPTER 3 CHAPTER 4 CHAPTER 5 CHAPTER 6 CHAPTER 7

Figure 6: Pressure-response framework for patchy landscapes. Rectangles in color represent the terrestrial input, dashed rectangles show the disturbed ecological key parameters and circles symbolize abiotic responses in terms of oxygen, food and habitat structure and biotic responses in terms of macroinvertebrate community composition. Pathways are illustrated by positive (+ solid line) and negative (- dashed line) connecting arrows.

144

The landscape drives the stream

3. Conclusions Based on the results obtained in the present thesis, the following conclusions

â&#x20AC;˘

Oxygen availability, habitat heterogeneity and food resources are considered key ecological filters driving macroinvertebrate community composition.

â&#x20AC;˘

We demonstrated the importance of including the landscape scale and multiple

interconnected

parameters

in

ecological

stream

quality

assessments, yet the proposed framework needs to be tested in practice.

Hence, in this thesis I showed that the landscape indeed drives the stream and that only by unravelling the underlying mechanisms restoration measures may be improved.

4. Implications for stream restoration The present thesis underlines the importance of including landscape scale anthropogenic activities in ecological stream assessments and restoration. This

CHAPTER 2

accumulation of particles in deposition zones.

CHAPTER 3

Land use specific impacts on lowland streams are exerted via the

CHAPTER 4

â&#x20AC;˘

CHAPTER 1

can be drawn:

sources. As land use specific inputs of particles and nutrients influence stream ecosystem

structure

and

function

by

changing

dissolved

substances

concentrations and sediment composition, the need to identify the characteristics, such as volume and composition, is crucial in selecting the appropriate restoration measure. Such an approach may help to identify the main stressors, the pathways of disturbances and the macroinvertebrate community responses.

2.

Design land use specific stream restoration strategies. The results obtained in the present thesis show that each anthropogenic activity has a specific impact on stream ecosystems. Therefore, to improve stream restoration success, restoration measures should take these pathways of stress and disturbance into account. Using the knowledge of land use specific effects on macroinvertebrate community composition allows to design tailor made restoration strategies.

145

CHAPTER 6

Identify the input of particles and nutrients from different anthropogenic

CHAPTER 7

1.

CHAPTER 5

knowledge should be considered in designing stream restoration projects as follows:

Chapter 7

3.

Improve WWTP effluent quality and manage discharge. WWTPs change stream hydrology and water quality. Effluent nutrient loads must be lowered, and effluent hydrological flashiness should be eliminated to ecologically restore streams affected by WWPT effluent discharge.

CHAPTER 1

4.

Retain water, sediments and nutrients at the source. The runoff of dissolved substances and sediment should be minimized and retained either on or close to the source. Buffer zones that store water and retain nutrients strongly add to stream restoration.

CHAPTER 2

5.

Develop and stimulate natural and sustainable land use types along streams.

Keeping a natural vegetation corridor along a stream will filter particles and nutrients and subsidize the stream ecosystem with more natural materials.

However, the application of this measure can cause economic conflicts.

CHAPTER 3

Developing agroforest along a streambank instead of tradition agricultural activities maintains a buffer function, while simultaneously supporting agriculture.

CHAPTER 4

Streams are beautiful and complex ecosystems. They are not stand alone systems, but are part and product of relationships that include the atmosphere, hydrosphere, biosphere, lithosphere, and anthroposphere. In science, we are in a continuous process of growing understanding of these relationships, which hopefully contributes to bridge the science of stream ecology and ecological stream restoration

CHAPTER 5

practice. However, the impoverishment of the worlds streams and the losses of species and ecosystem processes proceeds faster than the growth in knowledge. As long as the rights of a stream, such as to freely flow and to be free of (excess of) nutrients and contaminants, are not respected and legally incorporated in our

CHAPTER 6

societies, I believe that there will be no way to fully enjoy, understand and reveal the mechanism by which the landscape drives the stream.

CHAPTER 7 146

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Whatley, M. H., van Loon, E. E., Cerli, C., Vonk, J. A., Van Der Geest, H. G., & Admiraal, W. (2014). Linkages between benthic microbial and freshwater insect communities in degraded peatland ditches.

Ecological Indicators, 46, 415–424. http://doi.org/10.1016/j.ecolind.2014.06.031 White, J. C., Hannah, D. M., House, A., Beatson, S. J. V., Martin, A., & Wood, P. J. (2017).

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179

Summary

The landscape drives the stream

The landscape drives the stream: unraveling ecological mechanisms to improve restoration The influence of surrounding land use on stream ecosystems is scale‐ dependent, whereby instream habitat structure and organic matter inputs are determined primarily by local conditions such as vegetation cover, whereas nutrient supply, sediment input, hydrology and channel characteristics are influenced by regional conditions, including landscape features and land use types at some distance upstream and lateral to each specific site. Yet, the underlying mechanisms linking adverse in stream ecological effects to stream valley land use are still not fully understood. The aim of this thesis was therefore to unravel the mechanisms by which land use affects structure and functioning of lowland stream ecosystems.

To this end the following objectives were defined: •

To evaluate 40 years of stream restoration practices by assessing the influence of policy goals on stream restoration efforts, the biophysical restoration objectives, the restoration measures, the scale on which these measures were applied and the accompanying monitoring efforts.

•

To unravel the mechanisms by which terrestrial runoff affects sediment composition and macroinvertebrate community composition in deposition zones of lowland stream ecosystems.

•

To determine if lowland stream sediment characteristics in terms of food resources and habitat structure are land use specific and if they shape macroinvertebrate communities.

•

To assess the impact of catchment land use on the structure (macroinvertebrate community composition) and functioning (instream oxygen regimes) of lowland stream ecosystems.

•

To improve the success of stream restoration projects by applying a novel approach, consisting of the addition of sand to the stream channel in combination with the introduction of coarse woody debris, to restore sandy‐ bottom lowland streams degraded by channelization and channel incision.

Because the reasons for the unsuccessful restoration efforts remain

inconclusive and need urgent clarification, the aim of chapter 2 was to evaluate 40 years of stream restoration to fuel future perspectives. To this purpose we evaluated the influence of policy goals on stream restoration efforts, biophysical restoration 181

Summary

objectives, restoration measures applied, including the scale of application, and monitoring efforts. Information was obtained from five stream restoration surveys that were held among the regional water authorities in the Netherlands over the last 40 years, and from an analysis of the international scientific publications on stream restoration spanning the same time period. Our study showed that there was a considerable increase in stream restoration efforts, especially motivated by environmental legislation. However, proper monitoring of the effects of these efforts was often lacking. Furthermore, a mismatch between the initial restoration goals and the actual restoration measures taken to achieve these goals was observed. Measures are still mainly focused on hydromorphological techniques, while biological goals remain underexposed and therefore need to be better targeted. Moreover, restoration practices occur mainly on small scales, despite the widely recognized relevance of large scale ecological processes for stream ecosystem recovery. In order to increase the success rate of restoration projects, it is recommended to improve the design of the accompanying monitoring programs, allowing to evaluate, over longer time periods, if the measures taken led to the desired results, and secondly to scale up the spatial scale of stream restoration projects from local instream efforts to catchment wide measures to tackle the overriding effects of catchment wide stressors.

To better understand the contribution of terrestrial runoff to the sediment composition in lowland stream deposition zones and the subsequent effects on benthic invertebrates, the aim of chapter 3 was to investigate the mechanisms by which runoff affects sediment composition and macroinvertebrates in deposition zones of lowland stream ecosystems. To this end, sediment from runoff and adjacent instream deposition zones from streams with different land use was chemically characterized and the biological effects were assessed at the species, community and ecosystem level. Runoff and deposition zone sediment composition as well as biological responses differed clearly between forest and agricultural streams. The stream deposition zone sediment C/N ratio reflected the respective runoff sediment composition. Deposition zones in the forest stream had a higher C/N ratio in comparison to the agricultural streams. Growth of Hyalella azteca and reproduction of Asellus aquaticus were higher on forest stream sediment, whereas chironomids and worms suffered less mortality on the agricultural sediments containing only natural food. The forest stream deposition zones showed higher values for indices indicative of biological integrity and had a lower sediment oxygen demand. We concluded that agricultural land use affects lowland stream ecosystem deposition zones at the 182

The landscape drives the stream

species, community and ecosystem level via altered food quality (C/N ratio) and higher oxygen demand of the sediment. This outcome motivated us to study the effects of land use on oxygen regime, food resources and habitat structure in more depth in chapters 4 and 5.

In chapter 4, we aimed to assess the impact of catchment land use on the structure and functioning of lowland stream ecosystems in order to disentangle the land use specific effects of fine sediment input on lowland stream ecosystems and to unravel the underlying mechanisms. To this purpose, twenty streams surrounded by five different land use types were selected and sediment and water quality parameters were measured, diel dissolved oxygen regimes were recorded, and macroinvertebrate community composition was determined. The results showed that anthropogenic land use type altered fine particulate organic matter substrate cover, sediment

organic

matter

content

and

sediment

nutrient

concentrations.

Subsequently, this impacted instream metabolic processes, such as primary production and respiration and sediment oxygen demand, leading to highly different oxygen regimes in the streams, which in turn were reflected by large differences in macroinvertebrate community composition. We therefore argue that land use specific impacts on lowland streams, exerted via fine sediment accumulation in deposition zones, stress the importance of including the catchment scale in ecological stream quality assessments.

The input of land use specific organic matter into lowland streams may also impact sediment characteristics in terms of food resources and habitat structure for macroinvertebrates. Therefore, in chapter 5 we investigated to what extent land use specific sediment characteristics structure macroinvertebrate communities. To this purpose

linear

multiple

regression

models

were

constructed,

in

which

macroinvertebrate biotic indices were considered as response variables and sediment characteristics as predictor variables, analysed in 20 stream stretches running through five different land use types. Sediment characteristics and macroinvertebrate community composition were land use specific. C/N ratio, woody debris substrate cover and the origin of fatty acids influenced macroinvertebrate community composition. Shannon-Wiener diversity was better explained by fatty acids origin, such as in grassland streams, where a higher relative content of plant derived fatty acids related to a higher macroinvertebrate diversity. In Crop and WWTP streams with a low C/N ratio and dominated by microbial derived fatty acids, higher abundances of Oligochaeta and Chironomus sp. were observed. EPT (Ephemeroptera, Plecoptera and 183

Summary

Trichoptera) richness was positively related to woody debris substrate cover, which only occurred in forest streams. Hence, macroinvertebrate community composition was influenced by the origin of the organic material, being either allochthonous or autochthonous and when autochthonous being either autotrophic or heterotrophic.

Yet, in spite of the observed relation between sediment characteristics and macroinvertebrate community composition, this is obviously not the only driver of community composition. But, if the minimum requirements of the other ecological parameters such as oxygen, habitat heterogeneity and stream velocity are fulfilled, sediment characteristics can certainly be considered as a key ecological filter.

In chapter 6, an experimental study was performed to evaluate a novel technique to restore sandy-bottom lowland streams degraded by channel incision, consisting of the addition of sand to the stream channel in combination with the introduction of coarse woody debris. The aim of the study was therefore to evaluate if sand addition can improve hydromorphological stream complexity on the short-term leading to an increase in macroinvertebrate biodiversity. To this end, particle transport, water depth, current velocity, dissolved oxygen dynamics and sediment composition were measured. The response of the macroinvertebrate community composition was determined at different stages during the disturbance and short-term recovery process. Immediately downstream the sand addition site, transport and sedimentation of the sand was initially intense, until an equilibrium was reached and the physical conditions stabilized. The stream section matured fast as habitat formation took place within a short-term. Macroinvertebrate diversity decreased initially, but recovered rapidly following stabilization. Moreover, an increase in rheophilic taxa was observed in the newly formed habitats. Thus, although sand addition initially disturbed the stream, a relatively fast physical and biological recovery occurred, leading to improved instream conditions for a diverse macroinvertebrate community, including rheophilic taxa. Therefore, we concluded that sand addition is a promising restoration measure for incised lowland streams.

To both better understand land use specific stressor-response pathways and to support land use specific restoration practices, in chapter 7 a framework integrating the results obtained from the previous chapters was proposed. The land use specific effects on lowland stream macroinvertebrate communities were described as land use pressure, stress, disturbance of ecological key parameters and abiotic and biotic responses, analogous to the DPSIR framework (driver, pressure,

184

The landscape drives the stream

state, impact and response). Based on the results obtained in the present thesis, the following conclusions were drawn: â&#x20AC;˘

Land use specific impacts on lowland streams are exerted via the accumulation of particles in deposition zones.

â&#x20AC;˘

Oxygen availability, habitat heterogeneity and food resources are considered key ecological filters driving macroinvertebrate community composition.

â&#x20AC;˘

We demonstrated the importance of including the landscape scale and multiple

interconnected

parameters

in

ecological

stream

quality

assessments, yet the proposed framework needs to be tested in practice.

Hence, in this thesis I showed that the landscape indeed drives the stream and that only by unravelling the underlying mechanisms restoration measures may be improved.

The present thesis underlines the importance of including landscape scale anthropogenic activities in ecological stream assessments and restoration. This knowledge should be considered in designing stream restoration projects as follows: 1- Identify the input of particles and nutrients from different anthropogenic sources.

2- Design land use specific stream restoration strategies. 3- Improve WWTP effluent quality and manage discharge. 4- Retain water, sediments and nutrients at the source.

5- Develop and stimulate natural or sustainable land use types along streams.

As long as the rights of a stream, such as to freely flow and to be free of (excess of) nutrients and contaminants, are not respected and legally incorporated in our societies, I believe that there will be no way to fully enjoy, understand and reveal the mechanism by which the landscape drives the stream.

185

Samenvatting

The landscape drives the stream

Het landschap dicteert de beek: het ontrafelen van ecologische mechanismen om herstelmaatregelen te verbeteren De invloed van het omliggende landgebruik op beekecosystemen verloopt over meerdere schalen, waarbij de beekhabitatstructuur en de toevoer van organisch materiaal worden bepaald door lokale omstandigheden, zoals de aanwezige beek- en oevervegetatie, terwijl de toestroom van voedingsstoffen en bodemdeeltjes, de hydrologie en de karakteristieken van de beekbedding worden beïnvloed door regionale omstandigheden, zoals de eigenschappen van het omliggende landschap en het landgebruik stroomopwaarts en op de flanken van ieder specifieke beektraject. De onderliggende mechanismen die de negatieve effecten van het bovenstroomse en zijdelingse landgebruik op beekecosystemen bewerkstelligen zijn echter nog grotendeels onbekend. Het doel van dit proefschrift was daarom de mechanismen waardoor landgebruik de structuur en functie van beekecosystemen aantast te ontrafelen.

Hiertoe zijn de volgende doelstellingen geformuleerd: • Het evalueren van beekherstelprojecten die zijn uitgevoerd in de afgelopen 40 jaar door het vaststellen van de invloed van 1) de beleidsdoelen, 2) de biofysische hersteldoelen, 3) de herstelmaatregelen, 4) de schaal van de ingezette maatregelen en 5) de monitoring.

• Het ontrafelen van de mechanismen waarmee de toevoer van terrestrisch materiaal de samenstelling van het sediment en de macrofaunagemeenschappen in depositiezones van laaglandbeken bepaald.

• Het vaststellen of de sedimentkarakteristieken van laaglandbeken, in termen van voedselbronnen en habitatstructuur, landgebruik specifiek zijn en of deze sedimentkarateristieken de samenstelling van de macrofaunagemeenschappen bepaalt.

• Het vaststellen van de invloed van het omliggende landgebruik op de structuur (de samenstelling van de macrofaunagemeenschappen) en het functioneren (de zuurstofhuishouding) van laaglandbeken.

187

Samenvatting • Het toepassen van een nieuwe beekherstelbenadering, bestaande uit het suppleren van zand in combinatie met het inbrengen van dood hout om beekbodeminsijding teniet te doen en de beek weer met haar dal te verbinden.

Het doel van hoofdstuk 2 was om 40 jaar praktijkervaring met beekherstelprojecten te evalueren om de oorzaken van het geringe succes van deze projecten te achterhalen en hiervan te leren voor de toekomst. Hiervoor is de invloed van beleidsdoelen op de inspanningen om tot herstel te komen vastgesteld en zijn de biofysische hersteldoelen, de uitgevoerde herstelmaatregelen, de schaal waarop deze maatregelen zijn toegepast en de bijgaande monitoringsprogramma’s geëvalueerd. De benodigde informatie werd verkregen uit vijf enquêtes gehouden onder de Nederlandse waterschappen die de afgelopen 40 jaar omvatten en uit een analyse van de internationale wetenschappelijke literatuur over laaglandbeekherstel gedurende dezelfde periode. Onze studie toonde een aanzienlijke toename van het aantal herstelprojecten

aan

over

deze

periode,

met

name

gemotiveerd

door

milieuwetgevingen. Monitoringprogramma’s om de effecten van de uitgevoerde herstelmaatregelen te volgen bleven echter vaak achterwege. Bovendien kwamen de getroffen herstelmaatregelen vaak slecht overeen met de gestelde doelen.

Herstelmaatregelen zijn nog steeds vooral gericht op morfologische aanpassingen, terwijl andere aspecten en biologische doelen onderbelicht blijven. Deze verdienen meer aandacht wil het succes van herstelprojecten toenemen. Bovendien vinden herstelmaatregelen vaak plaats op kleine schaal, ondanks het breed gedragen inzicht van het belang van de veel grotere schalen waarop ecologische processen plaatsvinden en de relevantie daarvan voor succesvol beekherstel. Om het slagingspercentage van beekherstelprojecten te vergroten is aanbevolen om meer toegesneden monitoringsprogramma’s te ontwerpen, waardoor het mogelijk wordt om te evalueren of de toegepaste maatregelen daadwerkelijk tot het gewenste herstel leiden. Ook wordt daarmee inzicht verkregen in de tijdschaal van herstel. Een tweede aanbeveling betrof het opschalen van beekherstelprojecten van lokale inspanningen in de beekbedding tot stroomgebiedsbrede maatregelen om ook negatieve invloeden op regionale schaal en stroomgebiedsniveau aan te pakken.

Het doel van hoofdstuk 3 was om te onderzoeken hoe instromend fijn organisch materiaal van terrestrische oorsprong, afkomstig van verschillende typen landgebruik, de samenstelling van het sediment en de macrofaunagemeenschappen in de depositiezones van laaglandbeken beïnvloedt. Hiertoe werd een chemische karakterisering uitgevoerd van het instromende fijn organisch materiaal en van het 188

The landscape drives the stream

sediment in de depositiezones van de aangrenzende beken. Ook werden de biologische effecten van instromend fijn organisch materiaal vastgesteld op soorts-, levensgemeenschaps- en ecosysteemniveau. Zowel de samenstelling van het instromende fijn organisch materiaal, van het sediment van de depositiezones in de beken en de biologische effecten verschilden sterk tussen bosbeken en beken die door landbouwgebieden stroomden. De C/N-ratio van het sediment in de depositiezones weerspiegelde die van het instromende terrestrische materiaal.

Sediment van de depositiezones van de bosbeken vertoonde een hogere C/N-ratio in vergelijking met landbouwbeken. De groei in bioassays van Hyalella azteca en de voortplanting van Asellus aquaticus waren hoger op bosbeeksediment, terwijl dansmuggen en wormen juist minder sterfte op de landbouwbeeksedimenten dan op het bosbeeksediment vertoonden indien geen extra voedsel werd toegevoegd. De depostiezones in de bosbeken werden gekenmerkt door hogere waarden voor biotische indices die indicatief zijn voor biologische integriteit en door een lagere zuurstofbehoefte van het sediment. We concludeerden dat landbouw de depositiezones in laaglandbeken aantast op soort-, levensgemeenschap en ecosysteemniveau door een veranderde voedselkwaliteit (C/N-ratio) en een hogere zuurstofbehoefte van het sediment. Deze resultaten motiveerden ons om de effecten van landgebruik op het zuurstofregime, de voedselbronnen en de habitatstructuur in laaglandbeken in meer detail te onderzoeken in de hoofdstukken 4 en 5.

Het doel van hoofdstuk 4 was om de invloed van het omliggende landgebruik vast te stellen op de structuur en het functioneren van laaglandbeken, om zo de landgebruik specifieke effecten van de instroom van fijn organisch materiaal van terrestrische oorsprong op laaglandbeken te ontrafelen en om de onderliggende mechanismen aan het licht te brengen. Hiertoe werden twintig beken omgeven door vijf verschillende typen landgebruik geselecteerd. In deze beken werden vervolgens sediment- en waterkwaliteit parameters gemeten, de dagelijkse patronen in opgeloste

zuurstof

regimes

vastgelegd

en

de

samenstelling

van

de

macrofaunagemeenschappen bepaald. De resultaten toonden aan dat het type landgebruik invloed had op de samenstelling van het fijn particulair organisch materiaal waarmee het sediment bedekt is, het organisch materiaalgehalte van het sediment en de concentraties van voedingsstoffen in het sediment. Deze sedimentkarakteristieken bleken de metabolische processen in de beek te veranderen, zoals de primaire productie, de respiratie en de zuurstofbehoefte van het sediment, wat vervolgens leidde tot grote verschillen in de samenstelling van de macrofaunagemeenschappen. We beargumenteerden daarom dat de landgebruik189

Samenvatting

specifieke invloeden op laaglandbeken worden uitgeoefend via de accumulatie van fijn sediment of slib in de depositiezones, wat het belang onderschrijft van het opnemen

van

regionale

en

stroomgebiedbrede

invloeden

in

ecologische

waterkwaliteitsbeoordelingen.

De instroom van landgebruik specifiek organisch materiaal in laaglandbeken kan ook invloed hebben op de sedimentkarakteristieken in termen van voedselbronnen en habitatstructuur voor de macrofauna. Daarom hebben we in hoofdstuk 5 onderzocht in welke mate landgebruik specifieke sedimentkarakteristieken de samenstelling van macrofaunagemeenschappen bepalen. Hiertoe hebben we lineaire meervoudige regressiemodellen

ontworpen,

macrofaunagemeenschappen

als

waarin

biotische

responsvariabelen

indices

werden

van

beschouwd

de en

sedimentkarakteristieken als voorspellende variabelen., Met deze regressiemodellen zijn 20 laaglandbeken die door vijf verschillende typen landgebruik stroomden geanalyseerd.

De

sedimentkarakteristieken

en

de

samenstelling

van

de

macrofaunagemeenschappen bleken landgebruik specifiek. De C/N-ratio, de aanwezigheid van grof organisch materiaal op de beekbodem en de oorsprong van de vetzuren

in

het

sediment

bepaalden

de

samenstelling

van

de

macrofaunagemeenschappen. De Shannon-Wiener diversiteit werd het best verklaard door de oorsprong van de vetzuren in het sediment, zoals in de beken die door graslanden stroomden, waarin een groter aandeel van planten afkomstige vetzuren gepaard ging met een hogere macrofaunadiversiteit. Het sediment van beken die door landbouwgebieden stroomden en beken die afvalwaterzuiveringseffluent ontvingen werden gekenmerkt door een lage C/N ratio. In deze beken werden hogere dichtheden van wormen en dansmuggen van het geslacht Chironomus waargenomen.

De EPT (Ephemeroptera, Plecoptera and Trichoptera) soortenrijkdom was positief gerelateerd aan een beekbodembedekking met grof organisch materiaal, wat alleen voorkwam in de bosbeken. De samenstelling van de macrofaunagemeenschappen werd dus beĂŻnvloed door de oorsprong van het organisch materiaal op en in het sediment, dat allochtoon (van buiten de beek) of autochtoon (in de beek zelf geproduceerd) kan zijn en als het autochtoon is, van autotrofe (plantaardig) of van heterotrofe (bacterieel of dierlijk) origine is. Ondanks de waargenomen relatie tussen de sedimenkarakteristieken en de samenstelling van de macrofaunagemeenschappen, is de sedimentsamenstelling uiteraard niet de enige stuurfactor die de samenstelling van de macrofaunagemeenschappen bepaalt. Maar als aan de randvoorwaarden van de andere ecologische stuurfactoren, zoals de zuurstofbeschikbaarheid, de

190

The landscape drives the stream

habitatstructuur

en

de

stroomsnelheid

wordt

voldaan,

dan

kan

de

sedimentsamenstelling zeker gezien worden als een ecologische sleutelfactor.

In hoofdstuk 6 is een experimentele studie uitgevoerd om een nieuwe beekhersteltechniek te testen voor beken met een ingesneden beekbedding. Deze nieuwe hersteltechniek bestaat uit het suppleren van zand aan de beekbedding in combinatie met de introductie van dood hout. Het doel van deze studie was het evalueren of het suppleren van zand aan de beekbedding op relatief korte termijn de hydromorfologische complexiteit van de beek kan verbeteren, leidend tot een verhoging van de diversiteit van de macrofaunagemeenschappen. Hiertoe werden tijdens en kort na een zandsuppletie het transport van zanddeeltjes, de waterdiepte, de stroomsnelheid, de zuurstofconcentratie en de sedimentsamenstelling gemeten.

De samenstelling van de macrofaunagemeenschappen werd opgenomen tijdens de verschillende fasen van het verstorings- (de suppletie) en herstelproces. Direct stroomafwaarts van de plek waarop het zand in de beek werd gestort vond in eerste instantie intensieve erosie, transport en sedimentatie van zand plaats, totdat een nieuw evenwicht was bereikt en de fysische condities stabiliseerden. Het behandelde traject van de beek ontwikkelde zich snel, omdat de vorming van nieuw habitat zich relatief

snel

voltrok.

In

eerste

instantie

nam

de

diversiteit

van

de

macrofaunagemeenschappen af, maar deze nam weer snel toe na het stabiliseren van het habitat. Bovendien werd een toename van het aantal stromingsminnende soorten waargenomen in de nieuw gevormde habitats. Dus hoewel het suppleren van zand in eerste instantie het beekecosysteem verstoorde, vond er een relatief snel fysisch en biologisch herstel plaats, leidend tot verbeterde habitatcondities voor een meer diverse macrofaunalevensgemeenschap, inclusief stromingsminnende soorten. We concludeerden daarom dat het suppleren van zand in ingesneden laaglandbeken een veelbelovende herstelmaatregel is.

Om zowel de landgebruik-specifieke stressor-respons relaties beter te begrijpen en om landgebruik specifieke herstelmaatregelen te faciliteren werd in hoofdstuk 7 een raamwerk voorgesteld waarin de resultaten van de vorige hoofdstukken werden geĂŻntegreerd. De landgebruik-specifieke effecten op de macrofaunagemeenschappen

in

laaglandbeken

werden

achtereenvolgens

omschreven als de druk uitgeoefend door landgebruik, de veroorzaakte stress, de invloed op ecologische sleutelfactoren en de abotische en biotische responsen, analoog aan het DPSIR-raamwerk (driver, pressure, state, impact and response). Dit

191

Samenvatting

raamwerk helpt het beekherstel vooruit maar het moet nog wel in de praktijk worden getoetst.

Gebaseerd op de resultaten van dit proefschrift werden de volgende conclusies getrokken: • De landgebruik-specifieke invloed op laaglandbeken wordt bewerkstelligd door de ophoping van uitgespoelde deeltjes in depositiezones.

• Zuurstofbeschikbaarheid, ecologische

habitatheterogeniteit

sleutelfactoren

die

de

en

voedselbronnen

samenstelling

van

zijn de

macrofaunagemeenschappen beïnvloeden.

• Stroomgebiedsbrede invloeden dienen te worden opgenomen in de ecologische waterkwaliteitsbeoordeling van laaglandbeken.

In dit proefschrift is aangetoond dat het landschap de beek dicteert, en dat alleen door het ontrafelen van de onderliggende mechanismen er locatie specifieke herstelmaatregelen kunnen worden genomen die daadwerkelijk verbeteringen teweegbrengen.

Het belang van het opnemen van stroomgebiedsbrede invloeden betreft niet alleen de ecologische waterkwaliteitsbeoordeling van laaglandbeken, maar ook het verbeteren van de keuzen van herstelmaatregelen. Hieraan zou de kennis verkregen in dit proefschrift als volgt kunnen bijdragen: 1. Het identificeren van de toestroom van organische bodemdeeltjes van terrestrische (landgebruiks-)oorsprong en voedingsstoffen van verschillende bronnen van menselijk handelen. 2. Het ontwerpen van landgebruik specifieke herstelmaatregelen. 3. Het verbeteren van de kwaliteit van het effluent van afvalwaterzuiveringsinstallaties en het beter beheersen van de lozingen van effluent. 4. Het tegenhouden bij de bron van water, organische bodemdeeltjes en voedingsstoffen die van het land afspoelen. 5. Het ontwikkelen en stimuleren van natuurlijke en duurzame vormen van landgebruik langs laaglandbeken.

Zolang de rechten van een beek, zoals het vrij stromen en het vrij zijn van overtollige voedingsstoffen en verontreinigingen, niet worden gerespecteerd en wettelijk worden opgenomen in onze samenleving ben ik van mening dat het moeilijk is om te begrijpen hoe het landschap de stroom dicteert en dat niet ten volle van het laaglandbeeklandschap genoten kan worden.

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Acknowledgements

Acknowledgments

“A vida é a arte do encontro…” Vinicius de Moraes I definitely agree with Vinicius de Moraes when he says that life is the art of encountering. During my PhD I could experience some of that, where along the process of developing scientific skills I met many helpful and amazing people. Now, this is a great part of the thesis where I can acknowledge them!

First, I would like to thank my promotors and co-promotors Piet Verdonschot, Michiel Kraak, Harm van der Geest and Ralf Verdonschot for sharing knowledge, ideas and guiding me through the PhD. I'm very grateful to each one of them, from whose I've learned something different and complementary.

Piet, your work with applied ecology motivates me! Thanks for considering and replying to my email when I started dreaming about a PhD in 2012. Since then you have supported me in many ways, willing to solve “challenges”, looking for good streams to sample, sharing ideas and sending me to courses and conferences. With you, I've learned a lot about freshwater ecology and how to be prepared with strong arguments.

Michiel, thanks for your kindness, wines after submitting a manuscript to a journal and to share Dutch culture and stories. You were always present and aware of my PhD. With you, I would never lose a deadline! I've learned a lot from your teaching skills, commitment, and manuscript revisions.

Harm, thanks for being full of ideas and a positive and very happy person.

Meeting you for feedbacks were always smooth and helped me to build up motivation and confidence.

The challenges of my daily PhD life were accompanied by my “PhD Pieting Partners”: Judith, Tiedo, Milo, Jip, Gea, Nienke, Rob and Bart. Many thanks for your presence and help in the field, the lab, in R, with presentations and text feedback, advice, Dutch letter translations and sharing experiences. Whenever I would ask for help, I kindly got good answers! I can't image my PhD life without you! Judith, you were the first person who received me at UvA, and it couldn't be better! You have been a great colleague and friend, always willing to help, to talk, to have a beer and to dance salsa! Tiedo, I really enjoyed our time at UvA, helpful feedback, writing course organization partnership and dinner/beer celebrations. Milo, thanks for being a positive person and willing to help. I really appreciated your advice and our 195

Acknowledgments

conversations about life and science. Jip, your kindness is contagious! I always had a good time with you at work, cycling and outside work. Gea, you were a conference partner, a great colleague to discuss R related problems and solving metabolism calculation problems. I really enjoyed our time in the Blue Mountains ridge, hunting for the nicest animal picture! Nienke, you are an example of biologist and hard worker for me! You made our office a better place to be.

I also would like to thank my other “freshwater” colleagues Ciska, Charlotte, Cherel, Anca, Catarina, Tom, Jason, Tim and Vittorio, and the “marine” colleagues Meggie, Martijn, and Nik for the good time that we had together. Special thanks for Sara’s friendship, kindness, Italian food and garden activities partnership, we had a great time!

To my dear IBED colleagues Milan and Marian. I had many funny and enjoyable moments with you at UvA and in outside activities.

Dear Dorine, I had a great time with you in the field and lab! I am very grateful for your friendship and help with macroinvertebrate- identification and solving ANY kind of problem with experiments. You have inspired me!

I would like to thank all technicians from UvA, but especially Mariska, Leo, Merijn, Chiara, Joke, Samira, Rick, Jorien, Peter, Leen and Rutger for being nice and enjoyable people.

Dear secretaries Maria Dolorita, Mary, Tanya and Pascale thanks for all your help, kindness and smiles!

I would like to thanks the Dutch water authorities and Natuurmonumenten for their support in this research and for saving me from being stuck in the mud and from angry farmers.

Dear students Tom, Ton, Joana and Jan-Thijs, thanks for helping me gathering data and for our enjoyable time in the field and lab. Special thanks to the master students Sofia, Michelle and Dani. You were my research partners, helpers and friends!

João Lotufo, my life partner who also became the best fieldwork partner, time planner coach, thesis formatter and cook, thank you! Your good pizza improved 196

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my PhD social life! You also helped me to grow up as a person, being faithful in the most difficult moments of our life during a PhD in a foreign country.

I am and will be eternally grateful for my beloved parents Maria Alice and JosĂŠ Carlos, sisters Thays and Thelma and niece Beatriz. With you I always find support and a safe place to be.

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Curriculum vitae

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Curriculum

Paula Caroline dos Reis Oliveira was born on 22nd of June 1983, in São Paulo, Brazil. In 2004, she obtained a bachelor’s degree in Biology at the Institute of Biosciences from the São Paulo State University (UNESP). During her graduation, she completed her first freshwater research project on the effects of a cascade of large reservoirs constructed for hydropower generation on the aquatic biota of zooplankton populations. For this project, she was granted a scholarship from São Paulo research foundation FAPESP (02/07228-2; 99/09667-9). Shortly thereafter, in 2006, she obtained a teaching degree in Biology at the São Paulo State University (UNESP). In the next year of 2007, she started a master research project on benthic macroinvertebrate community composition, water and sediment quality in the Capivara, Lavapés, Araguá and Pardo rivers in Botucatu, São Paulo with a scholarship granted from CNPq (131802/2007-0). After completing her master in Biological Sciences (Zoology) at the Institute of Biosciences, São Paulo State University (UNESP) in 2009 she worked for five years at the Secretary for the Environmental of São Paulo city where she applied the law of environmental crimes and managed the monitoring of lakes water quality in urban parks. The experience of dealing with environmental problems concerning land use occupation and freshwater degradation motivated her to look for environmentally driven solutions, resulting in a PhD project in applied ecology for restoration of freshwater ecosystems at the University of Amsterdam, IBED department of Freshwater and Marine Ecology under the supervision of dr. ir.

Piet Verdonschot and dr. Michiel Kraak supported by the program Science Without Borders (CNPq 200879/2014-6) leading to the present thesis. Paula aims to continue her career in ecological restoration of freshwaters by bridging science and management.

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