# Agricultural land use weakens the relationship between biodiversity and ecosystem functioning

Alexander Feckler, Jacob Schnurr, Gabriela Kalčíková, Amélie Truchy, Brendan G Mckie, Ralf B Schäfer, Ralf Schulz, Mirco Bundschuh

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Alexander Feckler, Jacob Schnurr, Gabriela Kalčíková, Amélie Truchy, Brendan G Mckie, et al. Agricultural land use weakens the relationship between biodiversity and ecosystem functioning. Oikos, 2023, 2023 (10), 10.1111/oik.09936. hal-04515536

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OIKOS

Research article

Agricultural land use weakens the relationship between
biodiversity and ecosystem functioning

Alexander Feckler ID <fnref n="1" />,<fnref n="2" />,<fnref n="3" />, Jacob Schnurr<fnref n="2" />, Gabriela Kalčíková<fnref n="4" />, Amélie Truchy<fnref n="1" />,<fnref n="5" />, Brendan G. McKie<fnref n="1" />,
Ralf B. Schäfer<fnref n="2" />, Ralf Schulz<fnref n="2" />,<fnref n="3" /> and Mirco Bundschuh<fnref n="1" />,<fnref n="2" />

**Correspondence:** Alexander Feckler (alexander.fleckler@rptu.de)

Oikos

2023: e09936

doi: 10.1111/oik.09936

Subject Editor: Christopher Swan

Editor-in-Chief: Dries Bonte

Accepted 09 June 2023

<figure><img src="image_2.png" /></figure>

Leaf litter decomposition is a significant ecosystem process for streams' energy provisioning, while species-specific decomposition rates often form a continuum from slow to fast decomposing species allowing for resources' availability to stream consumers over a longer time period after leaf fall. Leaf litter mixtures in streams typically comprise leaf species varying in their traits, allowing for litter diversity effects on decomposition. At the same time, agricultural land use, habitat characteristics, water quality and invertebrate composition modulate leaf litter decomposition. To identify leaf litter diversity effects and disentangle the roles of agricultural intensity, habitat characteristics, water quality and invertebrate composition for leaf litter processing in streams, we quantified leaf litter decomposition of three leaf species covering a gradient from slow to fast decomposing species, tested either individually or as a three-species mixture. The study was conducted over 21 days across 18 streams with a gradient of agricultural intensity (percent agricultural land use) in their catchments. We found leaf litter diversity effects in terms of complementarity under low to intermediate agricultural intensity, given that slow decomposing leaf species decomposed almost twice as fast in the three-species mixture compared to the observations on individual leaf species. This leaf litter diversity effect decreased with increasing agricultural intensity, suggesting that agriculture weakens the biodiversity-ecosystem functioning relationship. However, pathways by which agriculture affected decomposition differed between single-species and mixed-species scenarios. For the single-species scenario, negative effects of agriculture appeared to be mediated through effects on the proportion of sensitive detritivore species and altered habitat characteristics. For the mixed-species scenario, altered water quality negatively affected the proportion of sensitive detritivore species, in turn reducing the diversity effect on functioning. Our results suggest that the weakened biodiversity-ecosystem functioning relationship under increasing agricultural intensity might be a significant factor threatening carbon cycling and food web integrity in streams.

Keywords: biodiversity-ecosystem functioning, complementarity, detritivore, detritus breakdown, leaf litter mixture, litter quality

<figure><img src="image_3.png" /></figure>

www.oikosjournal.org

<footnote n="1">¹Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden</footnote>

<footnote n="2">²iES Landau, Institute for Environmental Sciences, RPTU Kaiserslautern-Landau, Landau, Germany</footnote>

<footnote n="3">³Eusserthal Ecosystem Research Station, RPTU Kaiserslautern-Landau, Eusserthal, Germany</footnote>

<footnote n="4">⁴Faculty of Chemistry and Chemical Technology, University of Ljubljana, Ljubljana, Slovenia</footnote>

<footnote n="5">⁵INRAE, UR RiverLy, Centre Lyon-Grenoble Auvergne-Rhône-Alpes, Villeurbanne, France</footnote>
<figure><img src="image_2.png" /></figure>

## Research article

# Agricultural land use weakens the relationship between biodiversity and ecosystem functioning

Alexander Feckler<fnref n="1" />,<fnref n="2" />,<fnref n="3" />, Jacob Schnurr<fnref n="2" />, Gabriela Kalčíková<fnref n="4" />, Amélie Truchy<fnref n="1" />,<fnref n="5" />, Brendan G. McKie<fnref n="1" />, Ralf B. Schäfer<fnref n="2" />, Ralf Schulz<fnref n="2" />,<fnref n="3" /> and Mirco Bundschuh<fnref n="1" />,<fnref n="2" />

**Correspondence:** Alexander Feckler (alexander.fleckler@rptu.de)

Oikos

2023: e09936

doi: 10.1111/oik.09936

Subject Editor: Christopher Swan

Editor-in-Chief: Dries Bonte

Accepted 09 June 2023

<figure><img src="image_3.png" /></figure>

Leaf litter decomposition is a significant ecosystem process for streams' energy provisioning, while species-specific decomposition rates often form a continuum from slow to fast decomposing species allowing for resources' availability to stream consumers over a longer time period after leaf fall. Leaf litter mixtures in streams typically comprise leaf species varying in their traits, allowing for litter diversity effects on decomposition. At the same time, agricultural land use, habitat characteristics, water quality and invertebrate composition modulate leaf litter decomposition. To identify leaf litter diversity effects and disentangle the roles of agricultural intensity, habitat characteristics, water quality and invertebrate composition for leaf litter processing in streams, we quantified leaf litter decomposition of three leaf species covering a gradient from slow to fast decomposing species, tested either individually or as a three-species mixture. The study was conducted over 21 days across 18 streams with a gradient of agricultural intensity (percent agricultural land use) in their catchments. We found leaf litter diversity effects in terms of complementarity under low to intermediate agricultural intensity, given that slow decomposing leaf species decomposed almost twice as fast in the three-species mixture compared to the observations on individual leaf species. This leaf litter diversity effect decreased with increasing agricultural intensity, suggesting that agriculture weakens the biodiversity-ecosystem functioning relationship. However, pathways by which agriculture affected decomposition differed between single-species and mixed-species scenarios. For the single-species scenario, negative effects of agriculture appeared to be mediated through effects on the proportion of sensitive detritivore species and altered habitat characteristics. For the mixed-species scenario, altered water quality negatively affected the proportion of sensitive detritivore species, in turn reducing the diversity effect on functioning. Our results suggest that the weakened biodiversity-ecosystem functioning relationship under increasing agricultural intensity might be a significant factor threatening carbon cycling and food web integrity in streams.

Keywords: biodiversity-ecosystem functioning, complementarity, detritivore, detritus breakdown, leaf litter mixture, litter quality

<figure><img src="image_4.png" /></figure>

<footnote n="1">¹Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden</footnote>

<footnote n="2">²iES Landau, Institute for Environmental Sciences, RPTU Kaiserslautern-Landau, Landau, Germany</footnote>

<footnote n="3">³Eusserthal Ecosystem Research Station, RPTU Kaiserslautern-Landau, Eusserthal, Germany</footnote>

<footnote n="4">⁴Faculty of Chemistry and Chemical Technology, University of Ljubljana, Ljubljana, Slovenia</footnote>

<footnote n="5">⁵INRAE, UR RiverLy, Centre Lyon-Grenoble Auvergne-Rhône-Alpes, Villeurbanne, France</footnote>
Introduction

Ecosystem processes that regulate the flux and transformation of energy and nutrients are paramount for the functioning of ecosystems (Gessner and Chauvet 2002). One ecosystem process of prime importance for the energy supply in heterotrophic stream food webs is the decomposition of terrestrially-derived leaf litter by microbial decomposers and invertebrate detritivores (Gessner and Chauvet 2002). Microbial decomposers contribute comparatively little to bulk leaf litter decomposition in temperate regions (Hieber and Gessner 2002). However, fungi especially play a key role in increasing litter nutrient content and degrading recalcitrant structural components, increasing the palatability and nutrient content of litter as a food source for invertebrate detritivores (Bärlocher 1985).

The rates at which leaf litter is microbially colonized and subsequently decomposed by detritivores strongly depend on the leaf species (Swan et al. 2009). The chemical composition of leaf litter is a crucial factor that controls process rates, since decomposers and detritivores prefer substrates with a high content of labile carbon (C) and nutrients (Graça 2001, Gessner et al. 2007). Leaf litter mixtures in streams typically comprise multiple leaf species varying in chemical composition, and consumers are able to optimize net energy and nutrient intake and resolve stoichiometric imbalances by feeding across multiple leaf species (Hladyz et al. 2009, Frainer et al. 2016). This ‘complementary resource use’ by detritivores (McKie et al. 2008) and decomposers such as fungi (Jabiol et al. 2013) can further enhance rates of C and nitrogen (N) cycling in leaf litter mixtures compared to single species (Gessner et al. 2010, Handa et al. 2014).

The generic term ‘complementarity’ is used to describe a broad class of mechanisms underpinning the influences of biodiversity on ecosystem functioning (Gessner et al. 2010), which occur when the interplay among species results in a non-additive change in ecosystem process rates. Complementary resource use by detritivores is one example whereby different species feeding on different components of the leaf litter resource might result in not only more efficient leaf litter decomposition, but also greater biomass production (Cardinale et al. 2006). Another mechanism is facilitation, whereby the activities of some organisms enhance activities of others (Gessner et al. 2010). An example is fungal-mediated N-transfer among leaf litter species of different chemical composition (Handa et al. 2014), which speeds conditioning and decomposition of less nitrogen rich species, and thus facilitates feeding by detritivores. In contrast to these mechanisms involving multiple species, the ‘selection effect’ occurs when biodiversity effects are mainly caused by a single species, which harbors traits that change its performance in multi-species assemblages (Tilman et al. 1997, Loreau and Hector 2001). For instance, leaf chemistry in terms of tan-nin and lignin content can lead to an increased (positive selection) or decreased (negative selection) feeding of detri-tivores on leaf species in multi-species assemblages compared to the monoculture (Hättenschwiler and Bretscher 2001,

López-Rojo et al. 2021). The relative importance of complementarity and the selection effects for leaf litter decomposition documented in manipulative experiments, including those conducted in situ in some form of enclosure, have been idiosyncratic. While some studies resulted in positive (faster decomposition of slow decomposing litter species) effects of diversity on functioning, others reported constraining (slower decomposition of fast decomposing litter species) or null effects (Kominoski et al. 2010).

An additional challenge in predicting substrate diversity effects is understanding the influence of altered biotic and abiotic environmental factors, which might modify the biodiversity effects. For example, human impacts that shape assemblages of organisms and their resources may affect biodiversity effects on leaf litter decomposition through alteration of the occurrence and relative abundances of key species (Heffernan et al. 2014). In this context, agricultural land use is associated with changes in the structure of the riparian vegetation and in-stream habitat characteristics, and impacts on the water quality of streams (Allan 2004). As a consequence, agricultural land use has the potential to disrupt biodiversity effects on leaf litter decomposition by altering the leaf litter mixtures entering streams as well as the diversity and composition of detritivore communities, ultimately altering the process rates of leaf litter (Truchy et al. 2022).

In this study we aimed to identify leaf litter diversity effects and disentangle the roles of agricultural intensity, habitat characteristics, water quality and invertebrate metrics (e.g. Shannon index, metabolic capacity, and SPEAR<sub>pesticides</sub> as an index of the ratio of sensitive to tolerant species) for leaf litter processing in streams. We quantified microbially-mediated and detritivore-mediated leaf litter decomposition of three leaf species that cover a gradient from slow to fast decomposing species (pedunculate oak, black locust, and black alder), tested either individually or as a three-species mixture. The study was conducted for 21 days across 18 streams in southern Sweden, ranging from forested least-disturbed sites (low agricultural intensity in the streams' catchments) to sites heavily degraded by high agricultural activity, including those associated with the use of fertilizers and land-use changes in the riparian zone (e.g. loss of riparian vegetation and consequently increased sediment transport into the streams). The agricultural practices in the streams' catchments consisted of production of crops such as cereals, beets, brassicas, potatoes, and legumes (Raderschall et al. 2021) and a minor share of orchards and pasture (own observation, Fig. 1). In accordance with previous studies (Truchy et al. 2022), we expected increasing agricultural intensity to compromise leaf litter decomposition rates driven by alterations in habitat characteristics, water quality and invertebrate metrics. The hypothesized pathways by which leaf litter decomposition rates are affected were visualized and tested using structural equation models. Consistent with biodiversity-ecosystem functioning theory (Gessner et al. 2010), we hypothesized that the strongest complementarity effects will be observed in streams supporting the highest detritivore diversity, which are expected to be our sites exhibiting low agricultural intensity
Introduction

Ecosystem processes that regulate the flux and transformation of energy and nutrients are paramount for the functioning of ecosystems (Gessner and Chauvet 2002). One ecosystem process of prime importance for the energy supply in heterotrophic stream food webs is the decomposition of terrestrially-derived leaf litter by microbial decomposers and invertebrate detritivores (Gessner and Chauvet 2002). Microbial decomposers contribute comparatively little to bulk leaf litter decomposition in temperate regions (Hieber and Gessner 2002). However, fungi especially play a key role in increasing litter nutrient content and degrading recalcitrant structural components, increasing the palatability and nutrient content of litter as a food source for invertebrate detritivores (Bärlocher 1985).

The rates at which leaf litter is microbially colonized and subsequently decomposed by detritivores strongly depend on the leaf species (Swan et al. 2009). The chemical composition of leaf litter is a crucial factor that controls process rates, since decomposers and detritivores prefer substrates with a high content of labile carbon (C) and nutrients (Graça 2001, Gessner et al. 2007). Leaf litter mixtures in streams typically comprise multiple leaf species varying in chemical composition, and consumers are able to optimize net energy and nutrient intake and resolve stoichiometric imbalances by feeding across multiple leaf species (Hladyz et al. 2009, Frainer et al. 2016). This ‘complementary resource use’ by detritivores (McKie et al. 2008) and decomposers such as fungi (Jabiol et al. 2013) can further enhance rates of C and nitrogen (N) cycling in leaf litter mixtures compared to single species (Gessner et al. 2010, Handa et al. 2014).

The generic term ‘complementarity’ is used to describe a broad class of mechanisms underpinning the influences of biodiversity on ecosystem functioning (Gessner et al. 2010), which occur when the interplay among species results in a non-additive change in ecosystem process rates. Complementary resource use by detritivores is one example whereby different species feeding on different components of the leaf litter resource might result in not only more efficient leaf litter decomposition, but also greater biomass production (Cardinale et al. 2006). Another mechanism is facilitation, whereby the activities of some organisms enhance activities of others (Gessner et al. 2010). An example is fungal-mediated N-transfer among leaf litter species of different chemical composition (Handa et al. 2014), which speeds conditioning and decomposition of less nitrogen rich species, and thus facilitates feeding by detritivores. In contrast to these mechanisms involving multiple species, the ‘selection effect’ occurs when biodiversity effects are mainly caused by a single species, which harbors traits that change its performance in multi-species assemblages (Tilman et al. 1997, Loreau and Hector 2001). For instance, leaf chemistry in terms of tan-nin and lignin content can lead to an increased (positive selection) or decreased (negative selection) feeding of detri-tivores on leaf species in multi-species assemblages compared to the monoculture (Hättenschwiler and Bretscher 2001,

López-Rojo et al. 2021). The relative importance of complementarity and the selection effects for leaf litter decomposition documented in manipulative experiments, including those conducted in situ in some form of enclosure, have been idiosyncratic. While some studies resulted in positive (faster decomposition of slow decomposing litter species) effects of diversity on functioning, others reported constraining (slower decomposition of fast decomposing litter species) or null effects (Kominoski et al. 2010).

An additional challenge in predicting substrate diversity effects is understanding the influence of altered biotic and abiotic environmental factors, which might modify the biodiversity effects. For example, human impacts that shape assemblages of organisms and their resources may affect biodiversity effects on leaf litter decomposition through alteration of the occurrence and relative abundances of key species (Heffernan et al. 2014). In this context, agricultural land use is associated with changes in the structure of the riparian vegetation and in-stream habitat characteristics, and impacts on the water quality of streams (Allan 2004). As a consequence, agricultural land use has the potential to disrupt biodiversity effects on leaf litter decomposition by altering the leaf litter mixtures entering streams as well as the diversity and composition of detritivore communities, ultimately altering the process rates of leaf litter (Truchy et al. 2022).

In this study we aimed to identify leaf litter diversity effects and disentangle the roles of agricultural intensity, habitat characteristics, water quality and invertebrate metrics (e.g. Shannon index, metabolic capacity, and SPEAR<sub>pesticides</sub> as an index of the ratio of sensitive to tolerant species) for leaf litter processing in streams. We quantified microbially-mediated and detritivore-mediated leaf litter decomposition of three leaf species that cover a gradient from slow to fast decomposing species (pedunculate oak, black locust, and black alder), tested either individually or as a three-species mixture. The study was conducted for 21 days across 18 streams in southern Sweden, ranging from forested least-disturbed sites (low agricultural intensity in the streams' catchments) to sites heavily degraded by high agricultural activity, including those associated with the use of fertilizers and land-use changes in the riparian zone (e.g. loss of riparian vegetation and consequently increased sediment transport into the streams). The agricultural practices in the streams' catchments consisted of production of crops such as cereals, beets, brassicas, potatoes, and legumes (Raderschall et al. 2021) and a minor share of orchards and pasture (own observation, Fig. 1). In accordance with previous studies (Truchy et al. 2022), we expected increasing agricultural intensity to compromise leaf litter decomposition rates driven by alterations in habitat characteristics, water quality and invertebrate metrics. The hypothesized pathways by which leaf litter decomposition rates are affected were visualized and tested using structural equation models. Consistent with biodiversity-ecosystem functioning theory (Gessner et al. 2010), we hypothesized that the strongest complementarity effects will be observed in streams supporting the highest detritivore diversity, which are expected to be our sites exhibiting low agricultural intensity
<figure><img src="image_4.png" /><figcaption>Figure 1. Location of the study area (Skåne County; white area) and the sampling sites (black dots) in southern Sweden. Colors depict land cover types based on ESRI land cover data (ESRI 2022). Both ‘crops’ and ‘pasture’ are considered as ‘agricultural land’ in the analyses.</figcaption></figure>

in their catchments. Complementarity should increase the overall leaf litter decomposition rates in mixed-species leaf litterbags in general and the leaf litter decomposition rates of slow-decomposing leaf species in particular. Under increasing agricultural intensity, we hypothesized that biodiversity effects in general and complementarity in particular will weaken, in line with expected reductions in detritivore diversity, and also possible impacts of reduced habitat and water quality on the activity of organisms.

# Material and methods

## General study design

Environmental variables, stream-inhabiting macroinvertebrate communities, and a measure of ecosystem function (i.e. leaf-litter decomposition) were quantified across 18 low-order streams (Strahler stream order ≤ 3) situated in Skåne County, southern Sweden (Fig. 1, Supporting information), over a three-week period from 31 May to 21 June 2016. The sampling sites (i.e. stream reaches of ~25 m) were chosen to represent a gradient of agricultural intensity in the streams' catchments that is associated with an increasing pressure on in-stream species assemblages and functions they provide (Blann et al. 2009). Stream catchments were dominated by deciduous forests (including black alder and pedunculate oak trees in the riparian area), agriculture, or a combination of both (Fig. 1, Table 1). Agricultural intensity was quantified by first calculating the percentage contribution of each land-use category by delineating the topographic sub-catchments for each sampling site in QGIS (ver. 3.28.0-Firenze; QGIS 2021) using ESRI land cover data (ESRI 2022) and afterwards extracting the land-use data for the contributing

sub-catchments. Sampling sites with additional major upstream anthropogenic pressures (such as wastewater treatment plants, industrial facilities, and large urban areas) that potentially confound the interpretation of results were avoided. The streambeds were composed predominantly of medium and fine substrates (~ 30 and 50%, respectively), with some boulders and cobbles present at most of the sites (Table 1). To quantify decomposition of the three tested leaf species and detect potential litter diversity effects, we immersed leaves in single-species and mixed-species leaf litterbags at the sampling sites for up to 21 days.

## Environmental variables

We visually assessed the streambed substrate characteristics and plant cover within and along the streams at the time of study commencement for the respective stream reach of 25 m: the percentage contribution of coarse (boulder and cobble), medium (pebble and gravel), and fine sediments (sand and silt) as well as the coverage of the streambed by leaves and woods (ø < 10 cm), woods (ø > 10 cm) and submersed/immersed plants was estimated. In addition, the coverage by trees and shrubs along the riverbanks was estimated by eye. All variables except the sediment composition were measured using an ordinal scale that relied on the percentage proportion: 0%=0, 1–20%=1, 21–40%=2, 41–60%=3, 61–80%=4, 81–100%=5.

Conductivity, pH, dissolved oxygen concentration, flow velocity, stream width, and water depth were measured *in situ* at the study commencement and every seventh day thereafter (ProfiLine Multi 3320, Wissenschaftlich Technische Werkstätten GmbH; MiniAir20 with a Mini sensor 0.02–5 m s⁻¹, Schiltknecht, Gossau, Switzerland). All variables were
<figure><img src="image_5.png" /><figcaption>Figure 1. Location of the study area (Skåne County; white area) and the sampling sites (black dots) in southern Sweden. Colors depict land cover types based on ESRI land cover data (ESRI 2022). Both ‘crops’ and ‘pasture’ are considered as ‘agricultural land’ in the analyses.</figcaption></figure>

in their catchments. Complementarity should increase the overall leaf litter decomposition rates in mixed-species leaf litterbags in general and the leaf litter decomposition rates of slow-decomposing leaf species in particular. Under increasing agricultural intensity, we hypothesized that biodiversity effects in general and complementarity in particular will weaken, in line with expected reductions in detritivore diversity, and also possible impacts of reduced habitat and water quality on the activity of organisms.

# Material and methods

## General study design

Environmental variables, stream-inhabiting macroinvertebrate communities, and a measure of ecosystem function (i.e. leaf-litter decomposition) were quantified across 18 low-order streams (Strahler stream order ≤ 3) situated in Skåne County, southern Sweden (Fig. 1, Supporting information), over a three-week period from 31 May to 21 June 2016. The sampling sites (i.e. stream reaches of ~25 m) were chosen to represent a gradient of agricultural intensity in the streams' catchments that is associated with an increasing pressure on in-stream species assemblages and functions they provide (Blann et al. 2009). Stream catchments were dominated by deciduous forests (including black alder and pedunculate oak trees in the riparian area), agriculture, or a combination of both (Fig. 1, Table 1). Agricultural intensity was quantified by first calculating the percentage contribution of each land-use category by delineating the topographic sub-catchments for each sampling site in QGIS (ver. 3.28.0-Firenze; QGIS 2021) using ESRI land cover data (ESRI 2022) and afterwards extracting the land-use data for the contributing

sub-catchments. Sampling sites with additional major upstream anthropogenic pressures (such as wastewater treatment plants, industrial facilities, and large urban areas) that potentially confound the interpretation of results were avoided. The streambeds were composed predominantly of medium and fine substrates (~ 30 and 50%, respectively), with some boulders and cobbles present at most of the sites (Table 1). To quantify decomposition of the three tested leaf species and detect potential litter diversity effects, we immersed leaves in single-species and mixed-species leaf litterbags at the sampling sites for up to 21 days.

## Environmental variables

We visually assessed the streambed substrate characteristics and plant cover within and along the streams at the time of study commencement for the respective stream reach of 25 m: the percentage contribution of coarse (boulder and cobble), medium (pebble and gravel), and fine sediments (sand and silt) as well as the coverage of the streambed by leaves and woods (ø < 10 cm), woods (ø > 10 cm) and submersed/immersed plants was estimated. In addition, the coverage by trees and shrubs along the riverbanks was estimated by eye. All variables except the sediment composition were measured using an ordinal scale that relied on the percentage proportion: 0%=0, 1–20%=1, 21–40%=2, 41–60%=3, 61–80%=4, 81–100%=5.

Conductivity, pH, dissolved oxygen concentration, flow velocity, stream width, and water depth were measured *in situ* at the study commencement and every seventh day thereafter (ProfiLine Multi 3320, Wissenschaftlich Technische Werkstätten GmbH; MiniAir20 with a Mini sensor 0.02–5 m s⁻¹, Schiltknecht, Gossau, Switzerland). All variables were
<table><caption>Table 1. Descriptive statistics of environmental variables at the study sites (means, standard errors, minimum, and maximum; n=18). For more details see the Supporting information. <sup>a</sup>Measured using an ordinal scale (0–5). <sup>b</sup>Quantified for the entire stream catchment. <sup>c</sup>Mean from the left and right banks.</caption><thead><tr><th>Variable</th><th>Unit</th><th>Mean</th><th>SE</th><th>Min</th><th>Max</th></tr></thead><tbody><tr><td>Catchment size</td><td>ha</td><td>3171</td><td>608</td><td>914</td><td>11864</td></tr><tr><td>Width</td><td>m</td><td>2.3</td><td>0.2</td><td>1.4</td><td>4.8</td></tr><tr><td>Depth</td><td>m</td><td>0.19</td><td>0.02</td><td>0.07</td><td>0.34</td></tr><tr><td>Velocity</td><td>m s<sup>-1</sup></td><td>0.22</td><td>0.02</td><td>0.04</td><td>0.44</td></tr><tr><td>Temperature</td><td>°C</td><td>14.7</td><td>0.32</td><td>12.0</td><td>17.1</td></tr><tr><td>pH</td><td></td><td>7.73</td><td>0.05</td><td>7.36</td><td>8.01</td></tr><tr><td>Oxygen</td><td>mg l<sup>-1</sup></td><td>11.0</td><td>0.58</td><td>6.33</td><td>15.19</td></tr><tr><td>Conductivity</td><td>µS cm<sup>-1</sup></td><td>53.98</td><td>4.77</td><td>28</td><td>119</td></tr><tr><td>Alkalinity</td><td>meq l<sup>-1</sup></td><td>3.74</td><td>0.22</td><td>1.64</td><td>5.06</td></tr><tr><td>DIN</td><td>µg l<sup>-1</sup></td><td>2320.48</td><td>387.70</td><td>497</td><td>6020</td></tr><tr><td>PO<sub>4</sub><sup>3-</sup>-P</td><td>µg l<sup>-1</sup></td><td>101.44</td><td>32.97</td><td>7</td><td>578</td></tr><tr><td>Coarse substrates<br>(boulder and<br>cobble)</td><td>%</td><td>20.0</td><td>3.9</td><td>0.0</td><td>50.0</td></tr><tr><td>Medium<br>substrates<br>(pebble and<br>gravel)</td><td>%</td><td>31.1</td><td>4.6</td><td>5.0</td><td>70.0</td></tr><tr><td>Fine substrates<br>(sand and silt)</td><td>%</td><td>48.3</td><td>6.2</td><td>10.0</td><td>90.0</td></tr><tr><td>In-stream leaves<br>and wood (ø &lt;<br>10 cm)<sup>a</sup></td><td></td><td>0.9</td><td>0.08</td><td>0</td><td>1</td></tr><tr><td>In-stream wood<br>(ø &gt; 10 cm)<sup>a</sup></td><td></td><td>0.3</td><td>0.1</td><td>0</td><td>1</td></tr><tr><td>Immersed plants<sup>a</sup></td><td></td><td>1.2</td><td>0.3</td><td>0</td><td>4</td></tr><tr><td>Submerged<br>plants<sup>a</sup></td><td></td><td>1.0</td><td>0.1</td><td>0</td><td>1</td></tr><tr><td>Agricultural land<br>use<sup>b</sup></td><td>%</td><td>67.1</td><td>5.9</td><td>8.5</td><td>97.1</td></tr><tr><td>Forestry<sup>b</sup></td><td>%</td><td>19.7</td><td>5.2</td><td>0.0</td><td>73.6</td></tr><tr><td>Tree cover along<br>the bank<sup>c</sup></td><td></td><td>1.9</td><td>0.4</td><td>0</td><td>4</td></tr><tr><td>Shrub cover along<br>the bank<sup>c</sup></td><td></td><td>3.1</td><td>0.3</td><td>0</td><td>5</td></tr></tbody></table>

measured at the same stream location, where we set up a transect for water depth measurements (measured every 30 cm along the transect), which were averaged for every sampling site before entering the analyses. Stream temperatures were measured hourly using button data loggers (SmartButton; ACR Systems). Temperature data were converted to daily means for calculation of leaf litter breakdown rates per degree day (below), and were also averaged across the entire study period for use in statistical models. Water samples for analyses of alkalinity, total nitrogen, ammonium, nitrite and nitrate, total phosphorus, and phosphate were taken once at the commencement of the study and commercially analyzed using SWEDAC accredited methods.

Although we measured pesticides in the water phase at all sites during the study period (Supporting information), low rain fall in the study region during June 2016 (~ 18 l m⁻² over the entire month; long-term monthly average for June 1991–2020: ~ 61 l m⁻²; Sveriges meteorologiska och hydrol ogiska institut) led to low dissolved concentrations being

measured, given that the main entry route of pesticides into running waters is through rainfall-induced surface run-off (Schulz 2004). Therefore, the pesticide data had only a minor explanatory power for the outcome of the present study and were excluded from further analyses, but are provided in the Supporting information for the sake of transparency.

## Macroinvertebrate sampling, trait information, and variable selection

We quantitatively sampled macroinvertebrate communities at the commencement of our field experiment, using a Surber Sampler (500 µm mesh-size; surface 1/8 m²). At each sampling site we took five samples by physically agitating benthic habitats, such as mineral substrates, in-stream leaf litter, and submerged vegetation, upstream of the Surber net for 60 seconds. By this, we anticipated to capture the entire suite of macroinvertebrates present in the sampling sites, which should provide a comprehensive inventory of the local community potentially influencing the decomposition process over the entire study period. Samples were preserved in 70% ethanol in the field and afterwards sorted in the laboratory. All macroinvertebrates in a given sample were identified to the lowest practical taxonomic level – mostly to the species level (except taxa such as Chironomidae, Eloeophila, Oligochatea, Pisidium, Simuliidae and Tricladida, Supporting information) – and counted using light microscopy. Afterwards, mean species abundances per sampling site were calculated and extrapolated to abundance per square meter.

Macroinvertebrate trait information was retrieved from Tachet et al. (2010). In extracting traits, we focused on those that are closest in their definition to true functional effect traits, viz. most likely to be correlated with the effects of organisms on ecosystem processes (Hooper et al. 2002, Lavorel and Garnier 2002, Naeem and Wright 2003). Following the classifications of Frainer et al. (2014) and Truchy et al. (2019), we selected traits that 1) directly influence the assessed functional measures (e.g. feeding habits and maximum body size) and 2) reflect habitat use that regulate when and where different species are likely to be most active in their influences on functioning (Supporting information). Given the assessed measure of ecosystem function (i.e. leaf litter decomposition), we included only species that exhibited a value of > 0 for the trait expression ‘shredder’ in their feeding habit in further analyses.

In addition, we calculated the metabolic capacities of the macroinvertebrate communities following Brown et al. (2004) using the mean per capita body mass of sampled macroinvertebrate species, which was quantified by weighing up to 50 oven-dried (60°C for 24 h) specimen of each species to the nearest 0.01 mg. Finally, we used the SPEcies At Risk (SPEAR) calculator ‘Indicate’ (Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany) to calculate a standard risk indicator for pesticides (SPEAR<sub>pesticides</sub>) that is computed based on trait data on 1) physiological sensitivity to insecticides and other pesticides with insecticidal mode of action, 2) generation time, 3) presence of aquatic
<table><caption>Table 1. Descriptive statistics of environmental variables at the study sites (means, standard errors, minimum, and maximum; n=18). For more details see the Supporting information. <sup>a</sup>Measured using an ordinal scale (0–5). <sup>b</sup>Quantified for the entire stream catchment. <sup>c</sup>Mean from the left and right banks.</caption><thead><tr><th>Variable</th><th>Unit</th><th>Mean</th><th>SE</th><th>Min</th><th>Max</th></tr></thead><tbody><tr><td>Catchment size</td><td>ha</td><td>3171</td><td>608</td><td>914</td><td>11864</td></tr><tr><td>Width</td><td>m</td><td>2.3</td><td>0.2</td><td>1.4</td><td>4.8</td></tr><tr><td>Depth</td><td>m</td><td>0.19</td><td>0.02</td><td>0.07</td><td>0.34</td></tr><tr><td>Velocity</td><td>m s<sup>-1</sup></td><td>0.22</td><td>0.02</td><td>0.04</td><td>0.44</td></tr><tr><td>Temperature</td><td>°C</td><td>14.7</td><td>0.32</td><td>12.0</td><td>17.1</td></tr><tr><td>pH</td><td></td><td>7.73</td><td>0.05</td><td>7.36</td><td>8.01</td></tr><tr><td>Oxygen</td><td>mg l<sup>-1</sup></td><td>11.0</td><td>0.58</td><td>6.33</td><td>15.19</td></tr><tr><td>Conductivity</td><td>µS cm<sup>-1</sup></td><td>53.98</td><td>4.77</td><td>28</td><td>119</td></tr><tr><td>Alkalinity</td><td>meq l<sup>-1</sup></td><td>3.74</td><td>0.22</td><td>1.64</td><td>5.06</td></tr><tr><td>DIN</td><td>µg l<sup>-1</sup></td><td>2320.48</td><td>387.70</td><td>497</td><td>6020</td></tr><tr><td>PO<sub>4</sub><sup>3-</sup>-P</td><td>µg l<sup>-1</sup></td><td>101.44</td><td>32.97</td><td>7</td><td>578</td></tr><tr><td>Coarse substrates<br>(boulder and<br>cobble)</td><td>%</td><td>20.0</td><td>3.9</td><td>0.0</td><td>50.0</td></tr><tr><td>Medium<br>substrates<br>(pebble and<br>gravel)</td><td>%</td><td>31.1</td><td>4.6</td><td>5.0</td><td>70.0</td></tr><tr><td>Fine substrates<br>(sand and silt)</td><td>%</td><td>48.3</td><td>6.2</td><td>10.0</td><td>90.0</td></tr><tr><td>In-stream leaves<br>and wood (ø &lt;<br>10 cm)<sup>a</sup></td><td></td><td>0.9</td><td>0.08</td><td>0</td><td>1</td></tr><tr><td>In-stream wood<br>(ø &gt; 10 cm)<sup>a</sup></td><td></td><td>0.3</td><td>0.1</td><td>0</td><td>1</td></tr><tr><td>Immersed plants<sup>a</sup></td><td></td><td>1.2</td><td>0.3</td><td>0</td><td>4</td></tr><tr><td>Submerged<br>plants<sup>a</sup></td><td></td><td>1.0</td><td>0.1</td><td>0</td><td>1</td></tr><tr><td>Agricultural land<br>use<sup>b</sup></td><td>%</td><td>67.1</td><td>5.9</td><td>8.5</td><td>97.1</td></tr><tr><td>Forestry<sup>b</sup></td><td>%</td><td>19.7</td><td>5.2</td><td>0.0</td><td>73.6</td></tr><tr><td>Tree cover along<br>the bank<sup>c</sup></td><td></td><td>1.9</td><td>0.4</td><td>0</td><td>4</td></tr><tr><td>Shrub cover along<br>the bank<sup>c</sup></td><td></td><td>3.1</td><td>0.3</td><td>0</td><td>5</td></tr></tbody></table>

measured at the same stream location, where we set up a transect for water depth measurements (measured every 30 cm along the transect), which were averaged for every sampling site before entering the analyses. Stream temperatures were measured hourly using button data loggers (SmartButton; ACR Systems). Temperature data were converted to daily means for calculation of leaf litter breakdown rates per degree day (below), and were also averaged across the entire study period for use in statistical models. Water samples for analyses of alkalinity, total nitrogen, ammonium, nitrite and nitrate, total phosphorus, and phosphate were taken once at the commencement of the study and commercially analyzed using SWEDAC accredited methods.

Although we measured pesticides in the water phase at all sites during the study period (Supporting information), low rain fall in the study region during June 2016 (~ 18 l m⁻² over the entire month; long-term monthly average for June 1991–2020: ~ 61 l m⁻²; Sveriges meteorologiska och hydrol ogiska institut) led to low dissolved concentrations being

measured, given that the main entry route of pesticides into running waters is through rainfall-induced surface run-off (Schulz 2004). Therefore, the pesticide data had only a minor explanatory power for the outcome of the present study and were excluded from further analyses, but are provided in the Supporting information for the sake of transparency.

## Macroinvertebrate sampling, trait information, and variable selection

We quantitatively sampled macroinvertebrate communities at the commencement of our field experiment, using a Surber Sampler (500 µm mesh-size; surface 1/8 m²). At each sampling site we took five samples by physically agitating benthic habitats, such as mineral substrates, in-stream leaf litter, and submerged vegetation, upstream of the Surber net for 60 seconds. By this, we anticipated to capture the entire suite of macroinvertebrates present in the sampling sites, which should provide a comprehensive inventory of the local community potentially influencing the decomposition process over the entire study period. Samples were preserved in 70% ethanol in the field and afterwards sorted in the laboratory. All macroinvertebrates in a given sample were identified to the lowest practical taxonomic level – mostly to the species level (except taxa such as Chironomidae, Eloeophila, Oligochatea, Pisidium, Simuliidae and Tricladida, Supporting information) – and counted using light microscopy. Afterwards, mean species abundances per sampling site were calculated and extrapolated to abundance per square meter.

Macroinvertebrate trait information was retrieved from Tachet et al. (2010). In extracting traits, we focused on those that are closest in their definition to true functional effect traits, viz. most likely to be correlated with the effects of organisms on ecosystem processes (Hooper et al. 2002, Lavorel and Garnier 2002, Naeem and Wright 2003). Following the classifications of Frainer et al. (2014) and Truchy et al. (2019), we selected traits that 1) directly influence the assessed functional measures (e.g. feeding habits and maximum body size) and 2) reflect habitat use that regulate when and where different species are likely to be most active in their influences on functioning (Supporting information). Given the assessed measure of ecosystem function (i.e. leaf litter decomposition), we included only species that exhibited a value of > 0 for the trait expression ‘shredder’ in their feeding habit in further analyses.

In addition, we calculated the metabolic capacities of the macroinvertebrate communities following Brown et al. (2004) using the mean per capita body mass of sampled macroinvertebrate species, which was quantified by weighing up to 50 oven-dried (60°C for 24 h) specimen of each species to the nearest 0.01 mg. Finally, we used the SPEcies At Risk (SPEAR) calculator ‘Indicate’ (Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany) to calculate a standard risk indicator for pesticides (SPEAR<sub>pesticides</sub>) that is computed based on trait data on 1) physiological sensitivity to insecticides and other pesticides with insecticidal mode of action, 2) generation time, 3) presence of aquatic
stages, and 4) ability to migrate and recolonize. These traits are typically associated with greater tolerance to environmental disturbances to characterize variation (Liess and von der Ohe 2005). Accordingly, the SPEAR<sub>pesticides</sub> index captures information not only about potential legacy pesticide effects but also other effects caused by reduced water quality on the proportion of sensitive relative to tolerant taxa in macroinvertebrate communities (Schuwirth et al. 2015).

Using these data, we calculated community weighted means (CWM) for each trait following Lavorel et al. (2008) as well as a series of invertebrate metrics (density, species richness, Shannon index, functional dispersion, functional richness, functional evenness). We assessed collinearity among the variables (metabolic capacity, SPEAR<sub>pesticides</sub>, CWMs, invertebrate metrics) using the Pearson correlation coefficient (PCC). When two or more strongly correlating variables were indicated (PCC > 0.8), we only kept the variable that was least correlated with the remaining variables. This procedure led to the inclusion of metabolic capacity, SPEAR<sub>pesticides</sub>, CWMs for organic detritus as preferred habitat and shredding as feeding habit, density, Shannon index, and functional dispersion in the final analyses.

## Leaf litter decomposition

We quantified the decomposition of terrestrially-derived leaf litter as a measure of stream ecosystem functioning. Leaves of two common European broad-leaved tree species, black alder *Alnus glutinosa* and pedunculate oak *Quercus robur*, as well as one invasive tree species, black locust *Robinia pseudoacacia*, were picked from trees shortly before abscission during autumn 2015 (Supporting information). The leaf material was afterwards stored at -20°C until further processing. Freezing may have slightly affected the litter decomposition process, but such effects are generally minor (Bärlocher 1992) as shown by the alder decomposition rates measured here that match with the range of the decomposition rates reported for the temperature zone ($k_{dd; detritivore}$ = 0.015–0.060; $k_{dd; microbial}$ = 0.004–0.020) in a global decomposition study (Boyero et al. 2016). Our selection of these leaf species, which contrasted key decomposition-related traits (C-, N-, P-content, N:P-, C:N-, C:P-ratio, lignin and cellulose content, and toughness, Supporting information) was motivated by 1) potential leaf litter diversity effects on functioning (facilitation or constraint) because of known differences in decomposition rates of the two N-fixing species alder (fast decomposition) and black locust (intermediate decomposition) as well as the N-poor species oak (slow decomposition; Abelho 2001) and 2) the attempt to capture the importance of macroinvertebrate traits over a wider range of substrate variability.

Leaf litter decomposition rates were quantified using coarse mesh ($\theta$=10.0 mm, allowing access for both detritivores and microbial decomposers) and fine mesh ($\theta$=0.5 mm, preventing detritivore access) leaf litterbags packed with oven-dried (48 h at 60°C) leaf material. Single-species leaf litterbags contained 2.00 (± 0.01 SE; n=432) g leaf material of the respective leaf species, whereas mixed-species leaf

litterbags contained 0.66 (± 0.01 SE; n=144) g leaf material of each of the three tested leaf species leading to a total mass of 2.00 g. We immersed four leaf litterbags of each mesh type (coarse and fine), litter species (black alder, pedunculate oak, and black locust) and species combination (single- and mixed-species) at each sampling site, resulting in a total of 32 litterbags deployed in each of the assessed streams. The study sites were visited every seven days to inspect the stage of leaf litter decomposition and we retrieved the leaf litterbags from the field latest 21 days after deployment. We rinsed the remaining leaf material under running water to remove sediment particles and macroinvertebrates and sorted leaf material retrieved from mixed-species litterbags according to leaf litter species before further processing. The remaining leaf material was oven-dried at 60°C for 48 h, weighed to the nearest 0.01 mg, and ashed at 550°C for 4 h to quantify the ash free dry mass. Leaf litter decomposition was corrected using leaching factors that were determined in a 48 h lab experiment and represent the proportion mass remaining after leaching (black alder: 0.76; pedunculate oak: 0.81; black locust: 0.81). The detritivore-mediated share of leaf litter decomposition was calculated as the difference between the overall decomposition in coarse mesh bags and the microbially-mediated decomposition in fine mesh bags. Finally, the temperature-standardized leaf litter decomposition coefficients ($k_{dd; microbial}$ and $k_{dd; detritivore}$) were calculated for each leaf litterbag or species therein (in case of mixed-species leaf litterbags) using a negative exponential decay model (Benfield 2007).

## Statistical analyses

### Generalized linear models

In order to assess the individual and joint effects of ‘leaf species identity’ and ‘leaf litter mixing’ on the leaf litter decomposition rates ($k_{dd; microbial}$ and $k_{dd; detritivore}$), we fitted two-factorial generalized linear models (GLM) with an assumed Gaussian distribution of the response variable and a log link function. The GLMs’ goodness-of-fit was inspected using the R package ‘DHARMa’ (Hartig 2022).

### Diversity effects on leaf litter decomposition rates

To quantify the magnitude of the net biodiversity effect, the dominance effect and complementarity on leaf litter decomposition rates, we used the additive partition approach by Loreau and Hector (2001). This approach compares the observed functioning in mixed-species leaf litterbags with expected functioning based on leaf litter decomposition rates in single-species leaf litterbags (for a detailed description of the underlying calculations see Loreau and Hector (2001)). To facilitate the comparison with previous studies, we restore the nomenclature of Loreau and Hector (2001) and call the dominance effect the ‘selection effect’ in the following, because it quantifies the net biodiversity effect fraction attributable to processes analogous to natural selection (Fox 2005).

Afterwards, we used the R package ‘drm’ (www.r-project.org, Ritz et al. 2015) to fit several dose-response models (including lognormal, log-logistic, Weibull, Cedergreen-Ritz-Streibig
stages, and 4) ability to migrate and recolonize. These traits
are typically associated with greater tolerance to environmen-
tal disturbances to characterize variation (Liess and von der
Ohe 2005). Accordingly, the SPEAR<sub>pesticides</sub> index captures
information not only about potential legacy pesticide effects
but also other effects caused by reduced water quality on the
proportion of sensitive relative to tolerant taxa in macroin-
vertebrate communities (Schuwirth et al. 2015).

Using these data, we calculated community weighted
means (CWM) for each trait following Lavorel et al. (2008)
as well as a series of invertebrate metrics (density, species rich-
ness, Shannon index, functional dispersion, functional rich-
ness, functional evenness). We assessed collinearity among
the variables (metabolic capacity, SPEAR<sub>pesticides</sub>, CWMs,
invertebrate metrics) using the Pearson correlation coefficient
(PCC). When two or more strongly correlating variables were
indicated (PCC > 0.8), we only kept the variable that was
least correlated with the remaining variables. This procedure
led to the inclusion of metabolic capacity, SPEAR<sub>pesticides</sub>,
CWMs for organic detritus as preferred habitat and shred-
ding as feeding habit, density, Shannon index, and functional
dispersion in the final analyses.

Leaf litter decomposition

We quantified the decomposition of terrestrially-derived leaf
litter as a measure of stream ecosystem functioning. Leaves of
two common European broad-leaved tree species, black alder
*Alnus glutinosa* and pedunculate oak *Quercus robur*, as well as
one invasive tree species, black locust *Robinia pseudoacacia*,
were picked from trees shortly before abscission during autumn
2015 (Supporting information). The leaf material was after-
wards stored at -20°C until further processing. Freezing may
have slightly affected the litter decomposition process, but
such effects are generally minor (Bärlocher 1992) as shown by
the alder decomposition rates measured here that match with
the range of the decomposition rates reported for the temper-
ate zone ($k_{dd; detritivore}$ = 0.015–0.060; $k_{dd; microbial}$ = 0.004–0.020)
in a global decomposition study (Boyero et al. 2016). Our
selection of these leaf species, which contrasted key decom-
position-related traits (C-, N-, P-content, N:P-, C:N-, C:P-
ratio, lignin and cellulose content, and toughness, Supporting
information) was motivated by 1) potential leaf litter diversity
effects on functioning (facilitation or constraint) because of
known differences in decomposition rates of the two N-fixing
species alder (fast decomposition) and black locust (interme-
diate decomposition) as well as the N-poor species oak (slow
decomposition; Abelho 2001) and 2) the attempt to capture
the importance of macroinvertebrate traits over a wider range
of substrate variability.

Leaf litter decomposition rates were quantified using
coarse mesh (ø=10.0 mm, allowing access for both detri-
tivores and microbial decomposers) and fine mesh (ø=0.5
mm, preventing detritivore access) leaf litterbags packed with
oven-dried (48 h at 60°C) leaf material. Single-species leaf
litterbags contained 2.00 (± 0.01 SE; n=432) g leaf mate-
rial of the respective leaf species, whereas mixed-species leaf

litterbags contained 0.66 (± 0.01 SE; n=144) g leaf mate-
rial of each of the three tested leaf species leading to a total
mass of 2.00 g. We immersed four leaf litterbags of each mesh
type (coarse and fine), litter species (black alder, pedunculate
oak, and black locust) and species combination (single- and
mixed-species) at each sampling site, resulting in a total of
32 litterbags deployed in each of the assessed streams. The
study sites were visited every seven days to inspect the stage of
leaf litter decomposition and we retrieved the leaf litterbags
from the field latest 21 days after deployment. We rinsed the
remaining leaf material under running water to remove sedi-
ment particles and macroinvertebrates and sorted leaf material
retrieved from mixed-species litterbags according to leaf litter
species before further processing. The remaining leaf material
was oven-dried at 60°C for 48 h, weighed to the nearest 0.01
mg, and ashed at 550°C for 4 h to quantify the ash free dry
mass. Leaf litter decomposition was corrected using leach-
ing factors that were determined in a 48 h lab experiment
and represent the proportion mass remaining after leaching
(black alder: 0.76; pedunculate oak: 0.81; black locust: 0.81).
The detritivore-mediated share of leaf litter decomposition
was calculated as the difference between the overall decom-
position in coarse mesh bags and the microbially-mediated
decomposition in fine mesh bags. Finally, the temperature-
standardized leaf litter decomposition coefficients ($k_{dd; microbial}$
and $k_{dd; detritivore}$) were calculated for each leaf litterbag or spe-
cies therein (in case of mixed-species leaf litterbags) using a
negative exponential decay model (Benfield 2007).

Statistical analyses

Generalized linear models

In order to assess the individual and joint effects of ‘leaf
species identity’ and ‘leaf litter mixing’ on the leaf litter
decomposition rates ($k_{dd; microbial}$ and $k_{dd; detritivore}$), we fitted two-
factorial generalized linear models (GLM) with an assumed
Gaussian distribution of the response variable and a log link
function. The GLMs’ goodness-of-fit was inspected using the
R package ‘DHARMa’ (Hartig 2022).

Diversity effects on leaf litter decomposition rates

To quantify the magnitude of the net biodiversity effect, the
dominance effect and complementarity on leaf litter decom-
position rates, we used the additive partition approach by
Loreau and Hector (2001). This approach compares the
observed functioning in mixed-species leaf litterbags with
expected functioning based on leaf litter decomposition rates
in single-species leaf litterbags (for a detailed description of
the underlying calculations see Loreau and Hector (2001)).
To facilitate the comparison with previous studies, we restore
the nomenclature of Loreau and Hector (2001) and call
the dominance effect the ‘selection effect’ in the following,
because it quantifies the net biodiversity effect fraction attrib-
utable to processes analogous to natural selection (Fox 2005).

Afterwards, we used the R package ‘drm’ (www.r-project.org, Ritz et al. 2015) to fit several dose-response models (including lognormal, log-logistic, Weibull, Cedergreen-Ritz-Streibig
and Michaelis-Menten models) to the data to assess the effects
of the increasing agricultural intensity in the streams' catch-
ments on the net biodiversity effect, complementarity, and the
selection effect. The models fitting the data best were selected
based on visual judgement and Akaike's information criterion
(all models and their respective parameters are reported in the
Supporting information).

Structural equation modeling

We used structural equation modeling (SEM), representing
an analytical procedure for partitioning complex relationships
in multivariate data sets (Shipley 2016), to disentangle link-
ages between habitat characteristics (depth, width, flow, per-
centage cover of fine substrate, medium substrate, and coarse
substrate, submersed plants, percentage cover of leaves and
woods [ø < 10 cm], and woods [ø > 10 cm]) as well as water
quality parameters (alkalinity, pH, dissolved inorganic nitro-
gen [NO₂⁻ + NO₃⁻ + NH₄⁺], phosphate, and oxygen, Table 1)
and invertebrate metrics as drivers for leaf litter decomposi-
tion using the R package 'piecewiseSEM' (Lefcheck 2016).

Before building the models, we reduced the dimension-
ality of water quality parameters and habitat characteristics
by applying two principal component analyses (PCAs) on
standardized variables using the R package 'FactoMineR'
(Lê et al. 2008). Before conducting the PCAs, we assessed
collinearity among the variables using the Pearson correlation
coefficient (PCC). When two or more strongly correlating
variables were indicated (PCC > 0.8), we only kept the vari-
able that was least correlated with the remaining variables.
Based on the eigenvalues, the first two principal components
(PCs) were extracted to describe the water quality parameters
and the habitat characteristics in the SEMs.

We proposed a conceptual model of hypothesized rela-
tionships between predictor variables (agricultural intensity
represented as %agricultural land use in the catchment,

habitat characteristics, water quality parameters, inverte-
brate metrics, and leaf species identity) and the response
variable (k<sub>dd; detritivore</sub>) within a path diagram (Fig. 2). Our
proposed model structure was based on knowledge of the
leaf litter decomposition process, allowing a causal inter-
pretation of the model outputs (Shipley 2016). However,
the proposed model is only valid for the type of relations
introduced and does not exclude potential other types of
relations omitted here.

The overall influences of ‘%agricultural land use’ (repre-
senting agricultural intensity) and ‘leaf species identity’ on
leaf litter decomposition rates were modeled as exogenous
effects, while for the former both direct (variation attribut-
able to non-measured environmental variables) and indirect
(variation attributable to changes in habitat characteristics
and water quality parameters) relationships were consid-
ered (Fig. 2). To free up degrees of freedom and improve the
model fit, any path with a coefficient < 0.1 was removed
from the model when statistically non-significant. The mod-
els’ goodness-of-fit was assessed with Fisher’s test of direct
separation and Bayesian information criterion scores. All sta-
tistical analyses were performed using the open-source statis-
tical software R (www.r-project.org).

Results

Effects of leaf species identity and diversity on leaf litter
decomposition in streams under increasing agricultural
intensity

Leaf species identity significantly influenced detritivore-
mediated leaf litter decomposition (p < 0.001 for the factor
‘leaf species identity’ in GLM) and this effect was observed
independent of single-species or mixed-species leaf litterbags

<figure><img src="image_5.png" /><figcaption>Figure 2. Conceptual structural equation model depicting pathways by which the percentage share of agricultural land use in the streams' catchments, leaf species identity, habitat characteristics, water quality parameters, and invertebrate metrics influence leaf litter decomposition rates based on previous studies. '%agricultural land use' was modelled to have both direct and indirect effects (mediated by habitat characteristics, water quality parameters, and invertebrate metrics) on leaf litter decomposition rates. Habitat characteristics and water quality parameters are represented by the first two principal components from the respective principal component analyses.</figcaption></figure>
and Michaelis-Menten models) to the data to assess the effects
of the increasing agricultural intensity in the streams' catch-
ments on the net biodiversity effect, complementarity, and the
selection effect. The models fitting the data best were selected
based on visual judgement and Akaike's information criterion
(all models and their respective parameters are reported in the
Supporting information).

Structural equation modeling

We used structural equation modeling (SEM), representing
an analytical procedure for partitioning complex relationships
in multivariate data sets (Shipley 2016), to disentangle link-
ages between habitat characteristics (depth, width, flow, per-
centage cover of fine substrate, medium substrate, and coarse
substrate, submersed plants, percentage cover of leaves and
woods [ø < 10 cm], and woods [ø > 10 cm]) as well as water
quality parameters (alkalinity, pH, dissolved inorganic nitro-
gen [NO₂⁻ + NO₃⁻ + NH₄⁺], phosphate, and oxygen, Table 1)
and invertebrate metrics as drivers for leaf litter decomposi-
tion using the R package 'piecewiseSEM' (Lefcheck 2016).

Before building the models, we reduced the dimension-
ality of water quality parameters and habitat characteristics
by applying two principal component analyses (PCAs) on
standardized variables using the R package 'FactoMineR'
(Lê et al. 2008). Before conducting the PCAs, we assessed
collinearity among the variables using the Pearson correlation
coefficient (PCC). When two or more strongly correlating
variables were indicated (PCC > 0.8), we only kept the vari-
able that was least correlated with the remaining variables.
Based on the eigenvalues, the first two principal components
(PCs) were extracted to describe the water quality parameters
and the habitat characteristics in the SEMs.

We proposed a conceptual model of hypothesized rela-
tionships between predictor variables (agricultural intensity
represented as %agricultural land use in the catchment,

habitat characteristics, water quality parameters, inverte-
brate metrics, and leaf species identity) and the response
variable (k<sub>dd; detritivore</sub>) within a path diagram (Fig. 2). Our
proposed model structure was based on knowledge of the
leaf litter decomposition process, allowing a causal inter-
pretation of the model outputs (Shipley 2016). However,
the proposed model is only valid for the type of relations
introduced and does not exclude potential other types of
relations omitted here.

The overall influences of ‘%agricultural land use’ (repre-
senting agricultural intensity) and ‘leaf species identity’ on
leaf litter decomposition rates were modeled as exogenous
effects, while for the former both direct (variation attribut-
able to non-measured environmental variables) and indirect
(variation attributable to changes in habitat characteristics
and water quality parameters) relationships were consid-
ered (Fig. 2). To free up degrees of freedom and improve the
model fit, any path with a coefficient < 0.1 was removed
from the model when statistically non-significant. The mod-
els’ goodness-of-fit was assessed with Fisher’s test of direct
separation and Bayesian information criterion scores. All sta-
tistical analyses were performed using the open-source statis-
tical software R (www.r-project.org).

Results

Effects of leaf species identity and diversity on leaf litter
decomposition in streams under increasing agricultural
intensity

Leaf species identity significantly influenced detritivore-
mediated leaf litter decomposition (p < 0.001 for the factor
‘leaf species identity’ in GLM) and this effect was observed
independent of single-species or mixed-species leaf litterbags

<figure><img src="image_6.png" /><figcaption>Figure 2. Conceptual structural equation model depicting pathways by which the percentage share of agricultural land use in the streams' catchments, leaf species identity, habitat characteristics, water quality parameters, and invertebrate metrics influence leaf litter decomposition rates based on previous studies. '%agricultural land use' was modelled to have both direct and indirect effects (mediated by habitat characteristics, water quality parameters, and invertebrate metrics) on leaf litter decomposition rates. Habitat characteristics and water quality parameters are represented by the first two principal components from the respective principal component analyses.</figcaption></figure>
(p=0.388 for the interaction 'leaf species identity × mixture'). Detritivores decomposed alder ($k_{dd; detritivore}$=0.025 ± 0.005; mean ± SE) approx. 8-fold and 3.5-fold faster than oak ($k_{dd; detritivore}$=0.003 ± 0.001) and black locust ($k_{dd; detritivore}$=0.007 ± 0.002), respectively, in single-species litterbags (Fig. 3). In mixed-species leaf litterbags, the same pattern was observed, however, detritivores decomposed alder ($k_{dd; detritivore}$=0.020 ± 0.04) only 4-fold and 2-fold faster than oak ($k_{dd; detritivore}$=0.005 ± 0.001) and black locust ($k_{dd; detritivore}$=0.011 ± 0.001), respectively (Fig. 3). The pattern of substantially faster alder decomposition by detritivores – compared to oak and black locust – was especially observed under low to intermediate agricultural intensity in the upstream catchment (≤30%), while the differences in decomposition among species became smaller with an increase in its intensity (Fig. 3). The observation of an ~ 2-fold faster detritivore-mediated decomposition of oak and black locust in mixed-species leaf litterbags, especially at low to intermediate agricultural intensity (≤

30%), is coherent with our results on biodiversity effects, which showed a positive net biodiversity effect – driven by complementarity. The influence of the selection effect, on the other hand, was negligible (Fig. 4). Furthermore, both the net biodiversity effect and complementarity showed a monotonic, inverse S-shaped decrease along the gradient of agricultural intensity (Fig. 4).

For microbially-mediated leaf litter decomposition, leaf species identity and litter mixing showed significant influences (p ≤ 0.003) on the decomposition rates, while both factors interacted (p=0.048). Microorganisms decomposed alder ($k_{dd; microbial}$=0.0022 ± 0.0001) approx. 1.5-fold and 1.3-fold faster than oak ($k_{dd; microbial}$=0.0015 ± 0.0005) and black locust ($k_{dd; microbial}$=0.0017 ± 0.0001), respectively, in single-species litter bags (Fig. 3). In mixed-species leaf litterbags, the same pattern was observed, however, microorganisms decomposed alder ($k_{dd; microbial}$=0.0030 ± 0.0003) 3-fold and 2-fold faster than oak ($k_{dd; microbial}$=0.0010 ± 0.0001) and black locust ($k_{dd; microbial}$=0.0016 ± 0.0001), respectively (Fig. 3).

<figure><img src="image_6.png" /><figcaption>Figure 3. Detritivore-mediated (upper row) and microbially-mediated (lower row) leaf litter decomposition rates ($k_{dd}$) for alder (red), oak (yellow), and black locust (blue) along the gradient of agricultural land use in the streams' catchments for single-species (left column) and mixed-species (right column) leaf litterbags. Black lines depict generalized linear models applied to the leaf litter decomposition rates of individual leaf species together with the associated 95% confidence bands in the respective color.</figcaption></figure>
(p=0.388 for the interaction 'leaf species identity × mixture'). Detritivores decomposed alder ($k_{dd; detritivore}$=0.025 ± 0.005; mean ± SE) approx. 8-fold and 3.5-fold faster than oak ($k_{dd; detritivore}$=0.003 ± 0.001) and black locust ($k_{dd; detritivore}$=0.007 ± 0.002), respectively, in single-species litterbags (Fig. 3). In mixed-species leaf litterbags, the same pattern was observed, however, detritivores decomposed alder ($k_{dd; detritivore}$=0.020 ± 0.04) only 4-fold and 2-fold faster than oak ($k_{dd; detritivore}$=0.005 ± 0.001) and black locust ($k_{dd; detritivore}$=0.011 ± 0.001), respectively (Fig. 3). The pattern of substantially faster alder decomposition by detritivores – compared to oak and black locust – was especially observed under low to intermediate agricultural intensity in the upstream catchment (≤30%), while the differences in decomposition among species became smaller with an increase in its intensity (Fig. 3). The observation of an ~ 2-fold faster detritivore-mediated decomposition of oak and black locust in mixed-species leaf litterbags, especially at low to intermediate agricultural intensity (≤

30%), is coherent with our results on biodiversity effects, which showed a positive net biodiversity effect – driven by complementarity. The influence of the selection effect, on the other hand, was negligible (Fig. 4). Furthermore, both the net biodiversity effect and complementarity showed a monotonic, inverse S-shaped decrease along the gradient of agricultural intensity (Fig. 4).

For microbially-mediated leaf litter decomposition, leaf species identity and litter mixing showed significant influences (p ≤ 0.003) on the decomposition rates, while both factors interacted (p=0.048). Microorganisms decomposed alder ($k_{dd; microbial}$=0.0022 ± 0.0001) approx. 1.5-fold and 1.3-fold faster than oak ($k_{dd; microbial}$=0.0015 ± 0.0005) and black locust ($k_{dd; microbial}$=0.0017 ± 0.0001), respectively, in single-species litter bags (Fig. 3). In mixed-species leaf litterbags, the same pattern was observed, however, microorganisms decomposed alder ($k_{dd; microbial}$=0.0030 ± 0.0003) 3-fold and 2-fold faster than oak ($k_{dd; microbial}$=0.0010 ± 0.0001) and black locust ($k_{dd; microbial}$=0.0016 ± 0.0001), respectively (Fig. 3).

<figure><img src="image_7.png" /><figcaption>Figure 3. Detritivore-mediated (upper row) and microbially-mediated (lower row) leaf litter decomposition rates ($k_{dd}$) for alder (red), oak (yellow), and black locust (blue) along the gradient of agricultural land use in the streams' catchments for single-species (left column) and mixed-species (right column) leaf litterbags. Black lines depict generalized linear models applied to the leaf litter decomposition rates of individual leaf species together with the associated 95% confidence bands in the respective color.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Figure 4. Dose-response models (solid lines; shaded areas depict the 95% confidence interval bands) and individual measurements (filled circles) for complementarity, the selection effect, and the net diversity effect along the gradient of agricultural land use in the streams' catchments, based on detritivore-mediated leaf litter decomposition rates.</figcaption></figure>

## Habitat characteristics and water quality parameters

The PCA on the habitat characteristics revealed that the first two PCs captured 49% of the total variation (PC1: 30%; PC2: 19%). PC1 was mainly (individual |loadings| ≥ 0.40) associated with increasing depth, fine sediment, and submersed plants, as well as decreasing flow, share of in-stream leaves and woods (ø < 10 cm), and in-stream woody debris (ø > 10 cm). Depth, flow and velocity increased along PC2 (Table 2). The PCA on the water quality parameters revealed that the first two PCs explained 69% of the total variation (PC1: 39%; PC2: 30%). PC1 was associated with higher alkalinity, DIN, and phosphate. Oxygen and pH increased along PC2 (Table 2).

## Direct and indirect effects of increasing agricultural intensity on leaf litter decomposition in streams

For single-species leaf litterbags, there were significant direct (path coefficient = −0.29) and indirect effects of agricultural intensity on leaf litter decomposition rates in the SEM (Fig. 5a). We found that negative indirect effects of agricultural intensity appeared to be mediated through effects on the proportion of sensitive invertebrate species (SPEAR<sub>pesticides</sub>, Supporting information) and habitat characteristics: agricultural intensity had a negative effect on SPEAR<sub>pesticides</sub> (R<sup>2</sup>=0.32; path coefficient = −0.57), while SPEAR<sub>pesticides</sub> itself positively affected leaf litter decomposition rates (path coefficient = 0.23, Fig. 5a). On the other hand, agricultural intensity positively affected PC1 of the habitat characteristics (R<sup>2</sup>=0.35; path coefficient = 0.42), meaning that depth, the share of fine substrate, and the growth of submerged plants increased, while the water flow, and the share of in-stream leaves and woods (ø < 10 cm) as well as in-stream woody debris (ø > 10 cm) decreased along the agricultural intensity gradient. PC1 of the habitat characteristics finally negatively affected leaf litter decomposition rates (path coefficient = −0.19, Fig. 5a). The significant influence of leaf species identity on leaf litter decomposition rates became also apparent in the SEM. There was no evidence for a significant

influence of any other predictor, including further invertebrate metrics or the water quality parameters (Fig. 5a).

For the mixed-species leaf litterbags, SEM showed evidence of significant direct (path coefficient = −0.49) and indirect effects of agricultural intensity on leaf litter decomposition rates (Fig. 5b). Negative indirect effects of agricultural intensity in the SEM were mediated through effects on the proportion of sensitive invertebrate species (SPEAR<sub>pesticides</sub>, Supporting information) and water quality parameters: agricultural intensity had a negative effect on SPEAR<sub>pesticides</sub> (R<sup>2</sup>=0.32; path coefficient = −0.66), while SPEAR<sub>pesticides</sub> positively affected leaf litter decomposition rates (path coefficient = 0.26, Fig. 5b). On the other hand, agricultural intensity positively affected PC1 of the water quality parameters (R<sup>2</sup>=0.34; path coefficient = 0.35), meaning that alkalinity, DIN and PO<sub>4</sub><sup>3-</sup>P increased, while the pH and oxygen decreased along the agricultural intensity gradient. PC1 of the water quality parameters negatively affected

<table><caption>Table 2. Results extracted from the principal component analyses on habitat characteristics and water quality parameters; only two principle components (PC1 and PC2) were extracted for each principle component analysis based on eigenvalues. Percent of variation explained by the variables and |loadings| ≥ 0.40 (in bold) are shown.</caption><thead><tr><th></th><th>% variance PC1</th><th>% variance PC2</th><th>Loadings PC1</th><th>Loadings PC2</th></tr></thead><tbody><tr><td>Habitat characteristics</td><td></td><td></td><td></td><td></td></tr><tr><td>Depth</td><td><strong>14.4</strong></td><td><strong>30.5</strong></td><td><strong>0.55</strong></td><td><strong>0.63</strong></td></tr><tr><td>Width</td><td>1.6</td><td><strong>28.1</strong></td><td>0.18</td><td><strong>0.61</strong></td></tr><tr><td>Flow</td><td><strong>21.0</strong></td><td><strong>18.56</strong></td><td><strong>-0.67</strong></td><td><strong>0.49</strong></td></tr><tr><td>Fine sediment</td><td><strong>15.7</strong></td><td>6.9</td><td><strong>0.58</strong></td><td>-0.30</td></tr><tr><td>Submersed plants</td><td><strong>20.9</strong></td><td>3.6</td><td><strong>0.66</strong></td><td>0.22</td></tr><tr><td>Leaves and woods</td><td><strong>10.9</strong></td><td>3.2</td><td><strong>-0.48</strong></td><td>-0.20</td></tr><tr><td>Woods</td><td><strong>15.6</strong></td><td>9.3</td><td><strong>-0.57</strong></td><td>0.35</td></tr><tr><td>Water quality parameters</td><td></td><td></td><td></td><td></td></tr><tr><td>Alkalinity</td><td><strong>28.3</strong></td><td>4.6</td><td><strong>0.74</strong></td><td>0.26</td></tr><tr><td>pH</td><td>7.0</td><td><strong>43.2</strong></td><td>0.37</td><td><strong>0.81</strong></td></tr><tr><td>DIN</td><td><strong>35.7</strong></td><td>3.9</td><td><strong>0.83</strong></td><td>-0.24</td></tr><tr><td>PO<sub>4</sub><sup>3-</sup>-P</td><td><strong>28.7</strong></td><td><strong>14.3</strong></td><td><strong>0.75</strong></td><td><strong>-0.46</strong></td></tr><tr><td>Oxygen</td><td>0.3</td><td><strong>33.9</strong></td><td>0.08</td><td><strong>0.71</strong></td></tr></tbody></table>
<figure><img src="image_8.png" /><figcaption>Figure 4. Dose-response models (solid lines; shaded areas depict the 95% confidence interval bands) and individual measurements (filled circles) for complementarity, the selection effect, and the net diversity effect along the gradient of agricultural land use in the streams' catchments, based on detritivore-mediated leaf litter decomposition rates.</figcaption></figure>

## Habitat characteristics and water quality parameters

The PCA on the habitat characteristics revealed that the first two PCs captured 49% of the total variation (PC1: 30%; PC2: 19%). PC1 was mainly (individual |loadings| ≥ 0.40) associated with increasing depth, fine sediment, and submersed plants, as well as decreasing flow, share of in-stream leaves and woods (ø < 10 cm), and in-stream woody debris (ø > 10 cm). Depth, flow and velocity increased along PC2 (Table 2). The PCA on the water quality parameters revealed that the first two PCs explained 69% of the total variation (PC1: 39%; PC2: 30%). PC1 was associated with higher alkalinity, DIN, and phosphate. Oxygen and pH increased along PC2 (Table 2).

## Direct and indirect effects of increasing agricultural intensity on leaf litter decomposition in streams

For single-species leaf litterbags, there were significant direct (path coefficient = −0.29) and indirect effects of agricultural intensity on leaf litter decomposition rates in the SEM (Fig. 5a). We found that negative indirect effects of agricultural intensity appeared to be mediated through effects on the proportion of sensitive invertebrate species (SPEAR<sub>pesticides</sub>, Supporting information) and habitat characteristics: agricultural intensity had a negative effect on SPEAR<sub>pesticides</sub> (R<sup>2</sup>=0.32; path coefficient = −0.57), while SPEAR<sub>pesticides</sub> itself positively affected leaf litter decomposition rates (path coefficient = 0.23, Fig. 5a). On the other hand, agricultural intensity positively affected PC1 of the habitat characteristics (R<sup>2</sup>=0.35; path coefficient = 0.42), meaning that depth, the share of fine substrate, and the growth of submerged plants increased, while the water flow, and the share of in-stream leaves and woods (ø < 10 cm) as well as in-stream woody debris (ø > 10 cm) decreased along the agricultural intensity gradient. PC1 of the habitat characteristics finally negatively affected leaf litter decomposition rates (path coefficient = −0.19, Fig. 5a). The significant influence of leaf species identity on leaf litter decomposition rates became also apparent in the SEM. There was no evidence for a significant

influence of any other predictor, including further invertebrate metrics or the water quality parameters (Fig. 5a).

For the mixed-species leaf litterbags, SEM showed evidence of significant direct (path coefficient = −0.49) and indirect effects of agricultural intensity on leaf litter decomposition rates (Fig. 5b). Negative indirect effects of agricultural intensity in the SEM were mediated through effects on the proportion of sensitive invertebrate species (SPEAR<sub>pesticides</sub>, Supporting information) and water quality parameters: agricultural intensity had a negative effect on SPEAR<sub>pesticides</sub> (R<sup>2</sup>=0.32; path coefficient = −0.66), while SPEAR<sub>pesticides</sub> positively affected leaf litter decomposition rates (path coefficient = 0.26, Fig. 5b). On the other hand, agricultural intensity positively affected PC1 of the water quality parameters (R<sup>2</sup>=0.34; path coefficient = 0.35), meaning that alkalinity, DIN and PO<sub>4</sub><sup>3-</sup>P increased, while the pH and oxygen decreased along the agricultural intensity gradient. PC1 of the water quality parameters negatively affected

<table><caption>Table 2. Results extracted from the principal component analyses on habitat characteristics and water quality parameters; only two principle components (PC1 and PC2) were extracted for each principle component analysis based on eigenvalues. Percent of variation explained by the variables and |loadings| ≥ 0.40 (in bold) are shown.</caption><thead><tr><th></th><th>% variance<br>PC1</th><th>% variance<br>PC2</th><th>Loadings<br>PC1</th><th>Loadings<br>PC2</th></tr></thead><tbody><tr><td><strong>Habitat characteristics</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Depth</td><td><strong>14.4</strong></td><td><strong>30.5</strong></td><td><strong>0.55</strong></td><td><strong>0.63</strong></td></tr><tr><td>Width</td><td>1.6</td><td><strong>28.1</strong></td><td>0.18</td><td><strong>0.61</strong></td></tr><tr><td>Flow</td><td><strong>21.0</strong></td><td><strong>18.56</strong></td><td><strong>-0.67</strong></td><td><strong>0.49</strong></td></tr><tr><td>Fine sediment</td><td><strong>15.7</strong></td><td>6.9</td><td><strong>0.58</strong></td><td>-0.30</td></tr><tr><td>Submersed<br>plants</td><td><strong>20.9</strong></td><td>3.6</td><td><strong>0.66</strong></td><td>0.22</td></tr><tr><td>Leaves and<br>woods</td><td><strong>10.9</strong></td><td>3.2</td><td><strong>-0.48</strong></td><td>-0.20</td></tr><tr><td>Woods</td><td><strong>15.6</strong></td><td>9.3</td><td><strong>-0.57</strong></td><td>0.35</td></tr><tr><td><strong>Water quality parameters</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Alkalinity</td><td><strong>28.3</strong></td><td>4.6</td><td><strong>0.74</strong></td><td>0.26</td></tr><tr><td>pH</td><td>7.0</td><td><strong>43.2</strong></td><td>0.37</td><td><strong>0.81</strong></td></tr><tr><td>DIN</td><td><strong>35.7</strong></td><td>3.9</td><td><strong>0.83</strong></td><td>-0.24</td></tr><tr><td>PO<sub>4</sub><sup>3-</sup>-P</td><td><strong>28.7</strong></td><td><strong>14.3</strong></td><td><strong>0.75</strong></td><td><strong>-0.46</strong></td></tr><tr><td>Oxygen</td><td>0.3</td><td><strong>33.9</strong></td><td>0.08</td><td><strong>0.71</strong></td></tr></tbody></table>
<figure><img src="image_8.png" /><figcaption>Figure 5. Piecewise structural equation models showing the pathways by which the percentage share of agricultural land use in the streams' catchments, leaf species identity, the SPEAR<sub>pesticides</sub> index, water quality parameters and habitat characteristics influence detritivore-mediated leaf litter decomposition rates in (a) single-species and (b) mixed-species leaf litterbags. Solid black and solid red arrows indicate significant positive and negative influences, respectively. Standardized path coefficients are shown. Note that leaf species identity entered the analyses as a factorial parameter, for which no path coefficients are produced (grey arrow). Marginal R<sup>2</sup> values indicate explained variance. Single-species litterbags: Fisher's C=0.367, p=0.999, 6 df, BIC=52.224; mixed-species litterbags: Fisher's C=3.505, p=0.743, 6 df, BIC=55.362.
* p < 0.05;
* p < 0.01;
* * p < 0.001.</figcaption></figure>

the SPEAR<sub>pesticides</sub> index (path coefficient = -0.27, Fig. 5b). The significant influence of leaf species identity on leaf litter decomposition rates became also apparent in the SEM. There was no evidence for a significant influence of any other predictor, including further invertebrate metrics or habitat quality parameters (Fig. 5b).

Discussion

Effects of leaf species identity and diversity on leaf litter
decomposition in streams under increasing agricultural
intensity

We observed strong preferential feeding responses of detri-
tivores among the leaf species, with alder strongly favored
irrespective of whether leaves were offered in single-spe-
cies or mixed-species leaf litterbags as indicated by the fast

detritivore-mediated leaf litter decomposition rates. Such pref-
erential feeding is in line with previous studies (Hladyz et al.
2009). Preferential feeding patterns are likely explained
by the nutrient content and recalcitrance of the individual
leaf species that shape the attractiveness of the substrate for
microbial decomposers and macroinvertebrate detritivores
(Cornwell et al. 2008, Frainer et al. 2016). Both groups of
heterotrophic organisms tend to prefer resources rich in labile
compounds and nutrients as well as a low recalcitrance (Graça
2001, Gessner et al. 2007) to maximize their net energy intake
and overcome imbalances in C:N:P ratios of leaf litter and
their own tissue (Martinson et al. 2008, Hladyz et al. 2009).

Consequently, we found that the N-fixing and lignin-
poor leaf species alder was preferably eaten by detritivores,
followed by the N-fixing but lignin-richer black locust and
the N-poor and highly lignin-rich oak, indicating that black
locust and oak leaves are less attractive food sources (cf.
Swan et al. 2008, Frainer and McKie 2015). On the other
<figure><img src="image_9.png" /><figcaption>Figure 5. Piecewise structural equation models showing the pathways by which the percentage share of agricultural land use in the streams' catchments, leaf species identity, the SPEAR<sub>pesticides</sub> index, water quality parameters and habitat characteristics influence detritivore-mediated leaf litter decomposition rates in (a) single-species and (b) mixed-species leaf litterbags. Solid black and solid red arrows indicate significant positive and negative influences, respectively. Standardized path coefficients are shown. Note that leaf species identity entered the analyses as a factorial parameter, for which no path coefficients are produced (grey arrow). Marginal R<sup>2</sup> values indicate explained variance. Single-species litterbags: Fisher's C=0.367, p=0.999, 6 df, BIC=52.224; mixed-species litterbags: Fisher's C=3.505, p=0.743, 6 df, BIC=55.362.
* p < 0.05;
* * p < 0.01;
* ** p < 0.001.</figcaption></figure>

the SPEAR<sub>pesticides</sub> index (path coefficient = -0.27, Fig. 5b). The significant influence of leaf species identity on leaf litter decomposition rates became also apparent in the SEM. There was no evidence for a significant influence of any other predictor, including further invertebrate metrics or habitat quality parameters (Fig. 5b).

Discussion

Effects of leaf species identity and diversity on leaf litter
decomposition in streams under increasing agricultural
intensity

We observed strong preferential feeding responses of detri-
tivores among the leaf species, with alder strongly favored
irrespective of whether leaves were offered in single-spe-
cies or mixed-species leaf litterbags as indicated by the fast

detritivore-mediated leaf litter decomposition rates. Such pref-
erential feeding is in line with previous studies (Hladyz et al.
2009). Preferential feeding patterns are likely explained
by the nutrient content and recalcitrance of the individual
leaf species that shape the attractiveness of the substrate for
microbial decomposers and macroinvertebrate detritivores
(Cornwell et al. 2008, Frainer et al. 2016). Both groups of
heterotrophic organisms tend to prefer resources rich in labile
compounds and nutrients as well as a low recalcitrance (Graça
2001, Gessner et al. 2007) to maximize their net energy intake
and overcome imbalances in C:N:P ratios of leaf litter and
their own tissue (Martinson et al. 2008, Hladyz et al. 2009).

Consequently, we found that the N-fixing and lignin-
poor leaf species alder was preferably eaten by detritivores,
followed by the N-fixing but lignin-richer black locust and
the N-poor and highly lignin-rich oak, indicating that black
locust and oak leaves are less attractive food sources (cf.
Swan et al. 2008, Frainer and McKie 2015). On the other
hand, indirect effects via leaf-associated microbial decompos-
ers are conceivable. Fungal decomposers are known to shape
the palatability and nutritious value of leaf litter (Bärlocher
1985, Hladyz et al. 2009). Since also fungal decomposers
prefer nutrient-rich and low recalcitrant leaf litter (Gessner
and Chauvet 1994), alder should have allowed fungi to grow
better and be more productive, as leaf-bound nutrients and
energy are more easily available. Oak and black locust, on
the other hand, are N-poorer and are more recalcitrant and
such leaf litter should have been colonized and processed less
efficiently, retaining a high recalcitrance and low palatabil-
ity, ultimately slowing down detritivore-mediated leaf litter
decomposition (Gonçalves et al. unpubl., Gonçalves et al.
2023). Although we did not measure leaf-associated fungal
biomass, the microbially-mediated decomposition patterns
observed for the three leaf species at least indicate that micro-
organisms increased decomposition of alder vs oak and black
locust leaf litter, irrespective if observed for single-species or
mixed-species leaf litterbags. Rates of detritivore-mediated
leaf litter decomposition decreased for all three leaf species
as agricultural intensity increased. Similar results have been
found in some studies (Piscart et al. 2009, Rasmussen et al.
2012). Most notably, Woodward et al. (2012), who quantified
detritivore-mediated leaf litter decomposition rates across a
broad nutrient gradient (DIN: 14–21641 µg l⁻¹; soluble reac-
tive P: < 1 to 926 µg l⁻¹), also observed declining detritivore
mediated leaf decomposition over nutrient concentrations >
~ 1000 µg DIN l⁻¹, similar to the concentration range at our
sites (Table 1). These negative relationships between increas-
ing agricultural impact and detritivore-mediated decomposi-
tion are likely to reflect a combination of a loss of sensitive,
highly efficient detritivores in the more degraded environ-
mental conditions (Frainer and McKie 2015) and poten-
tial direct effects of pesticides or high concentrations of, for
instance, ammonium on detritivore activity and feeding rates
(Woodward et al. 2012).

In contrast with detritivore-mediated decomposition,
microbially-mediated leaf litter decomposition remained
comparatively stable along the gradient of agricultural inten-
sity in both single-species and mixed-species leaf litterbags, a
pattern also observed in previous studies (Pascoal et al. 2005,
Englert et al. 2015, but see Gulis and Suberkropp 2003 for ele-
vated microbial decomposition in nutrient-enriched environ-
ments). This may be explained by redundancy in the microbial
communities, by which the accomplished function remains
stable because increased biomasses of tolerant species compen-
sate for the loss of sensitive species (Naeem and Li 1997).

Mixing the leaf species can be seen as a very small-scale
manipulation, where three resources are brought into greater
proximity. This gives scope for biodiversity effects, as each
leaf species exhibits their own structural and chemical char-
acteristics, which in turn affect the formation and activity
of microbial communities, detritivore preferences, and ulti-
mately functional dynamics. The observed increase in the
detritivore-mediated leaf litter decomposition rates of oak
and black locust in mixed-species leaf litterbags under low to
intermediate agricultural intensity reflects the importance of

complementarity. Identifying the exact mechanism in a field
study is challenging, but previous research points to several
possibilities. Studies showed compounds being transported
through rhizomorphs of fungal networks from a source site
towards the growing front (Cairney 1992). Fungal translo-
cation of N from N-rich leaf litter (alder) could have sup-
ported the microbial colonization of N-poorer leaf litter
(Handa et al. 2014). These microbial processes might have
increased nutrient content in oak and black locust, making
them a more attractive food resource for detritivores. Litter
mixing might also enhance complementarity by favoring
greater niche differentiation of detritivores among leaf spe-
cies (and among individual leaves at different decay stages),
increasing species-specific feeding efficacies.

A further potential mechanism explaining the positive
effects of litter mixing on decomposition relates to variation
in litter stoichiometry. Alder leaves were almost always a pre-
ferred food source over oak and black locust leaves in mixed-
species leaf litterbags. In most of the cases only midribs of
alder leaves were obtained from coarse-mesh leaf litterbags
while large leaf fragments of oak and black locust remained
(Supporting information). Such feeding patterns can be
explained from an energetic and stoichiometric perspective,
as consumers try optimizing their growth and reproduction
through feeding on high-quality food sources. Meeting their
nutrient demands seems especially challenging for detriti-
vores, as the stoichiometric composition of their food sources
can differ considerably from their body (Cross et al. 2003).
The fact that stoichiometric imbalances between detritivores
and leaf litter were found to be lowest for alder (Hladyz et al.
2009) may therefore explain the strong preferential feeding on
alder leaf litter in mixed-species leaf litterbags. Consequently,
feeding on leaves of lower nutritional value later in the study
might have benefitted from the ‘nutrient subsidy’ provided
by alder earlier in the experiment, such that some key nutri-
ent requirements were already met and allowed more efficient
feeding on the less nutritious species after alder depleted.

Irrespective of the underlying mechanism, complementar-
ity could explain the approximately 2-fold increased detri-
tivore-mediated leaf litter decomposition of oak and black
locust in mixed-species leaf litterbags compared to their sin-
gle-species counterparts under low to intermediate agricul-
tural pressure. Leaf litter diversity effects on detritivore-driven
decomposition were, however, modified along the agricul-
tural intensity gradient, observed as monotonic decreases in
the net biodiversity effect and complementarity as the share
of agriculture in the upstream catchment increased. Bottom–
up effects mediated through less developed networks of fun-
gal hyphae extending among leaf species under increasing
agricultural intensity may have shortened the transport of
N across leaves and by this reduced their nutritious value.
On the other hand, top-down effects, either as lethal or sub-
lethal (reduced feeding efficacy or drift) effects of agriculture
likely compromised complementarity among detritivores, for
instance through variation in the degree of dominance (both
numerical and functional dominance) and the identity of key
species (McKie et al. 2008).
hand, indirect effects via leaf-associated microbial decompos-
ers are conceivable. Fungal decomposers are known to shape
the palatability and nutritious value of leaf litter (Bärlocher
1985, Hladyz et al. 2009). Since also fungal decomposers
prefer nutrient-rich and low recalcitrant leaf litter (Gessner
and Chauvet 1994), alder should have allowed fungi to grow
better and be more productive, as leaf-bound nutrients and
energy are more easily available. Oak and black locust, on
the other hand, are N-poorer and are more recalcitrant and
such leaf litter should have been colonized and processed less
efficiently, retaining a high recalcitrance and low palatabil-
ity, ultimately slowing down detritivore-mediated leaf litter
decomposition (Gonçalves et al. unpubl., Gonçalves et al.
2023). Although we did not measure leaf-associated fungal
biomass, the microbially-mediated decomposition patterns
observed for the three leaf species at least indicate that micro-
organisms increased decomposition of alder vs oak and black
locust leaf litter, irrespective if observed for single-species or
mixed-species leaf litterbags. Rates of detritivore-mediated
leaf litter decomposition decreased for all three leaf species
as agricultural intensity increased. Similar results have been
found in some studies (Piscart et al. 2009, Rasmussen et al.
2012). Most notably, Woodward et al. (2012), who quantified
detritivore-mediated leaf litter decomposition rates across a
broad nutrient gradient (DIN: 14–21641 µg l⁻¹; soluble reac-
tive P: < 1 to 926 µg l⁻¹), also observed declining detritivore
mediated leaf decomposition over nutrient concentrations >
~ 1000 µg DIN l⁻¹, similar to the concentration range at our
sites (Table 1). These negative relationships between increas-
ing agricultural impact and detritivore-mediated decomposi-
tion are likely to reflect a combination of a loss of sensitive,
highly efficient detritivores in the more degraded environ-
mental conditions (Frainer and McKie 2015) and poten-
tial direct effects of pesticides or high concentrations of, for
instance, ammonium on detritivore activity and feeding rates
(Woodward et al. 2012).

In contrast with detritivore-mediated decomposition,
microbially-mediated leaf litter decomposition remained
comparatively stable along the gradient of agricultural inten-
sity in both single-species and mixed-species leaf litterbags, a
pattern also observed in previous studies (Pascoal et al. 2005,
Englert et al. 2015, but see Gulis and Suberkropp 2003 for ele-
vated microbial decomposition in nutrient-enriched environ-
ments). This may be explained by redundancy in the microbial
communities, by which the accomplished function remains
stable because increased biomasses of tolerant species compen-
sate for the loss of sensitive species (Naeem and Li 1997).

Mixing the leaf species can be seen as a very small-scale
manipulation, where three resources are brought into greater
proximity. This gives scope for biodiversity effects, as each
leaf species exhibits their own structural and chemical char-
acteristics, which in turn affect the formation and activity
of microbial communities, detritivore preferences, and ulti-
mately functional dynamics. The observed increase in the
detritivore-mediated leaf litter decomposition rates of oak
and black locust in mixed-species leaf litterbags under low to
intermediate agricultural intensity reflects the importance of

complementarity. Identifying the exact mechanism in a field
study is challenging, but previous research points to several
possibilities. Studies showed compounds being transported
through rhizomorphs of fungal networks from a source site
towards the growing front (Cairney 1992). Fungal translo-
cation of N from N-rich leaf litter (alder) could have sup-
ported the microbial colonization of N-poorer leaf litter
(Handa et al. 2014). These microbial processes might have
increased nutrient content in oak and black locust, making
them a more attractive food resource for detritivores. Litter
mixing might also enhance complementarity by favoring
greater niche differentiation of detritivores among leaf spe-
cies (and among individual leaves at different decay stages),
increasing species-specific feeding efficacies.

A further potential mechanism explaining the positive
effects of litter mixing on decomposition relates to variation
in litter stoichiometry. Alder leaves were almost always a pre-
ferred food source over oak and black locust leaves in mixed-
species leaf litterbags. In most of the cases only midribs of
alder leaves were obtained from coarse-mesh leaf litterbags
while large leaf fragments of oak and black locust remained
(Supporting information). Such feeding patterns can be
explained from an energetic and stoichiometric perspective,
as consumers try optimizing their growth and reproduction
through feeding on high-quality food sources. Meeting their
nutrient demands seems especially challenging for detriti-
vores, as the stoichiometric composition of their food sources
can differ considerably from their body (Cross et al. 2003).
The fact that stoichiometric imbalances between detritivores
and leaf litter were found to be lowest for alder (Hladyz et al.
2009) may therefore explain the strong preferential feeding on
alder leaf litter in mixed-species leaf litterbags. Consequently,
feeding on leaves of lower nutritional value later in the study
might have benefitted from the ‘nutrient subsidy’ provided
by alder earlier in the experiment, such that some key nutri-
ent requirements were already met and allowed more efficient
feeding on the less nutritious species after alder depleted.

Irrespective of the underlying mechanism, complementar-
ity could explain the approximately 2-fold increased detri-
tivore-mediated leaf litter decomposition of oak and black
locust in mixed-species leaf litterbags compared to their sin-
gle-species counterparts under low to intermediate agricul-
tural pressure. Leaf litter diversity effects on detritivore-driven
decomposition were, however, modified along the agricul-
tural intensity gradient, observed as monotonic decreases in
the net biodiversity effect and complementarity as the share
of agriculture in the upstream catchment increased. Bottom–
up effects mediated through less developed networks of fun-
gal hyphae extending among leaf species under increasing
agricultural intensity may have shortened the transport of
N across leaves and by this reduced their nutritious value.
On the other hand, top-down effects, either as lethal or sub-
lethal (reduced feeding efficacy or drift) effects of agriculture
likely compromised complementarity among detritivores, for
instance through variation in the degree of dominance (both
numerical and functional dominance) and the identity of key
species (McKie et al. 2008).
Direct and indirect effects of agricultural intensity
on leaf litter decomposition in streams

The observed negative influence of increasing agricultural intensity in streams' catchments on detritivore-mediated leaf litter decomposition rates match with earlier studies (Piscart et al. 2009, Rasmussen et al. 2012). However, pathways by which agricultural intensity affected the assessed ecosystem function rates differed to some degree between single-species and mixed-species leaf litterbags. In both litterbag types, agricultural intensity showed a direct negative effect on the proportion of sensitive invertebrate species (SPEAR<sub>pesticides</sub>), in turn affecting the detritivore-mediated leaf litter decomposition rates. These patterns have been reported previously (Schäfer et al. 2012) and indicate that stress associated with agricultural land use either alters the functional capacity of species with only minor alteration of the community (Kefford et al. 2012) or leads to the loss of keystone species (Paine 1969), affecting functioning. As a consequence, agricultural land use effects on the functional capacity and abundance of sensitive species seem to translate to similar indirect effects on detritivore-mediated leaf litter decomposition, given the positive relationship between the latter two measures.

The positive correlation between agricultural intensity and the first principal component of the habitat character-
istics observed for single-species leaf litterbags is in line with
previous studies that reported high sediment inputs, loss of
riparian vegetation, and altered hydrology due to agricul-
tural practices that caused excessive sedimentation and loss
of in-stream habitat complexity (as reviewed by Lester and
Boulton 2008). The subsequent negative impact on detriti-
vore-mediated leaf litter decomposition in single-species leaf
litterbags are possibly explained by sedimentation on the
leaf litter surface that reduces the surface area of the leaves
available for microbial colonization and detritivore feeding.
Consequently, leaf litter with less abundant fungal commu-
nities and a lower available surface area for feeding should
represent less attractive food and by this mechanism reduce
leaf litter decomposition rates (cf. Truchy et al. 2022).

In contrast, the direct positive effect of agricultural
intensity on the water quality parameters in the SEM for
mixed-species leaf litterbags reflects the influx of DIN and
PO₄³⁻-P in agricultural streams due to the run-off of fertil-
izers (Moss 2008), a pattern that matches well with earlier
studies (Truchy et al. 2022). Our finding that water quality
parameters in terms of elevated DIN, PO₄³⁻-P, and alkalinity
were negatively associated with SPEARₚesticides may be driven
by a response of that indicator to water quality, and/or past or
current pesticide pollution (Schuwirth et al. 2015).

Finally, the direct (unexplained) effect of agricultural
intensity on leaf litter decomposition rates revealed by the
SEMs for single-species and mixed-species leaf litterbags
seems to point at effects of habitat characteristics or environ-
mental parameters not measured in the present study. These
habitat characteristics and environmental parameters could
be associated with river regulation (deviation in discharge,

channelization, removal of dead wood and vegetation, ditch-
ing) and forest management (habitat clearing, standing age,
tree volume; for more details see Truchy et al. 2022), which
affect detritivore-mediated leaf litter decomposition either
directly or indirectly through altered detritivore communities.

Conclusions

The results of the present study indicate that agricultural
land use weakens the relationship between biodiversity and
ecosystem functioning by detritivores through adverse effects
on mechanisms that govern complementarity in mixed leaf
litter assemblages. This disconnection of the biodiversity-
ecosystem functioning relationship was found at an inter-
mediate agricultural intensity in the streams' catchments and
was seemingly independent of the leaf litter species. Because
agricultural intensity is projected to increase in the future
(Tilman et al. 2011), the effects observed here could have far
reaching consequences for the C dynamics and food webs in
streams that potentially propagate across ecosystem bound-
aries (Schulz et al. 2015). Nevertheless, further scrutiny of
field studies on a larger scale in areas with different climate
regimes, leaf litter input in terms of different leaf species, and
altered flow regimes (e.g. intermittency) is needed to verify
the generalization and transferability of our results across bio-
geographical regions.

Acknowledgements – We thank Ove Jonsson for chemical analyses, Hannah E. Chmiel for her assistance during field work, and Jochen P. Zubrod for his laboratory assistance. Francis Burdon and Jonathan Jupke supported the data analysis. Open Access funding enabled and organized by Projekt DEAL.

*Funding* – The Swedish Research Council for Sustainable Development (FORMAS; grant number: 942-2015-1568) and the Carl Tryggers Stiftelse för Vetenskaplig Forskning, Stockholm, (grant no: CTS 13:72) financially supported this project. GK acknowledges the financial support by the Slovenian research agency (research program Chemical engineering (P2-0191)).

Author contributions

**Alexander Feckler:** Conceptualization (equal); Data cura-
tion (lead); Formal analysis (equal); Investigation (equal);
Methodology (equal); Visualization (lead); Writing – origi-
nal draft (equal); Writing – review and editing (equal). **Jacob
Schnurr:** Investigation (equal); Writing – review and editing
(equal). **Gabriela Kalčíková:** Investigation (equal); Writing
– review and editing (equal). **Amélie Truchy:** Formal analy-
sis (equal); Writing – review and editing (equal). **Brendan
G. McKay:** Conceptualization (equal); Methodology (equal);
Writing – original draft (equal); Writing – review and edit-
ing (equal). **Ralf B. Schäfer:** Conceptualization (equal);
Methodology (equal); Writing – original draft (equal); Writing
– review and editing (equal). **Ralf Schulz:** Conceptualization
(equal); Methodology (equal); Writing – review and edit-
ing (equal). **Mirco Bundschuh:** Conceptualization
Direct and indirect effects of agricultural intensity
on leaf litter decomposition in streams

The observed negative influence of increasing agricultural intensity in streams' catchments on detritivore-mediated leaf litter decomposition rates match with earlier studies (Piscart et al. 2009, Rasmussen et al. 2012). However, pathways by which agricultural intensity affected the assessed ecosystem function rates differed to some degree between single-species and mixed-species leaf litterbags. In both litterbag types, agricultural intensity showed a direct negative effect on the proportion of sensitive invertebrate species (SPEAR<sub>pesticides</sub>), in turn affecting the detritivore-mediated leaf litter decomposition rates. These patterns have been reported previously (Schäfer et al. 2012) and indicate that stress associated with agricultural land use either alters the functional capacity of species with only minor alteration of the community (Kefford et al. 2012) or leads to the loss of keystone species (Paine 1969), affecting functioning. As a consequence, agricultural land use effects on the functional capacity and abundance of sensitive species seem to translate to similar indirect effects on detritivore-mediated leaf litter decomposition, given the positive relationship between the latter two measures.

The positive correlation between agricultural intensity and the first principal component of the habitat character-
istics observed for single-species leaf litterbags is in line with
previous studies that reported high sediment inputs, loss of
riparian vegetation, and altered hydrology due to agricul-
tural practices that caused excessive sedimentation and loss
of in-stream habitat complexity (as reviewed by Lester and
Boulton 2008). The subsequent negative impact on detriti-
vore-mediated leaf litter decomposition in single-species leaf
litterbags are possibly explained by sedimentation on the
leaf litter surface that reduces the surface area of the leaves
available for microbial colonization and detritivore feeding.
Consequently, leaf litter with less abundant fungal commu-
nities and a lower available surface area for feeding should
represent less attractive food and by this mechanism reduce
leaf litter decomposition rates (cf. Truchy et al. 2022).

In contrast, the direct positive effect of agricultural
intensity on the water quality parameters in the SEM for
mixed-species leaf litterbags reflects the influx of DIN and
PO₄³⁻-P in agricultural streams due to the run-off of fertil-
izers (Moss 2008), a pattern that matches well with earlier
studies (Truchy et al. 2022). Our finding that water quality
parameters in terms of elevated DIN, PO₄³⁻-P, and alkalinity
were negatively associated with SPEARₚesticides may be driven
by a response of that indicator to water quality, and/or past or
current pesticide pollution (Schuwirth et al. 2015).

Finally, the direct (unexplained) effect of agricultural
intensity on leaf litter decomposition rates revealed by the
SEMs for single-species and mixed-species leaf litterbags
seems to point at effects of habitat characteristics or environ-
mental parameters not measured in the present study. These
habitat characteristics and environmental parameters could
be associated with river regulation (deviation in discharge,

channelization, removal of dead wood and vegetation, ditch-
ing) and forest management (habitat clearing, standing age,
tree volume; for more details see Truchy et al. 2022), which
affect detritivore-mediated leaf litter decomposition either
directly or indirectly through altered detritivore communities.

Conclusions

The results of the present study indicate that agricultural
land use weakens the relationship between biodiversity and
ecosystem functioning by detritivores through adverse effects
on mechanisms that govern complementarity in mixed leaf
litter assemblages. This disconnection of the biodiversity-
ecosystem functioning relationship was found at an inter-
mediate agricultural intensity in the streams' catchments and
was seemingly independent of the leaf litter species. Because
agricultural intensity is projected to increase in the future
(Tilman et al. 2011), the effects observed here could have far
reaching consequences for the C dynamics and food webs in
streams that potentially propagate across ecosystem bound-
aries (Schulz et al. 2015). Nevertheless, further scrutiny of
field studies on a larger scale in areas with different climate
regimes, leaf litter input in terms of different leaf species, and
altered flow regimes (e.g. intermittency) is needed to verify
the generalization and transferability of our results across bio-
geographical regions.

Acknowledgements – We thank Ove Jonsson for chemical analyses, Hannah E. Chmiel for her assistance during field work, and Jochen P. Zubrod for his laboratory assistance. Francis Burdon and Jonathan Jupke supported the data analysis. Open Access funding enabled and organized by Projekt DEAL.

*Funding* – The Swedish Research Council for Sustainable Development (FORMAS; grant number: 942-2015-1568) and the Carl Tryggers Stiftelse för Vetenskaplig Forskning, Stockholm, (grant no: CTS 13:72) financially supported this project. GK acknowledges the financial support by the Slovenian research agency (research program Chemical engineering (P2-0191)).

Author contributions

**Alexander Feckler:** Conceptualization (equal); Data cura-
tion (lead); Formal analysis (equal); Investigation (equal);
Methodology (equal); Visualization (lead); Writing – origi-
nal draft (equal); Writing – review and editing (equal). **Jacob

Schnurr: Investigation (equal); Writing – review and editing (equal). **Gabriela Kalčíková:** Investigation (equal); Writing – review and editing (equal). **Amélie Truchy:** Formal analysis (equal); Writing – review and editing (equal). **Brendan G. McKay:** Conceptualization (equal); Methodology (equal); Writing – original draft (equal); Writing – review and editing (equal).

**Ralf B. Schäfer:** Conceptualization (equal); Methodology (equal); Writing – original draft (equal); Writing – review and editing (equal). **Ralf Schulz:** Conceptualization (equal); Methodology (equal); Writing – original draft (equal); Writing – review and editing (equal). **Mirco Bundschuh:** Conceptualization (equal); Methodology (equal); Writing – review and editing (equal).
(equal); Funding acquisition (lead); Investigation (equal); Methodology (equal); Writing – original draft (equal); Writing – review and editing (equal).

## Data availability statement

Data are available from GitHub (https://github.com/aflan-dau/https-10.1111-oik.09936). Data, associated metadata, and calculation tools are also available from the corresponding author upon reasonable request (alexander.feckler@rptu.de).

## Supporting information

The Supporting information associated with this article is available with the online version.

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(equal); Funding acquisition (lead); Investigation (equal); Methodology (equal); Writing – original draft (equal); Writing – review and editing (equal).

## Data availability statement

Data are available from GitHub (https://github.com/aflan-dau/https-10.1111-oik.09936). Data, associated metadata, and calculation tools are also available from the corresponding author upon reasonable request (alexander.feckler@rptu.de).

## Supporting information

The Supporting information associated with this article is available with the online version.

## References

Abelho, M. 2001. From litterfall to breakdown in streams: a review. – *Sci. World* J. 1: 656–680.

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Martinson, H. M., Schneider, K., Gilbert, J., Hines, J. E., Hambäck, P. A. and Fagan, W. F. 2008. Detritivory: stoichiometry of a neglected trophic level. – *Ecol. Res.* 23: 487–491.

McKie, B. G., Woodward, G., Hladyz, S., Nistorescu, M., Preda, E., Popescu, C., Giller, P. S. and Malmqvist, B. 2008. Ecosystem functioning in stream assemblages from different regions: contrasting responses to variation in detritivore richness, evenness and density. – *J. Anim. Ecol.* 77: 495–504.

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Naeem, S. and Wright, J. P. 2003. Disentangling biodiversity effects on ecosystem functioning: deriving solutions to a seemingly insurmountable problem. – *Ecol. Lett.* 6: 567–579.

Paine, R. T. 1969. A note on trophic complexity and community stability. – *Am. Nat.* 103: 91–93.

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Piscart, C., Genoel, R., Doledec, S., Chauvet, E. and Marmonier, P. 2009. Effects of intense agricultural practices on heterotrophic processes in streams. – *Environ. Pollut.* 157: 1011–1018.

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Rasmussen, J. J., Wiberg-Larsen, P., Baattrup-Pedersen, A., Monberg, R. J. and Kronvang, B. 2012. Impacts of pesticides and natural stressors on leaf litter decomposition in agricultural streams. – *Sci. Total Environ.* 416: 148–155.

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Schäfer, R. B., von der Ohe, P. C., Rasmussen, J., Kefford, B. J., Bekekov, M. A., Schulz, R. and Liess, M. 2012. Thresholds for the effects of pesticides on invertebrate communities and leaf breakdown in stream ecosystems. – *Environ. Sci. Technol.* 46: 5134–5142.

Schulz, R. 2004. Field studies on exposure, effects, and risk mitigation of aquatic nonpoint-source insecticide pollution: a review. – *J. Environ. Qual.* 33: 419–448.

Schulz, R., Bundschuh, M., Gergs, R., Brühl, C. A., Diehl, D., Entling, M. H., Fahse, L., Frör, O., Jungkunst, H. F., Lorke, A., Schäfer, R. B., Schaumann, G. E. and Schwenk, K. 2015. Review on environmental alterations propagating from aquatic to terrestrial ecosystems. – *Sci. Total Environ.* 538: 246–261.

Schuwirth, N., Kattwinkel, M. and Stamm, C. 2015. How stressor specific are trait-based ecological indices for ecosystem management? – *Sci. Total Environ.* 505: 565–572.

Shipley, B. 2016. Cause and correlation in biology: a User's guide to path analysis, structural equations and causal inference with R. – *Cambridge Univ. Press*.

Swan, C. M., Healey, B. and Richardson, D. C. 2008. The role of native riparian tree species in decomposition of invasive tree of heaven (*Ailanthus altissima*) leaf litter in an urban stream. – *Écoscience* 15: 27–35.

Swan, C. M., Gluth, M. A. and Horne, C. L. 2009. Leaf litter species evenness influences nonadditive breakdown in a headwater stream. – *Ecology* 90: 1650–1658.

Tachet, H., Richoux, P., Bournaud, M. and Usseglio-Polatera, P. 2010. Invertébrés d'eau douce: systématique, biologie, écologie [*Freshwater invertebrates: systematics, biology, ecology*]. – *Centre National de la Recherche Scientifique*.

Tilman, D., Knops, J., Wedin, D., Reich, P., Ritchie, M. and Siemann, E. 1997. The influence of functional diversity and composition on ecosystem processes. – *Science* 277: 1300–1302.

Tilman, D., Balzer, C., Hill, J. and Befort, B. L. 2011. Global food demand and the sustainable intensification of agriculture. – *Proc. Natl Acad. Sci. USA* 108: 20260–20264.

Truchy, A., Göthe, E., Angeler, D. G., Ecke, F., Sponseller, R. A., Bundschuh, M., Johnson, R. K. and McKie, B. G. 2019. Partitioning spatial, environmental, and community drivers of ecosystem functioning. – *Landscape Ecol.* 34: 2371–2384.

Truchy, A., Sponseller, R. A., Ecke, F., Angeler, D. G., Kahler, M., Bundschuh, M., Johnson, R. K. and McKie, B. G. 2022. Responses of multiple structural and functional indicators along three contrasting disturbance gradients. – *Ecol. Indic.* 135: 108514.

Woodward, G. et al. 2012. Continental-scale effects of nutrient pollution on stream ecosystem functioning. – *Science* 336: 1438–1440.
Loreau, M., Naeem, S. and Inchausti, P. (eds.), Biodiversity and ecosystem functioning, synthesis and perspectives. Oxford Univ. Press, pp. 195–281.

Jabiol, J., McKie, B. G., Bruder, A., Bernadet, C., Gessner, M. O. and Chauvet, E. 2013. Trophic complexity enhances ecosystem functioning in an aquatic detritus-based model system. – *J. Anim. Ecol.* 82: 1042–1051.

Kefford, B. J., Schäfer, R. B. and Metzeling, L. 2012. Risk assessment of salinity and turbidity in Victoria (Australia) to stream insects' community structure does not always protect functional traits. – *Sci. Tot. Environ.* 415: 61–68.

Kominoski, J. S., Kominoski, J. S., Hoellein, T. J., Leroy, C. J., Pringle, C. M. and Swan, C. M. 2010. Beyond species richness: expanding biodiversity–ecosystem functioning theory in detritus-based streams. – *Riv. Res. Appl.* 26: 67–75.

Lavorel, S. and Garnier, E. 2002. Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. – *Funct. Ecol.* 16: 545–556.

Lavorel, S., Grigulis, K., McIntyre, S., Williams, N. S. G., Garden, D., Dorrough, J., Berman, S., Quétier, F., Thébault, A. and Bonis, A. 2008. Assessing functional diversity in the field – methodology matters! – *Funct. Ecol.* 22: 134–147.

Lê, S., Josse, J. and Husson, F. 2008. FactoMineR: an R package for multivariate analysis. – *J. Stat. Softw.* 25: 1–18.

Lefcheck, J. S. 2016. piecewiseSEM: piecewise structural equation modelling in r for ecology, evolution, and systematics. – *Methods Ecol. Evol.* 7: 573–579.

Lester, R. E. and Boulton, A. J. 2008. Rehabilitating agricultural streams in Australia with wood: a review. – *Environ. Manage.* 42: 310–326.

Liess, M. and Von Der Ohe, P. C. V. D. 2005. Analyzing effects of pesticides on invertebrate communities in streams. – *Environ. Toxicol. Chem.* 24: 954–965.

López-Rojo, N., Pérez, J., Pozo, J., Basaguren, A., Apodaka-Etxebarria, U., Correa-Araneda, F. and Boyero, L. 2021. Shifts in key leaf litter traits can predict effects of plant diversity loss on decomposition in streams. – *Ecosystems* 24: 185–196.

Loreau, M. and Hector, A. 2001. Partitioning selection and complementarity in biodiversity experiments. – *Nature* 412: 6842.

Martinson, H. M., Schneider, K., Gilbert, J., Hines, J. E., Hambäck, P. A. and Fagan, W. F. 2008. Detritivory: stoichiometry of a neglected trophic level. – *Ecol. Res.* 23: 487–491.

McKie, B. G., Woodward, G., Hladyz, S., Nistorescu, M., Preda, E., Popescu, C., Giller, P. S. and Malmqvist, B. 2008. Ecosystem functioning in stream assemblages from different regions: contrasting responses to variation in detritivore richness, evenness and density. – *J. Anim. Ecol.* 77: 495–504.

Moss, B. 2008. Water pollution by agriculture. – *Phil. Trans. R. Soc. B* 363: 659–666.

Naeem, S. and Li, S. 1997. Biodiversity enhances ecosystem reliability. – *Nature* 390: 507–509.

Naeem, S. and Wright, J. P. 2003. Disentangling biodiversity effects on ecosystem functioning: deriving solutions to a seemingly insurmountable problem. – *Ecol. Lett.* 6: 567–579.

Paine, R. T. 1969. A note on trophic complexity and community stability. – *Am. Nat.* 103: 91–93.

Pascoal, C. C., Cássio, F. and Marvanová, L. 2005. Anthropogenic stress may affect aquatic hyphomycete diversity more than leaf decomposition in a low-order stream. – *Arch. Hydrobiol.* 162: 481–496.

Piscart, C., Genoel, R., Doledec, S., Chauvet, E. and Marmonier, P. 2009. Effects of intense agricultural practices on heterotrophic processes in streams. – *Environ. Pollut.* 157: 1011–1018.

QGIS Development Team 2021. QGIS geographic information system. Open source geospatial foundation project. – https://qgis.org/en/site/

Raderschall, C. A., Bommarco, R., Lindström, S. A. M. and Lundin, O. 2021. Landscape crop diversity and semi-natural habitat affect crop pollinators, pollination benefit and yield. – *Agric. Ecosyst. Environ.* 306: 107189.

Rasmussen, J. J., Wiberg-Larsen, P., Baattrup-Pedersen, A., Monberg, R. J. and Kronvang, B. 2012. Impacts of pesticides and natural stressors on leaf litter decomposition in agricultural streams. – *Sci. Total Environ.* 416: 148–155.

Ritz, C., Baty, F., Streibig, J. C. and Gerhard, D. 2015. Dose-response analysis using R. – *PLoS One* 10: e0146021.

Schäfer, R. B., von der Ohe, P. C., Rasmussen, J., Kefford, B. J., Bekekov, M. A., Schulz, R. and Liess, M. 2012. Thresholds for the effects of pesticides on invertebrate communities and leaf breakdown in stream ecosystems. – *Environ. Sci. Technol.* 46: 5134–5142.

Schulz, R. 2004. Field studies on exposure, effects, and risk mitigation of aquatic nonpoint-source insecticide pollution: a review. – *J. Environ. Qual.* 33: 419–448.

Schulz, R., Bundschuh, M., Gergs, R., Brühl, C. A., Diehl, D., Entling, M. H., Fahse, L., Frör, O., Jungkunst, H. F., Lorke, A., Schäfer, R. B., Schaumann, G. E. and Schwenk, K. 2015. Review on environmental alterations propagating from aquatic to terrestrial ecosystems. – *Sci. Total Environ.* 538: 246–261.

Schuwirth, N., Kattwinkel, M. and Stamm, C. 2015. How stressor specific are trait-based ecological indices for ecosystem management? – *Sci. Total Environ.* 505: 565–572.

Shipley, B. 2016. Cause and correlation in biology: a User's guide to path analysis, structural equations and causal inference with R. – *Cambridge Univ. Press*.

Swan, C. M., Healey, B. and Richardson, D. C. 2008. The role of native riparian tree species in decomposition of invasive tree of heaven (*Ailanthus altissima*) leaf litter in an urban stream. – *Écoscience* 15: 27–35.

Swan, C. M., Gluth, M. A. and Horne, C. L. 2009. Leaf litter species evenness influences nonadditive breakdown in a headwater stream. – *Ecology* 90: 1650–1658.

Tachet, H., Richoux, P., Bournaud, M. and Usseglio-Polatera, P. 2010. Invertébrés d'eau douce: systématique, biologie, écologie [*Freshwater invertebrates: systematics, biology, ecology*]. – *Centre National de la Recherche Scientifique*.

Tilman, D., Knops, J., Wedin, D., Reich, P., Ritchie, M. and Siemann, E. 1997. The influence of functional diversity and composition on ecosystem processes. – *Science* 277: 1300–1302.

Tilman, D., Balzer, C., Hill, J. and Befort, B. L. 2011. Global food demand and the sustainable intensification of agriculture. – *Proc. Natl Acad. Sci. USA* 108: 20260–20264.

Truchy, A., Göthe, E., Angeler, D. G., Ecke, F., Sponseller, R. A., Bundschuh, M., Johnson, R. K. and McKie, B. G. 2019. Partitioning spatial, environmental, and community drivers of ecosystem functioning. – *Landscape Ecol.* 34: 2371–2384.

Truchy, A., Sponseller, R. A., Ecke, F., Angeler, D. G., Kahler, M., Bundschuh, M., Johnson, R. K. and McKie, B. G. 2022. Responses of multiple structural and functional indicators along three contrasting disturbance gradients. – *Ecol. Indic.* 135: 108514.

Woodward, G. et al. 2012. Continental-scale effects of nutrient pollution on stream ecosystem functioning. – *Science* 336: 1438–1440.