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The supply of multiple ecosystem services requires biodiversity across spatial scales

Nature Ecology & Evolution volume 7, pages 236–249 (2023)Cite this article

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Abstract

The impact of local biodiversity loss on ecosystem functioning is well established, but the role of larger-scale biodiversity dynamics in the delivery of ecosystem services remains poorly understood. Here we address this gap using a comprehensive dataset describing the supply of 16 cultural, regulating and provisioning ecosystem services in 150 European agricultural grassland plots, and detailed multi-scale data on land use and plant diversity. After controlling for land-use and abiotic factors, we show that both plot-level and surrounding plant diversity play an important role in the supply of cultural and aboveground regulating ecosystem services. In contrast, provisioning and belowground regulating ecosystem services are more strongly driven by field-level management and abiotic factors. Structural equation models revealed that surrounding plant diversity promotes ecosystem services both directly, probably by fostering the spill-over of ecosystem service providers from surrounding areas, and indirectly, by maintaining plot-level diversity. By influencing the ecosystem services that local stakeholders prioritized, biodiversity at different scales was also shown to positively influence a wide range of stakeholder groups. These results provide a comprehensive picture of which ecosystem services rely most strongly on biodiversity, and the respective scales of biodiversity that drive these services. This key information is required for the upscaling of biodiversity–ecosystem service relationships, and the informed management of biodiversity within agricultural landscapes.

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Fig. 1: Conceptual framework of the relationship between landscape- and field-level land use, field- and plot-level plant diversity and plot-level ecosystem services.
Fig. 2: Relative importance of plant diversity and land-use predictors on cultural, aboveground regulating and provisioning, and belowground regulating ecosystem services.
Fig. 3: The multiple drivers of cultural, aboveground regulating and provisioning, and belowground regulating ecosystem services in grasslands.
Fig. 4: The strength of direct and indirect effects of field-level plant diversity on plot-level ecosystem services.
Fig. 5: Effect of multiple drivers on the multifunctionality of grassland ecosystem services prioritized by four local stakeholder groups.

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Data availability

This work is based on data from several projects of the Biodiversity Exploratories programme (DFG Priority Program 1374). The data used for analyses are publicly available from the Biodiversity Exploratories Information System (https://doi.org/10.17616/R32P9Q), or will become publicly available after an embargo period of 3 years from the end of data assembly to give the owners and collectors of the data time to perform their analysis. Any other relevant data are available from the corresponding author upon reasonable request.

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Acknowledgements

We thank the managers of the three Exploratories, I. Steitz, S. Weithmann, F. Staub, S. Gockel, K. Wiesner, K. Lorenzen, A. Hemp, M. Gorke, M. Teuscher and all former managers for their work in maintaining the plot and project infrastructure; S. Pfeiffer, M. Gleisberg, C. Fischer and J. Mangels for giving support through the central office, J. Nieschulze, M. Owonibi and A. Ostrowski for managing the central database, and E. Linsenmair, D. Hessenmöller, F. Buscot, E.-D. Schulze and the late E. Kalko for their role in setting up the Biodiversity Exploratories project. We thank the administration of the Hainich National Park, the UNESCO Biosphere Reserve Swabian Alb and the UNESCO Biosphere Reserve Schorfheide-Chorin as well as all landowners for the excellent collaboration. The work was partly funded by the DFG Priority Program 1374 ‘Biodiversity-Exploratories’ and by the Senckenberg Gesellschaft für Naturforschung. C.W. is grateful for being funded by the German Research Foundation (DFG, Project number 493487387). E.K. is supported by the German Research Foundation (DFG, KA1590/8-5). H.S. is supported by a María Zambrano fellowship funded by the Ministry of Universities and European Union-Next Generation plan. M.M.G. acknowledges support from the Swiss National Science Foundation (grant number 310030E-173542). S.M. is supported by the German Research Foundation (DFG, MA4436/1-5). P.M. acknowledges support from the German Research Foundation (DFG; MA 7144/1-1). Field work permits were issued by the state environmental offices of Baden-Württemberg, Thüringen and Brandenburg from 2008 to 2021.

Author information

Authors and Affiliations

  1. Senckenberg Biodiversity and Climate Research Centre (SBIK-F), Senckenberg Gesellschaft für Naturforschung, Frankfurt, Germany

    Gaëtane Le Provost, Andrea Larissa Boesing, Markus Fischer, Margot Neyret, Sophie Peter & Peter Manning

  2. INRAE, Bordeaux Sciences Agro, ISVV, SAVE, Villenave d’Ornon, France

    Gaëtane Le Provost

  3. Institute of Plant Sciences, University of Bern, Bern, Switzerland

    Noëlle V. Schenk, Caterina Penone, Eric Allan, Ralph Bolliger, Markus Fischer, Daniel Prati & Hugo Saiz

  4. Thünen Institute of Biodiversity, Braunschweig, Germany

    Jan Thiele

  5. Functional Agrobiodiversity, Department of Crop Sciences, University of Göttingen, Göttingen, Germany

    Catrin Westphal

  6. Institute of Evolutionary Ecology and Conservations Genomics, University of Ulm, Ulm, Germany

    Manfred Ayasse, Kirsten Jung & Marco Tschapka

  7. Ecological Networks, Biology, Technische Universität Darmstadt, Darmstadt, Germany

    Nico Blüthgen & Christiane Weiner

  8. Institute of Soil Science and Land Evalution, Department of Soil Biology, University of Hohenheim, Stuttgart, Germany

    Runa S. Boeddinghaus, Ellen Kandeler & Sven Marhan

  9. Center for Agricultural Technology Augustenberg (LTZ), Section Agroecology, Karlsruhe, Germany

    Runa S. Boeddinghaus

  10. Department of Landscape Ecology and Resources Management, Justus Liebig University Giessen, Gießen, Germany

    Verena Busch & Till Kleinebecker

  11. Forest Entomology, WSL Swiss Federal Research Institute, Birmensdorf, Switzerland

    Martin M. Gossner & Felix Neff

  12. Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, ETH Zürich, Zürich, Switzerland

    Martin M. Gossner

  13. Institute of Landscape Ecology, University of Münster, Münster, Germany

    Norbert Hölzel

  14. Institute of Agricultural Sciences, ETH Zürich, Zürich, Switzerland

    Valentin H. Klaus

  15. Research Data Services, University Library, University of Duisburg-Essen, Duisburg, Germany

    Sophia Leimer

  16. Department of Biology, Xavier University, Cincinnati, OH, USA

    Kathryn Morris

  17. University of Freiburg, Faculty of Biology, Geobotany, Freiburg, Germany

    Sandra Müller & Michael Scherer-Lorenzen

  18. Agroecology and Environment, Agroscope, Zurich, Switzerland

    Felix Neff

  19. Geoecology, University of Tübingen, Tübingen, Germany

    Yvonne Oelmann

  20. School of Environmental and Rural Science, University of New England, Armidale, New South Wales, Australia

    David J. Perović

  21. ISOE—Institute for Social-Ecological Research, Biodiversity and People, Frankfurt am Main, Germany

    Sophie Peter

  22. Institut für Biologie, Plant Ecology, Freie Universität Berlin, Berlin, Germany

    Matthias C. Rillig

  23. Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany

    Matthias C. Rillig

  24. Departamento de Ciencias Agrarias y Medio Natural, Escuela Politécnica Superior, Instituto Universitario de Investigación en Ciencias Ambientales de Aragón (IUCA), Universidad de Zaragoza, Huesca, Spain

    Hugo Saiz

  25. Botanical Garden of the University of Bern, Bern, Switzerland

    Deborah Schäfer

  26. Helmholtz Munich, Research Unit for Comparative Microbiome Analysis, Oberschleissheim, Germany

    Michael Schloter

  27. Chair for Soil Science, Technical University of Munich, Freising, Germany

    Michael Schloter

  28. Max-Planck Institute for Biogeochemistry, Jena, Germany

    Ingo Schöning & Marion Schrumpf

  29. Department of Animal Ecology and Tropical Biology, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany

    Juliane Steckel, Ingolf Steffan-Dewenter & Michael Werner

  30. Natura 2000-Station ‘Unstrut-Hainich/Eichsfeld’, Wildtierland Hainich gGmbH, Hörselberg-Hainich, Germany

    Juliane Vogt

  31. Terrestrial Ecology Research Group, Department of Ecology and Ecosystem Management, Technical University of Munich, Freising, Germany

    Wolfgang Weisser

  32. Department of Biosciences, Swansea University, Swansea, UK

    Konstans Wells

  33. Institute of Geography and Geoecology, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Wolfgang Wilcke

  34. Department of Biological Sciences, University of Bergen, Bergen, Norway

    Peter Manning

Authors
  1. Gaëtane Le Provost
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  2. Noëlle V. Schenk
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  3. Caterina Penone
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  4. Jan Thiele
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  5. Catrin Westphal
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  6. Eric Allan
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  7. Manfred Ayasse
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  9. Runa S. Boeddinghaus
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  10. Andrea Larissa Boesing
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  11. Ralph Bolliger
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  12. Verena Busch
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  13. Markus Fischer
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  14. Martin M. Gossner
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  15. Norbert Hölzel
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  16. Kirsten Jung
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  17. Ellen Kandeler
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  18. Valentin H. Klaus
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  19. Till Kleinebecker
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  20. Sophia Leimer
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  21. Sven Marhan
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  23. Sandra Müller
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  27. David J. Perović
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  28. Sophie Peter
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  29. Daniel Prati
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  30. Matthias C. Rillig
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  31. Hugo Saiz
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  32. Deborah Schäfer
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  33. Michael Scherer-Lorenzen
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  34. Michael Schloter
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  35. Ingo Schöning
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  36. Marion Schrumpf
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  38. Ingolf Steffan-Dewenter
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  39. Marco Tschapka
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  40. Juliane Vogt
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  41. Christiane Weiner
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  42. Wolfgang Weisser
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  43. Konstans Wells
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  44. Michael Werner
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  45. Wolfgang Wilcke
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  46. Peter Manning
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Contributions

G.L.P. and P.M. conceived the study, designed and performed the analyses; G.L.P. and P.M. wrote the manuscript with significant inputs from all authors. Data were contributed by G.L.P., N.V.S., C.P., J.T., C.W., E.A., M.A., N.B., R.S.B., R.B., V.B., M.F., M.M.G., N.H., K.J., E.K., V.H.K., T.K., S.L., S. Marhan, K.M., S. Müller, F.N., Y.O., D.P., S.P., D.J.P., M.C.R., D.S., M.S.-L., M. Schloter, I.S., M. Schrumpf, J.S., I.S.-D., M.T., J.V., C.W., W. Weisser, K.W., M.W., W. Wilcke and P.M. Authorship order was determined as follows: (1) core authors; (2) other authors contributing data and inputs on the manuscript (alphabetical); (3) senior author.

Corresponding author

Correspondence to Gaëtane Le Provost.

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Competing interests

The authors declare no competing interests.

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Nature Ecology & Evolution thanks Rebecca Chaplin-Kramer, Shaopeng Wang, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Drivers of individual cultural, aboveground regulating and provisioning, and belowground regulating ecosystem services in grasslands.

Total standardized effects were calculated based on the results of structural equation models (considering both direct and indirect effects of the predictors) for each predictor: environmental factors, plot-level (50 m × 50 m) plant diversity, field-level (75 m radius from the plot centre) plant diversity, field-level (75 m radius from the plot centre) land use, and landscape-level (1,000 m radius from the plot centre) land use. The total standardized effects correspond to the sum of standardized direct effects (that is individual paths) and indirect effects (that is the multiplied paths). All predictors were scaled to allow interpretation of parameter estimates on a comparable scale. Plot-level and landscape-level predictors were log-transformed. n = 150 biologically independent samples for birdwatching potential, forage quality, nitrogen retention index, potential nitrification, groundwater recharge; n = 147 biologically independent samples for lack of herbivory; n = 146 biologically independent samples for soil carbon stocks; n = 142 biologically independent samples for dung decomposition, lack of pathogen infection and shoot biomass; n = 136 biologically independent samples for phosphorus retention index; n = 119 biologically independent samples for pollination; n = 114 biologically independent samples for acoustic diversity; n = 93 biologically independent samples for soil aggregation; n = 83 biologically independent samples for the natural enemy abundance; n = 70 biologically independent samples for the total flower cover.

Extended Data Fig. 2 The multiple drivers of cultural, aboveground regulating and provisioning, and belowground regulating ecosystem services in grasslands considering average-based multifunctionality indices.

Total standardized effects were calculated based on the results of structural equation models (considering both direct and indirect effects of the predictors) for each predictor: environmental factors, plot-level (50 m × 50 m) plant diversity, field-level (75 m radius from the plot centre) plant diversity, field-level (75 m radius from the plot centre) land use, and landscape-level (1,000 m radius from the plot centre) land use. Models were fitted to four multifunctionality measures: cultural, aboveground regulating and provisioning, and belowground regulating ecosystem service multifunctionality. The total standardized effects correspond to the sum of standardized direct effects (that is individual paths) and indirect effects (that is the multiplied paths). For each multifunctionality measure, total standardized effects of the different predictors are ordered from the highest positive effect to the lowest negative effect. All predictors were scaled to allow interpretation of parameter estimates on a comparable scale. Plot-level and landscape-level predictors were log-transformed. n = 150 biologically independent samples.

Extended Data Fig. 3 The multiple drivers of cultural, aboveground regulating and provisioning, and belowground regulating ecosystem services in grasslands considering multifunctionality indices calculated at the 25% (panel on the left) and 75% (panel on the right) thresholds.

Total standardized effects were calculated based on the results of structural equation models (considering both direct and indirect effects of the predictors) for each predictor: environmental factors, plot-level (50 m × 50 m) plant diversity, field-level (75 m radius from the plot centre) plant diversity, field-level (75 m radius from the plot centre) land use, and landscape-level (1,000 m radius from the plot centre) land use. Models were fitted to four multifunctionality measures: cultural, aboveground regulating and provisioning, and belowground regulating ecosystem service multifunctionality. The total standardized effects correspond to the sum of standardized direct effects (that is individual paths) and indirect effects (that is the multiplied paths). For each multifunctionality measure, total standardized effects of the different predictors are ordered from the highest positive effect to the lowest negative effect. All predictors were scaled to allow interpretation of parameter estimates on a comparable scale. Plot-level and landscape-level predictors were log-transformed. n = 150 biologically independent samples.

Extended Data Fig. 4 Drivers of plot-level plant α-diversity, and field-level plant β-diversity and ɣ-diversity.

To assess the surrounding field-level plant diversity of each grassland plot, we surveyed the vegetation within the major surrounding homogeneous vegetation zones in a 75 m radius of each plot (that is field level). These zones were mostly situated within the same grassland-field as the focal plot but we occasionally surveyed other habitat types (c. 20% were situated in hedgerows, margins or forests). We surveyed at least four quadrats in the surroundings of each grassland plot. Total standardized effects were calculated based on the results of structural equation models (considering both direct and indirect effects of the predictors) for each predictor: environmental factors, plot-level (50 m × 50 m) plant diversity, field-level (75 m radius from the plot centre) plant diversity, field-level (75 m radius from the plot centre) land use, and landscape-level (1,000 m radius from the plot centre) land use. The total standardized effects correspond to the sum of standardized direct effects (that is individual paths) and indirect effects (that is the multiplied paths). Total standardized effects of the different predictors are ordered from the highest positive effect to the lowest negative effect. All predictors were scaled to allow interpretation of parameter estimates on a comparable scale. Plot-level and landscape-level predictors were log-transformed. See Supplementary Data Table 2 for the individual path coefficients. n = 150 biologically independent samples.

Extended Data Fig. 5 Drivers of overall ecosystem service multifunctionality, considering (a) a 50% threshold-based index or (b) an average-based index.

Total standardized effects were calculated based on the results of structural equation models (considering both direct and indirect effects of the predictors) for each predictor: environmental factors, plot-level (50 m × 50 m) plant diversity, field-level (75 m radius from the plot centre) plant diversity, field-level (75 m radius from the plot centre) land use, and landscape-level (1,000 m radius from the plot centre) land use. The total standardized effects correspond to the sum of standardized direct effects (that is individual paths) and indirect effects (that is the multiplied paths). For each multifunctionality measure, total standardized effects of the different predictors are ordered from the highest positive effect to the lowest negative effect. All predictors were scaled to allow interpretation of parameter estimates on a comparable scale. Plot-level and landscape-level predictors were log-transformed. n = 150 biologically independent samples.

Extended Data Fig. 6 The multiple drivers of the most prioritized ecosystem services in grasslands by local stakeholders: aesthetic value, biodiversity conservation, fodder production, carbon sequestration.

Total standardized effects were calculated based on the results of structural equation models (considering both direct and indirect effects of the predictors) for each predictor: environmental factors, plot-level (50 m × 50 m) plant diversity, field-level (75 m radius from the plot centre) plant diversity, field-level (75 m radius from the plot centre) land use, and landscape-level (1,000 m radius from the plot centre) land use. Models were fitted to four ecosystem service supply variables: aesthetic value (that is acoustic diversity and total flower cover, n = 129 independent samples), fodder production (that is shoot biomass and forage quality, n = 150 independent samples), biodiversity conservation (that is birdwatching potential, n = 150 independent samples) and carbon sequestration (that is soil carbon stocks, n = 146 independent samples). The total standardized effects correspond to the sum of standardized direct effects (that is individual paths) and indirect effects (that is the multiplied paths). For each ecosystem service supply variable, total standardized effects of the different predictors are ordered from the highest positive effect to the lowest negative effect. All predictors were scaled to allow interpretation of parameter estimates on a comparable scale. Plot-level and landscape-level predictors were log-transformed.

Supplementary information

Supplementary Information

Supplementary Tables 1–3 and references.

Reporting Summary

Supplementary Data

Supplementary Data 1. Details of the sampling methods for each ecosystem service considered in the analysis. For each ecosystem service, we used a specific indicator measured for one or multiple years. Note that different services were measured on different areas within a given 50 m × 50 m plot. Most data are available at https://doi.org/10.17616/R32P9Q. For more details, see supplementary references. Supplementary Data 2. Path coefficients for the different SEMs fitted to the four multifunctionality measures: cultural, aboveground regulating and provisioning, and belowground regulating ecosystem service multifunctionality. All estimates are standardized path coefficients from the SEMs. Single-headed arrows (→) indicate directional relationships between variables, and double-headed arrows (↔) indicate co-variances between variables. Direct effects correspond to the individual paths (for example, Plant γ-diversity → Cultural ecosystem services), and indirect effects are the multiplied paths (for example, Plant γ-diversity → Plant α-diversity) × (Plant α-diversity → Cultural ecosystem services). n = 150 biologically independent samples. All predictors were scaled to allow interpretation of parameter estimates on a comparable scale.

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Le Provost, G., Schenk, N.V., Penone, C. et al. The supply of multiple ecosystem services requires biodiversity across spatial scales. Nat Ecol Evol 7, 236–249 (2023). https://doi.org/10.1038/s41559-022-01918-5

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