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Nature Ecology & Evolution (2022 )Cite this article
Many studies have shown that biodiversity regulates multiple ecological functions that are needed to maintain the productivity of a variety of ecosystem types. What is unknown is how human activities may alter the ‘multifunctionality’ of ecosystems through both direct impacts on ecosystems and indirect effects mediated by the loss of multifaceted biodiversity. Using an extensive database of 72 lakes spanning four large Neotropical wetlands in Brazil, we demonstrate that species richness and functional diversity across multiple larger (fish and macrophytes) and smaller (microcrustaceans, rotifers, protists and phytoplankton) groups of aquatic organisms are positively associated with ecosystem multifunctionality. Whereas the positive association between smaller organisms and multifunctionality broke down with increasing human pressure, this positive relationship was maintained for larger organisms despite the increase in human pressure. Human pressure impacted multifunctionality both directly and indirectly through reducing species richness and functional diversity of multiple organismal groups. These findings provide further empirical evidence about the importance of aquatic biodiversity for maintaining wetland multifunctionality. Despite the key role of biodiversity, human pressure reduces the diversity of multiple groups of aquatic organisms, eroding their positive impacts on a suite of ecological functions that sustain wetlands.
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The data that support the findings of this study are publicly available on Zenodo Digital Repository at https://doi.org/10.5281/zenodo.6406782. Source data are provided with this paper.
The code that supports the findings and figures of this study is available on Zenodo Digital Repository at https://doi.org/10.5281/zenodo.6406786.
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We would like to thank the Brazilian National Council of Technological and Scientific Development (CNPq) and Fundação Araucaria for all financial support to the SISBIOTA project (MCT/CNPq/MEC/CAPES/FNDCT number 47/2010). We are grateful to Nupelia, INPA, UnB, UFMS for providing access to infrastructure and sampling facilities. D.A.M. received a scholarship from the Brazilian National Council for Scientific and Technological Development (CNPQ: process number 141239/2019-0). F.M.L.-T. received a scholarship from CNPq and CAPES. G.Q.R. was supported by FAPESP (grants 2018/12225- 0 and 2019/08474- 8), CNPq-Brazil productivity grant and funding from the Royal Society, Newton Advanced Fellowship (grant number NAF/R2/180791). P.K. was supported by the Royal Society grant, Newton Advanced Fellowship (number 249 NAF/R2/180791). D.M.P. was supported by Royal Society grant (NMG\R1\201121). F.T.d.M. was supported by ANII National System of Researchers (SNI) and PEDECIBA Geosciencias and Biología. E.J. was supported by the TÜBITAK programme BIDEB2232 (project 118C250). F.A.L.-T., L.F.M.V. and R.P.M. were supported by productivity researchers receiving grants from CNPq and CAPES.
Department of Biology (DBI), Center of Biological Sciences (CCB), State University of Maringá (UEM), Maringá, Brazil
Dieison A. Moi, Fernando M. Lansac-Tôha, Fábio A. Lansac-Tôha, Luiz F. M. Velho & Roger P. Mormul
Laboratory of Multitrophic Interactions and Biodiversity, Department of Animal Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
Department of Botany and Ecology, Institute of Bioscience, Federal University of Mato Grosso, Cuiabá, Brazil
Department of Ecosystem Science and Management, Penn State University, University Park, PA, USA
School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
School of Life and Health Sciences, University of Roehampton, Whitelands College, London, UK
Departamento de Ecología y Gestión Ambiental CURE, Universidad de la República, Maldonado, Uruguay
Department of Ecoscience and WATEC, Aarhus University, Aarhus C, Denmark
Sino-Danish Centre for Education and Research, Beijing, China
Limnology Laboratory, Department of Biological Sciences and Centre for Ecosystem Research and Implementation, Middle East Technical University, Ankara, Turkey
Institute of Marine Sciences, Middle East Technical University, Erdemli-Mersin, Turkey
Freshwater Centre, Finnish Environment Institute, Oulu, Finland
Research Centre in Limnology, Ichthyology and Aquaculture (NUPÉLIA), Centre of Biological Sciences (CCB), State University of Maringá (UEM), Maringá, Brazil
Fábio A. Lansac-Tôha, Luiz F. M. Velho & Roger P. Mormul
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D.A.M., F.M.L.-T., G.Q.R. and R.P.M. developed the original ideas presented in the manuscript; F.A.L.-T. and L.F.M.V. coordinated all the field operations; HFP calculation was performed by T.S.-S. Functional analysis was performed by D.A.M. Statistical modelling was performed by D.A.M. The first draft of the paper was written by D.A.M., and further drafts were written by D.A.M., G.Q.R., R.P.M., B.J.C., P.K., D.M.P., F.T.d.M., E.J. and J.H., and all of the authors contributed to the subsequent drafts.
Correspondence to Dieison A. Moi.
The authors declare no competing interests.
Nature Ecology & Evolution thanks Robert Ptacnik, Rajeev Pillay and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Significant links between the species richness of single organismal group and multi-diversity (joint richness of seven organismal groups) with 11 individual ecosystem functions. Solid coloured lines are extracted from linear mixed-effect models and show the significant relationships with each organismal group and ecosystem function. Non-significant relationships are not shown. Full model results are provided in Supplementary Table 5. All single ecosystem functions are scaled (z-score standard) for better graphical interpretation.
Significant links between the functional diversity of single organismal group and multi-diversity (joint functional diversity of seven organismal groups) with 11 individual ecosystem functions. Solid coloured lines are extracted from linear mixed-effect models and show the significant relationships with each organismal group and ecosystem function. Non-significant relationships are not shown. Full model results are provided in Supplementary Table 6. All single ecosystem functions are scaled (z-score standard) for better graphical interpretation.
Standardized total effects (direct plus indirect effects) of seven ecosystem drivers and species richness to multifunctionality. The results were derived from the structural equation models (Fig. 5a). Species richness represents a composite variable that includes information about the species richness of seven groups of aquatic organisms. For the complete estimated model, see Supplementary Table 8.
Standardized total effects (direct plus indirect effects) of seven ecosystem drivers and functional diversity to multifunctionality. The results were derived from the structural equation models (Fig. 5c). Functional diversity is a composite variable that includes information about the functional diversity of seven groups of aquatic organisms. For the complete estimated model, see Supplementary Table 9.
Supplementary Methods, Figs. 1–11 and Tables 1–12.
Statistical source data—link between the species richness of multiple taxonomic groups and the ecosystem multifunctionality.
Statistical source data—link between the functional diversity of multiple taxonomic groups and the ecosystem multifunctionality.
Statistical source data—link between the species richness of multiple taxonomic groups and the ecosystem multifunctionality across different HFP intensities.
Statistical source data—link between the functional diversity of multiple taxonomic groups and the ecosystem multifunctionality across different HFP intensities.
Statistical source data—SEM results.
Statistical source data—link between the species richness of multiple taxonomic groups and the individual ecosystem functions.
Statistical source data—link between the functional diversity of multiple taxonomic groups and the individual ecosystem functions.
Statistical source data—effects of drivers on multifunctionality—richness model.
Statistical source data—effects of drivers on multifunctionality—functional diversity model.
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Moi, D.A., Lansac-Tôha, F.M., Romero, G.Q. et al. Human pressure drives biodiversity–multifunctionality relationships in large Neotropical wetlands. Nat Ecol Evol (2022). https://doi.org/10.1038/s41559-022-01827-7
DOI: https://doi.org/10.1038/s41559-022-01827-7
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