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Soil biodiversity supports the delivery of multiple ecosystem functions in urban greenspaces

Nature Ecology & Evolution volume 7, pages 113–126 (2023)Cite this article

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Abstract

While the contribution of biodiversity to supporting multiple ecosystem functions is well established in natural ecosystems, the relationship of the above- and below-ground diversity with ecosystem multifunctionality remains virtually unknown in urban greenspaces. Here we conducted a standardized survey of urban greenspaces from 56 municipalities across six continents, aiming to investigate the relationships of plant and soil biodiversity (diversity of bacteria, fungi, protists and invertebrates, and metagenomics-based functional diversity) with 18 surrogates of ecosystem functions from nine ecosystem services. We found that soil biodiversity across biomes was significantly and positively correlated with multiple dimensions of ecosystem functions, and contributed to key ecosystem services such as microbially driven carbon pools, organic matter decomposition, plant productivity, nutrient cycling, water regulation, plant–soil mutualism, plant pathogen control and antibiotic resistance regulation. Plant diversity only indirectly influenced multifunctionality in urban greenspaces via changes in soil conditions that were associated with soil biodiversity. These findings were maintained after controlling for climate, spatial context, soil properties, vegetation and management practices. This study provides solid evidence that conserving soil biodiversity in urban greenspaces is key to supporting multiple dimensions of ecosystem functioning, which is critical for the sustainability of urban ecosystems and human wellbeing.

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Fig. 1: The distribution of soil sampling locations in urban greenspaces.
Fig. 2: Soil biodiversity drives multiple ecosystem functions in urban greenspaces.
Fig. 3: Relationships between soil biodiversity and multi-threshold ecosystem functioning.
Fig. 4: Relationships between soil biodiversity and independent dimensions of ecosystem functioning.
Fig. 5: Contribution of soil biodiversity to ecosystem functions in urban greenspaces.
Fig. 6: Relationships between the diversity of soil microbial traits and ecosystem multifunctionality.

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Data availability

Soil biodiversity, plant diversity and ecosystem functioning data from urban greenspaces are publicly available at figshare: https://doi.org/10.6084/m9.figshare.21175492.v3 (ref. 64).

Code availability

Code for statistical analyses is available at https://github.com/huahuafan/Global-urban-greenspaces.

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Acknowledgements

We thank the researchers involved in the MUSGONET project for collection of field data and soil samples. This study was supported by a 2019 Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation (URBANFUN), and by the BES grant agreement number LRB17\1019 (MUSGONET). M.D.-B. acknowledges support from the Spanish Ministry of Science and Innovation for the I+D+i project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033. M.D.-B. is also supported by a project of the Fondo Europeo de Desarrollo Regional (FEDER) and the Consejería de Transformación Económica, Industria, Conocimiento y Universidades of the Junta de Andalucía (FEDER Andalucía 2014-2020 Objetivo temático ‘01—Refuerzo de la investigación, el desarrollo tecnológico y la innovación’) associated with the research project P20_00879 (ANDABIOMA). H.C. was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA28020202), National Key R&D Program of China (2022YFD1500202) and the National Natural Science Foundation of China (91951109, 42230511, 92251305). K.F. was supported by Young Elite Scientist Sponsorship Program by CAST (2021QNRC001) and China Postdoctoral Science Foundation (2021M703302). F.D.A. and S.A. were supported by ANID FONDECYT 11180538 and 1170995. J.P.V. was supported by SERB (SIR/2022/000626, EEQ/2021/001083), DST (DST/INT/SL/P-31/2021) and Banaras Hindu University, IoE (6031) incentives grant for plant-microbe interaction and soil microbiome research. T.G. and T.U.N were supported by the Slovenian Research Agency grants P4-0107, J4-3098 and J4-4547.

Author information

Authors and Affiliations

  1. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China

    Kunkun Fan & Haiyan Chu

  2. University of Chinese Academy of Sciences, Beijing, China

    Kunkun Fan & Haiyan Chu

  3. Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia

    David J. Eldridge

  4. National Institute of Agricultural Technology (INTA), Institute of Soil Science, Hurlingham, Argentina

    Juan J. Gaitan

  5. National University of Luján, Department of Technology, Luján, Argentina

    Juan J. Gaitan

  6. National Research Council of Argentina (CONICET), Buenos Aires, Argentina

    Juan J. Gaitan

  7. College of Resources and Environment, Huazhong Agricultural University, Wuhan, China

    Yu-Rong Liu & Xin-Quan Zhou

  8. Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA

    Blessing Sokoya

  9. Hawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales, Australia

    Jun-Tao Wang

  10. School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria, Australia

    Hang-Wei Hu & Ji-Zheng He

  11. Institute of Grassland Science, Northeast Normal University, Changchun, China

    Wei Sun, Haiying Cui, Ling Wang, Jianyong Wang & Tianxue Yang

  12. GEMA Center for Genomics, Ecology and Environment, Faculty of Interdisciplinary Studies, Universidad Mayor, Santiago, Chile

    Fernando D. Alfaro & Sebastian Abades

  13. CEBAS-CSIC, Murcia, Spain

    Felipe Bastida & Marta Díaz-López

  14. Natural History Museum (Botany Unit), Obafemi Awolowo University, Ile-Ife, Nigeria

    Adebola R. Bamigboye

  15. Institut de Biologia Evolutiva (UPF-CSIC), Barcelona, Spain

    Miguel Berdugo

  16. Institute of Integrative Biology, Department of Environment Systems Science, ETH Zurich, Univeritätstrasse, Zurich, Switzerland

    Miguel Berdugo

  17. Department of Plant Biology and Ecology, University of Seville, Seville, Spain

    José L. Blanco-Pastor

  18. Department of Forest Physiology and Genetics, Slovenian Forestry Institute, Ljubljana, Slovenia

    Tine Grebenc & Tina U. Nahberger

  19. Misión Biolóxica de Galicia, Consejo Superior de Investigaciones Científicas, Pontevedra, Spain

    Jorge Duran

  20. Centre for Functional Ecology, Department of Life Sciences, University of Coimbra, Calçada Martim de Freitas, Coimbra, Portugal

    Jorge Duran & Alexandra Rodríguez

  21. Department of Entomology, Washington State University, Pullman, WA, USA

    Javier G. Illán

  22. Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa

    Thulani P. Makhalanyane

  23. Plant–Microbe Interaction Lab, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, Uttar Pradesh, India

    Arpan Mukherjee & Jay Prakash Verma

  24. Laboratório de Sistemática Vegetal, Departamento de Botânica, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Pampulha, Belo Horizonte, Brazil

    Gabriel F. Peñaloza-Bojacá

  25. Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Científicas, Madrid, Spain

    César Plaza

  26. Soil Microbiology Lab, Department of Soil Science, Federal University of Ceara, Fortaleza, Brazil

    Jay Prakash Verma

  27. Department of Biogeography and Global Change, National Museum of Natural History (MNCN), Spanish National Research Council (CSIC) C/ Serrano 115bis, Madrid, Spain

    Ana Rey

  28. Instituto de Geología, Universidad Nacional Autónoma de México, Ciudad Universitaria, México D.F., México

    Christina Siebe

  29. Departamento de Botância e Ecologia, Instituto de Biociências, Universidade Federal de Mato Grosso, Boa Esperança, Cuiabá, Brazil

    Alberto L. Teixido

  30. Microbiome Network and Department of Agricultural Biology, Colorado State University, Fort Collins, CO, USA

    Pankaj Trivedi

  31. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China

    Xiaobing Zhou

  32. Department of Natural Resources, Agricultural Research Organization, Institute of Plant Sciences, Gilat Research Center, Negev, Israel

    Eli Zaady

  33. Department of Mycology and Microbiology, University of Tartu, Tartu, Estonia

    Leho Tedersoo

  34. Laboratorio de Biodiversidad y Funcionamiento Ecosistémico, Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), CSIC, Sevilla, Spain

    Manuel Delgado-Baquerizo

  35. Unidad Asociada CSIC-UPO (BioFun), Universidad Pablo de Olavide, Sevilla, Spain

    Manuel Delgado-Baquerizo

Authors
  1. Kunkun Fan
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  2. Haiyan Chu
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  3. David J. Eldridge
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  5. Yu-Rong Liu
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  9. Ji-Zheng He
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  10. Wei Sun
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  12. Fernando D. Alfaro
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  13. Sebastian Abades
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  15. Marta Díaz-López
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  16. Adebola R. Bamigboye
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  18. José L. Blanco-Pastor
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  19. Tine Grebenc
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  20. Jorge Duran
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  21. Javier G. Illán
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  22. Thulani P. Makhalanyane
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  28. Ana Rey
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  33. Ling Wang
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  35. Tianxue Yang
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  36. Xin-Quan Zhou
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  37. Xiaobing Zhou
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  38. Eli Zaady
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  39. Leho Tedersoo
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  40. Manuel Delgado-Baquerizo
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Contributions

M.D.-B. developed the original idea and designed the research with discussion with H.Chu. and K.F. M.D.-B. coordinated all field and laboratory operations. K.F., M.D.-B. and H.Chu. analysed data. Field data were collected by M.D.-B., D.J.E., Y.-R.L., B.S., A.R.B., J.L.B.-P., J.G.I., T.P.M., C.S., P.T., E.Z., J.P.V., L.W., J.W., T.G., A.M., M.B., G.F.P.-B., T.U.N., A.L.T., X.-Q.Z., F.B., M.D.-L, J.D., A. Rodríguez., X.Z., F.D.A., S.A., C.P., J.J.G., J.-T.W., H.-W.H., J.-Z.H., W.S., H.Cui., T.Y., L.T. and A. Rey. The manuscript was written by K.F., M.D.-B. and H.Chu., with contributions from all co-authors.

Corresponding authors

Correspondence to Haiyan Chu or Manuel Delgado-Baquerizo.

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Competing interests

The authors declare no competing interests.

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Nature Ecology & Evolution thanks María Gómez Brandón and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Location of the 27 urban greenspaces selected for shotgun sequencing analyses.

Location of the 27 urban greenspaces selected for shotgun sequencing analyses and covering the entire biogeographical range in Fig. 1.

Extended Data Fig. 2 Ordinary least squares linear regression between plant diversity and the multiple dimensions of ecosystem functions.

Ordinary least squares linear regression between plant diversity and the multiple dimensions of ecosystem functions, n = 56 study sites.

Extended Data Fig. 3 Conceptual model investigating the direct and indirect linkages between soil biodiversity and ecosystem function.

Conceptual model investigating the direct and indirect linkages between soil biodiversity and ecosystem function. (a) A priori structural equation modeling (SEM) metamodel aimed to evaluate the link between soil biodiversity and ecosystem multifunctionality after controlling for key ecological predictors such as space, climate, and soil and plant attributes. (b) Explanations for each association link priori structural equation modeling metamodel.

Extended Data Fig. 4 Random forest model detects soil biota that are accurately predictive of ecosystem multifunctionality in urban greenspaces across the globe.

Random forest model detects soil biota that are accurately predictive of ecosystem multifunctionality in urban greenspaces across the globe. The result of predicting ecosystem multifunctionality in urban greenspaces across the globe using the random forest (RF) models for the soil biota of the selected groups (bacteria, fungi, protists, and invertebrates). Heat maps of the relative abundance of the 77 indicative soil biota and ecosystem multifunctionality. Statistical analysis was performed using two-sided spearman correlations; P values were adjusted by Benjamini Hochberg false discovery correction, and indicated by asterisks, ‘*’ represents Benjamini Hochberg-adjusted 0.01 < P ≤ 0.05; ‘**’ represents Benjamini Hochberg-adjusted P ≤ 0.01; n = 56 study sites.

Extended Data Fig. 5 Random forest model detects soil genes that are accurately predictive of ecosystem multifunctionality in urban greenspaces across the globe.

Random forest model detects soil genes that are accurately predictive of ecosystem multifunctionality in urban greenspaces across the globe. (a) Random forest model detects 159 genes in contributing to the ecosystem multifunctionality in urban greenspaces across the globe. (b) Ordinary least squares linear regression between multifunctionality and the proportion of the selected nutrient cycling associated genes: methane monooxygenase subunit A encoding (pmoA) gene, ferredoxin-nitrate reductase encoding (narB) gene, alkaline phosphatase D encoding (phoD) gene, and sulfate adenylyltransferase subunit 2 encoding (cysD) gene; n = 27 study sites.

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Fan, K., Chu, H., Eldridge, D.J. et al. Soil biodiversity supports the delivery of multiple ecosystem functions in urban greenspaces. Nat Ecol Evol 7, 113–126 (2023). https://doi.org/10.1038/s41559-022-01935-4

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