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Tropical tree ectomycorrhiza are distributed independently of soil nutrients

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From Nature Ecology & Evolution

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Abstract

Mycorrhizae, a form of plant–fungal symbioses, mediate vegetation impacts on ecosystem functioning. Climatic effects on decomposition and soil quality are suggested to drive mycorrhizal distributions, with arbuscular mycorrhizal plants prevailing in low-latitude/high-soil-quality areas and ectomycorrhizal (EcM) plants in high-latitude/low-soil-quality areas. However, these generalizations, based on coarse-resolution data, obscure finer-scale variations and result in high uncertainties in the predicted distributions of mycorrhizal types and their drivers. Using data from 31 lowland tropical forests, both at a coarse scale (mean-plot-level data) and fine scale (20 × 20 metres from a subset of 16 sites), we demonstrate that the distribution and abundance of EcM-associated trees are independent of soil quality. Resource exchange differences among mycorrhizal partners, stemming from diverse evolutionary origins of mycorrhizal fungi, may decouple soil fertility from the advantage provided by mycorrhizal associations. Additionally, distinct historical biogeographies and diversification patterns have led to differences in forest composition and nutrient-acquisition strategies across three major tropical regions. Notably, Africa and Asia’s lowland tropical forests have abundant EcM trees, whereas they are relatively scarce in lowland neotropical forests. A greater understanding of the functional biology of mycorrhizal symbiosis is required, especially in the lowland tropics, to overcome biases from assuming similarity to temperate and boreal regions.

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Fig. 1: Study sites and variation in the relative abundance of EcM trees and soil properties.
Fig. 2: The association between the relative abundance of EcM trees and soil properties across 30 lowland tropical forests from three major tropical regions.
Fig. 3: The association between the probability of observing EcM trees and their relative abundance in relation to soil fertility across and within 16 lowland tropical forests.

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Data availability

ForestGEO plot data can be obtained upon request via the ForestGEO portal at http://ctfs.si.edu/datarequest/. All data sources are listed in Extended Data Table 1. PCA axes and the contribution (proportion) of EcM trees to basal area can be found at https://doi.org/10.5281/zenodo.10044772 ref. 93.

Code availability

The code to run the analyses at both coarse and fine scales can be found at https://doi.org/10.5281/zenodo.10044772 ref. 93.

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Acknowledgements

We express our gratitude to the dedicated field and data technicians whose meticulous data-gathering efforts were indispensable to this research. Their pivotal contributions formed the backbone of our study. Our gratitude also extends to the teams of scientists behind the papers and datasets that enriched our primary dataset. This research and J.A.M.-V. were supported as part of the Next Generation Ecosystem Experiments-Tropics, funded by the US Department of Energy, Office of Science, Office of Biological and Environmental Research. For site-specific acknowledgements, please refer to Supplementary Table 3.

Author information

Authors and Affiliations

  1. Forest Global Earth Observatory, Smithsonian Tropical Research Institute, Washington, DC, USA

    José A. Medina-Vega, Daniel Zuleta & Stuart J. Davies

  2. Smithsonian Tropical Research Institute, Balboa, Panama

    Salomón Aguilar, James W. Dalling, David Mitre & Rolando Pérez

  3. Center for Conservation and Sustainability, Smithsonian National Zoo and Conservation Biology Institute, Washington, DC, USA

    Alfonso Alonso

  4. Herbier National du Gabon, Institut de Pharmacopée et de Médecine Traditionelle, Libreville, Gabon

    Pulchérie Bissiengou

  5. National Biobank of Thailand, National Science and Technology Development Agency, Khlong Luang, Thailand

    Warren Y. Brockelman & Anuttara Nathalang

  6. Institute of Molecular Biosciences, Mahidol University, Nakhon Pathom, Thailand

    Warren Y. Brockelman

  7. Thai Long-Term Forest Ecological Research Project, Department of Forest Biology, Faculty of Forestry, Kasetsart University, Bangkok, Thailand

    Sarayudh Bunyavejchewin & Nantachai Pongpattananurak

  8. School of Biological Sciences, University of Aberdeen, Aberdeen, UK

    David F. R. P. Burslem

  9. Herbario Amazónico Colombiano, Instituto Amazónico de Investigaciones Científicas Sinchi, Bogotá, Colombia

    Nicolás Castaño

  10. Laboratoire Evolution et Diversité Biologique, CNRS, UPS, IRD, Université Paul Sabatier, Toulouse, France

    Jérôme Chave

  11. Department of Plant Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA

    James W. Dalling

  12. Departamento de Ecologia, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil

    Alexandre A. de Oliveira

  13. Departamento de Ciencias Forestales, Universidad Nacional de Colombia Sede Medellín, Medellín, Colombia

    Álvaro Duque

  14. Department of Science and Technology, Uva Wellassa University, Badulla, Sri Lanka

    Sisira Ediriweera

  15. Faculty of Sciences, University of Kisangani, Kisangani, Democratic Republic of the Congo

    Corneille E. N. Ewango & Jean-Remy Makana

  16. Binatang Research Center, Madang, Papua New Guinea

    Jonah Filip

  17. Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA

    Stephen P. Hubbell

  18. Graduate School of Science, Osaka Metropolitan University, Osaka, Japan

    Akira Itoh

  19. Faculty of Science and Technology, Thammasat University (Rangsit), Pathum Thani, Thailand

    Somboon Kiratiprayoon

  20. Asian School of the Environment, Nanyang Technological University, Singapore, Singapore

    Shawn K. Y. Lum

  21. Institut de Recherche en Ecologie Tropicale, Centre National de la Recherche Scientifique et Technologique, Libreville, Gabon

    Hervé Memiaghe

  22. Sarawak Forestry Department, Kuching, Malaysia

    Mohizah Bt. Mohamad & Sylvester Tan

  23. Sabah Forestry Department, Forest Research Centre, Sandakan, Malaysia

    Reuben Nilus

  24. School of Science, Navajo Technical University, Crownpoint, NM, USA

    Nsalambi V. Nkongolo

  25. Institut Facultaire des Sciences Agronomiques (IFA) de Yangambi, Kisangani, Democratic Republic of the Congo

    Nsalambi V. Nkongolo

  26. Biology Centre, Institute of Entomology of the Czech Academy of Sciences, Ceske Budejovice, Czech Republic

    Vojtech Novotny

  27. Faculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic

    Vojtech Novotny

  28. Estación Experimental de Zonas Áridas, Consejo Superior de Investigaciones Científicas, Almería, Spain

    Michael J. O’Brien

  29. Southeast Asia Rainforest Research Partnership (SEARRP), Kota Kinabalu, Malaysia

    Glen Reynolds

  30. School of Biological Sciences, University of Nebraska, Lincoln, NE, USA

    Sabrina E. Russo

  31. Center for Plant Science Innovation, University of Nebraska, Lincoln, NE, USA

    Sabrina E. Russo

  32. UK Centre for Ecology and Hydrology, Edinburgh, UK

    Jill Thompson

  33. Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York, NY, USA

    María Uriarte

  34. Escuela de Ciencias Biológicas, Pontificia Universidad Católica del Ecuador, Quito, Ecuador

    Renato Valencia

  35. Coordenação de Dinâmica Ambiental (CODAM), Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Brazil

    Alberto Vicentini

  36. Forestry and Environment Division, Forest Research Institute Malaysia, Kepong, Malaysia

    Tze Leong Yao

  37. Department of Environmental Sciences, University of Puerto Rico, San Juan, PR, USA

    Jess K. Zimmerman

Authors
  1. José A. Medina-Vega
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  2. Daniel Zuleta
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Contributions

J.A.M.-V. and S.J.D. conceptualized the study, coordinated the data compilations, designed the analysis and interpreted the data. J.A.M.-V. performed data analyses. J.A.M.-V. led the writing of the paper with inputs from S.J.D., D.F.R.P.B., J.W.D., S.E.R. and D.Z. S.A., A.A., P.B., W.Y.B., S.B., N.C., J.C., A.A.d.O., Á.D., S.E., C.E.N.E., J.F., S.P.H., A.I., S.K., S.K.Y.L., J.-R.M., H.M., D.M., M.B.M., A.N., R.N., N.V.N., V.N., M.J.O., R.P., N.P., G.R., S.T., J.T., M.U., R.V., A.V., T.L.Y., J.K.Z. and D.Z. provided coordination and leadership, data management and quality control, travel, consumables and commented on the paper.

Corresponding author

Correspondence to José A. Medina-Vega.

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The authors declare no competing interests.

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Nature Ecology & Evolution thanks Leho Tedersoo, César Marín 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 31 study sites.

Letters indicate the tags used to identify plots in the principal component analysis (PCA) of soil data, constructed using coarse scale soil data (Fig. 1b and Extended Data Table 1). The names of each study site are enclosed in parentheses. Thirty sites were used in the analysis at a coarse scale, whereas 16 sites (shown in bold and italics) were used for the fine scale analysis (see Methods). Map made with Natural Earth.

Extended Data Fig. 2 Variation in quadrat-level basal area and its association with the probability of observing EcM trees and their relative abundance in 16 lowland tropical forests.

a, Shows the distribution of the quadrat-level total basal area (BA) after applying a natural logarithm transformation. The x-axis represents the transformed total BA for each 20 × 20 m quadrat, whereas the y-axis indicates the study site. Vertical lines at the base of each density curve indicate individual observations. b,c, Present mean site-level coefficients, with panel b representing the probability (Prob.) of observing EcM trees and panel c for their relative abundance (conditional on the presence of EcM trees; Cd. Rel. Abun.) in relation to the quadrat-level total BA. The x-axes show the value of the coefficient on the logit scale, with the y-axes again showing the study site. Error bars show the 95% credible interval of the coefficient. These coefficients and their credible intervals derive from 200 draws from the Zero-Altered Beta (ZABE) regression’s posterior predictive distribution. This regression estimated the probability of observing EcM trees and their conditional relative abundance in BA, with the total quadrat-level basal area being logarithmically transformed before the analyses. The study includes 16 sites from lowland tropical regions in Africa (Af., two sites), Asia (As., eight sites), the neotropics (Neo., five sites), and Oceania (O., one site). Dashed lines indicate that the coefficients are not different from zero.

Extended Data Table 1 List of the 31 study sites94,95,96,97,98,99,100,101,102
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Extended Data Table 2 List of the 16 study sites for the analysis at a fine scale
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Extended Data Table 3 Principal component analyses (PCA) of soil data at coarse and fine scales
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Extended Data Table 4 Coefficients for the analysis of the relative abundance of EcM trees in relation to soil properties at a coarse scale
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Extended Data Table 5 Coefficients for the analysis of the relative abundance of EcM trees among and within 16 lowland tropical forests at a fine scale
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Extended Data Table 6 Coefficients for the analysis of the relative abundance of EcM trees among and within 13 lowland tropical forests at a fine scale
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Supplementary information

Supplementary Information

Supplementary discussion, Note 1, Tables 1–3 and Figs. 1 and 2.

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Medina-Vega, J.A., Zuleta, D., Aguilar, S. et al. Tropical tree ectomycorrhiza are distributed independently of soil nutrients. Nat Ecol Evol 8, 400–410 (2024). https://doi.org/10.1038/s41559-023-02298-0

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