in Ecology

Non-native and invasive tree species are abundant in neotropical secondary forest but decline over time

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Abstract

Non-native and invasive species are among the leading causes of global biodiversity loss and could therefore compromise the recovery of native forests after disturbance, such as on abandoned agricultural lands. Here we evaluated how the relative density and richness of non-native woody species (NNS) change across secondary tropical forest succession, determined whether they vary between dry and moist forests and identified the underlying environmental and social drivers of these changes. We used data from 1,561 forest plots and 58 chronosequences from ten neotropical countries. We classified 3,735 woody species by origin and invasiveness. Our analyses and conclusions focus on NNS, whereas native (potentially) invasive groups were examined separately. NNS were widespread, occurring in 81% of the chronosequences and comprising 18% of dry and 41% of moist forest plots. We recorded 11 non-native invasive species, most of which were multifunctional trees associated with human activity. In early succession (the first 10–20 years), NNS reached high relative density and richness, accounting for 28% of stems and 22% of species in moist forests, and 9% of stems and species in dry forests. Both metrics declined considerably during the same period but were still present in late succession, mirroring the successional trajectory of native pioneer species, probably due to canopy closure and increased shading. Spatially, NNS richness increased with the Human Development Index. However, both density and richness were negatively affected by increasing surrounding forest cover, agricultural proximity and precipitation, while soil organic carbon generally favoured NNS retention. Our findings suggest that naturally regrowing forests and maintaining relatively intact forest landscapes provide nature-based solutions to control NNS, thereby protecting native biodiversity, ecosystem integrity and local livelihoods.

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Fig. 1: Distribution of the study plots and socio-ecological drivers.
Fig. 2: Non-native invasive species density.
Fig. 3: Relative stem density per group versus time since abandonment in dry and moist areas.
Fig. 4: Relative species richness per group versus time since abandonment in dry and moist areas.
Fig. 5: Effects of environmental and social drivers on NNS.

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Data availability

The minimum dataset required to interpret, verify and reproduce the findings of this study is provided in the paper and its Supplementary Information. A thorough description of each analysed species, including scientific name, group, presence and absolute density, is provided in Extended Data Table 1. Metadata on the chronosequences and plots used in this study are provided in Extended Data Table 2 (for Fig. 1). The detailed forest inventory data supporting the findings of this study are available from the 2ndFor network (https://sites.google.com/view/2ndfor/home) upon reasonable request, subject to approval by the data providers and compliance with the network’s data-sharing policy and data use agreements. Publicly available datasets were analysed in this study. Taxonomic and invasiveness data are available from the World Checklist of Vascular Plants (https://powo.science.kew.org/), Flora do Brasil (https://floradobrasil.jbrj.gov.br/), the GloNAF database (https://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/ecy.2542#support-information-section), the IUCN SSC Invasive Species Specialist Group list (GISD, https://doi.org/10.3391/mbi.2015.6.2.03) and the CABI Compendium (https://www.cabidigitallibrary.org/). Environmental data are available from CHELSA (https://www.chelsa-climate.org/datasets), SoilGrids (https://soilgrids.org/) and the Copernicus Global Land Cover (https://land.copernicus.eu/). Socio-economic data (HDI) are available via Dryad at https://doi.org/10.5061/dryad.dk1j0 (ref. 89). Source data are provided with this paper.

Code availability

The custom code used for data processing and the main analysis is available via Zenodo at https://doi.org/10.5281/zenodo.19593673 (ref. 93).

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Acknowledgements

We thank J. Powers, P. Balvanera and F. Oberleitner for sharing their data, and I. Nogueira for his contribution during the preliminary phase. We also acknowledge the funding agencies described in the Funding statement.

Funding

We acknowledge the São Paulo Research Foundation (FAPESP, Brazil) for the research grants to A.F.R. (nos 2019/24049-5 and 2022/14605-0) and F.A.R.M. (nos 2024/07707-7 and 2025/26020-5). A.F.R., L.P., F.B. and P.H.S.B. thank FAPESP and NWO for the NewFor Project Grant (no. 2018/18416-2). P.H.S.B. thanks the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO; no. 5160957745). L.P. was supported by the European Research Council Advanced Grant PANTROP 834775, and M.T.v.d.S. was supported by the NWO-Veni.192.027 grant. D.H.D. thanks the Swiss National Science Foundation (Project Grant 310030_215738) and SENACYT (International Collaboration Grant COL10-052). D.K. thanks USAID (BOLFOR). The Brazilian National Council for Scientific and Technological Development (CNPq) is acknowledged for research grants to E.N.B. (nos 350182/2022-1 and 406516/2022-7), B.A.S. (no. 307260/2022-4), C.C.J. (nos 313001/2023-5 and 406792/2021-6), I.C.G.V. (INCT Nexus no. 406516/2022-7), J.S.d.A. (no. 314759/2023-9), M.M.E.S. (nos 403692/2024-5 and 304182/2025-7), P.H.S.B. (no. 304857/2022-0), Y.R.F.N. (no. 304263/2022-2), and G.W.F. and S.C.M. (no. 314309/2023-3). G.W.F. and M.M.E.S. also thank Fapemig (MMES no. APQ-03020-22) and the Knowledge Centre for Biodiversity/CNPq. I.C.G.V. thanks FAPESPA (no. E-2024/2215630). C.C.J. acknowledges support from Instituto Serrapilheira (Chamada 5). G.H. thanks the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes, Brazil; Finance code 001) and the Alexander von Humboldt Foundation. H.F.M.V. thanks Stichting Tropenbos and Stichting Het Kronendak. Á.I. thanks COLCIENCIAS for financial support (call 727 of 2015). M.M.-R. thanks the PAPIIT-UNAM grant no. IN202323. R.L.C. thanks the Blue Moon Foundation and the Andrew W. Mellon Foundation, NSF DEB-0424767, NSF DEB-0639393, NSF DEB-1147429, NSF DEB-1110722, NASA Terrestrial Ecology Program, National Geographic and the University of Connecticut Research Foundation. J.R. and M.C.F. thank the Department of Natural Resources Management & Engineering of the University of Connecticut, USA, and COLCIENCIAS (grant no. 1243-13-16640) and Universidad de La Salle (grant no. PINV-013-2005) for their grants. A.S.-A. thanks the National Sciences and Engineering Research Council of Canada—Discovery Grant Program.

Author information

Authors and Affiliations

  1. Department of Forest Sciences, ‘Luiz de Queiroz’ College of Agriculture, University of São Paulo, Piracicaba, Brazil

    Angélica F. Resende, Fabio A. R. Matos, Ricardo César & Pedro H. S. Brancalion

  2. Forest Ecology and Forest Management Group, Wageningen University & Research, Wageningen, the Netherlands

    Lourens Poorter, Frans Bongers, Iris Hordijk, Masha T. van der Sande, Madelon Lohbeck & Marielos Peña-Claros

  3. Centre for Global Wood Security, University of Cambridge, Cambridge, UK

    Fabio A. R. Matos

  4. Instituto Nacional da Mata Atlântica, Santa Teresa, Brazil

    Gustavo Heringer

  5. Associação para a Conservação da Biodiversidade (PROBIODIVERSA), Viçosa, Brazil

    Gustavo Heringer & Pedro Manuel Villa

  6. Institute of Biodiversity, Thünen Institute, Braunschweig, Germany

    Gustavo Heringer

  7. Center for Agricultural Sciences, Federal University of Santa Catarina, Florianópolis, Brazil

    Catarina C. Jakovac

  8. Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA

    Robin L. Chazdon

  9. Tropical Forests and People Research Centre, University of the Sunshine Coast, Maroochydore, Queensland, Australia

    Robin L. Chazdon

  10. Department of Environmental Systems Sciences, ETH Zurich, Zurich, Switzerland

    Daisy H. Dent

  11. Smithsonian Tropical Research Institute, Balboa, Panama

    Daisy H. Dent, Jefferson S. Hall & Michiel van Breugel

  12. Max Planck Institute of Animal Behavior, Konstanz, Germany

    Daisy H. Dent

  13. CIRAD, UMR EcoFoG (AgroParistech, CNRS, Inrae, Université des Antilles, Université de la Guyane), Kourou, French Guiana

    Géraldine Derroire

  14. CIRAD, UPR Forêts et Sociétés, University of Montpellier, Montpellier, France

    Géraldine Derroire

  15. Department of Forestry, University of Brasilia, Brasília, Brazil

    Géraldine Derroire

  16. Unidad de Recursos Naturales, Centro de Investigación Científica de Yucatán A.C., Mérida, Mexico

    Juan M. Dupuy-Rada & José Luis Hernández-Stefanoni

  17. Universidade Federal de Santa Catarina, Florianópolis, Brazil

    Alfredo Fantini, Daisy Christiane Zambiazi & Alexandre Siminski

  18. Departamento Genética, Ecologia & Evolução, ICB, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Geraldo W. Fernandes

  19. Knowledge Center for Biodiversity, Belo Horizonte, Brazil

    Geraldo W. Fernandes

  20. Institute of Botany, BOKU University, Vienna, Austria

    Peter Hietz

  21. Centro de Estudios Socioecológicos y Cambio Global, Instituto de Investigación de Recursos Biológicos Alexander von Humboldt, Bogotá, Colombia

    Natalia Norden

  22. Programa de Estudios de Posgrado en Geografia, Convenio Universidad Pedagogica y Tecnológica de Colombia-Instituto Geografico Agustin Codazzi, Bogotá, Colombia

    Jorge Ruíz

  23. Departamento de Botânica-CCB, Universidade Federal de Pernambuco, Pernambuco, Brazil

    Marcelo Tabarelli, Jarcilene S. de Almeida-Cortez & Felipe Melo

  24. Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, the Netherlands

    Hans F. M. Vester

  25. Graduate Program in Biodiversity and Nature Conservation, Institute of Biological Sciences, Federal University of Juiz de Fora, Juiz de Fora, Brazil

    Pedro Manuel Villa

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

    Bruno X. Pinho

  27. Plant Production Systems Group & Centre for Crop Systems Analysis, Wageningen University & Research, Wageningen, the Netherlands

    Danaë M. A. Rozendaal

  28. Departamento de Sistemática e Ecologia, Universidade Federal da Paraíba, João Pessoa, Brazil

    Bráulio A. Santos

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

    T. Mitchell Aide

  30. Center for Latin American Studies, University of Florida, Gainesville, FL, USA

    Angélica María Almeyda Zambrano

  31. Fundación Con Vida, Medellín, Colombia

    Esteban Alvarez-Davila

  32. Departamento de Biologia Geral, Universidade Estadual de Montes Claros, Montes Claros, Brazil

    Mário M. Espírito-Santo, Yule R. F. Nunes & Maria D. M. Veloso

  33. Environmental Studies, Colby College, Waterville, ME, USA

    Justin M. Becknell

  34. Spatial Ecology and Conservation Lab, School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL, USA

    Eben N. Broadbent

  35. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt, Bogotá, Colombia

    Carolina Castellano-Castro

  36. Centre de Recherche sur la Biodiversité et l’Environnement, CNRS, Université de Toulouse, IRD, INPT, Toulouse, France

    Jérôme Chave

  37. College of Biological Sciences, University of Minnesota Twin Cities, St. Paul, MN, USA

    Saara J. DeWalt

  38. Fondo Patrimonio Natural para la Biodiversidad y las Áreas Protegidas, Bogotá, Colombia

    Maria C. Fandiño

  39. Neotropical Primate Conservation Colombia, Bogotá, Colombia

    Alma Johanna Hernández

  40. Fundación Jardín Botánico de Medellín, Herbario JAUM, Medellín, Colombia

    Álvaro Idárraga

  41. Science Panel for the Amazon, New York, NY, USA

    André B. Junqueira

  42. Department of Physical and Environmental Sciences, Colorado Mesa University, Grand Junction, CO, USA

    Deborah Kennard

  43. College of the Atlantic, Bar Harbor, ME, USA

    Susan G. Letcher

  44. Facultad de Medio Ambiente y Recursos Naturales, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    René López-Camacho

  45. Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México, Morelia, Mexico

    Miguel Martínez-Ramos & Francisco Mora

  46. Departamento de Ecología y Recursos Naturales, Facultad de Ciencias, Universidad Nacional Autónoma de México, Ciudad de México, Mexico

    Jorge A. Meave

  47. Biological Dynamics of Forest Fragments Project, Environmental Dynamics Research Coordination, Instituto Nacional de Pesquisas da Amazonia, Manaus, Brazil

    Rita Mesquita & G. Bruce Williamson

  48. Departamento de Ecologia, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil

    Sandra C. Müller & Kátia J. Zanini

  49. Instituto Tecnológico de Costa Rica, Escuela de Ingeniería Forestal, Cartago, Costa Rica

    Edgar Ortiz-Malavassi

  50. Centro de Formação em Ciências Agroflorestais, Universidade Federal do Sul da Bahia, Itabuna, Brazil

    Daniel Piotto

  51. Earth and Atmospheric Sciences Department, Centre for Earth Observation Sciences, University of Alberta, Edmonton, Alberta, Canada

    Arturo Sanchez-Azofeifa

  52. Department of Geography, University of British Columbia, Vancouver, British Columbia, Canada

    Naomi B. Schwartz

  53. Soil Science Department, Universidade Federal de Viçosa, Viçosa, Brazil

    Heitor Mancini Teixeira

  54. Department of Ecology, Evolution & Environmental Biology, Columbia University, New York, NY, USA

    Maria Uriarte

  55. Department of Geography, National University of Singapore, Singapore, Singapore

    Michiel van Breugel

  56. Museu Paraense Emilio Goeldi, Belém, Brazil

    Ima C. G. Vieira

  57. Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA

    G. Bruce Williamson

  58. Center for Carbon Research in Tropical Agriculture, University of São Paulo, Piracicaba, Brazil

    Pedro H. S. Brancalion

  59. re.green, Rio de Janeiro, Brazil

    Pedro H. S. Brancalion

Authors

  1. Angélica F. Resende
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  2. Lourens Poorter
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  3. Fabio A. R. Matos
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  4. Frans Bongers
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  6. Gustavo Heringer
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  7. Iris Hordijk
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  8. Catarina C. Jakovac
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  9. Masha T. van der Sande
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  10. Robin L. Chazdon
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  11. Daisy H. Dent
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  12. Géraldine Derroire
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  13. Juan M. Dupuy-Rada
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  14. Alfredo Fantini
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  15. Geraldo W. Fernandes
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  16. José Luis Hernández-Stefanoni
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  17. Peter Hietz
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  18. Madelon Lohbeck
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  19. Natalia Norden
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  20. Jorge Ruíz
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  21. Marcelo Tabarelli
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  22. Hans F. M. Vester
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  23. Pedro Manuel Villa
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  24. Bruno X. Pinho
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  25. Danaë M. A. Rozendaal
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  26. Bráulio A. Santos
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  27. T. Mitchell Aide
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  28. Jarcilene S. de Almeida-Cortez
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  29. Angélica María Almeyda Zambrano
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  30. Esteban Alvarez-Davila
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  31. Mário M. Espírito-Santo
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  32. Justin M. Becknell
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  33. Eben N. Broadbent
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  34. Carolina Castellano-Castro
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  35. Jérôme Chave
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  36. Daisy Christiane Zambiazi
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  37. Saara J. DeWalt
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  38. Maria C. Fandiño
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  39. Jefferson S. Hall
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  40. Alma Johanna Hernández
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  41. Álvaro Idárraga
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  42. André B. Junqueira
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  43. Deborah Kennard
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  44. Susan G. Letcher
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  45. René López-Camacho
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  46. Miguel Martínez-Ramos
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  47. Jorge A. Meave
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  48. Felipe Melo
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  49. Rita Mesquita
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  50. Francisco Mora
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  51. Sandra C. Müller
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  52. Yule R. F. Nunes
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  56. Arturo Sanchez-Azofeifa
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  57. Naomi B. Schwartz
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  58. Alexandre Siminski
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  59. Heitor Mancini Teixeira
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  60. Maria Uriarte
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  61. Michiel van Breugel
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  62. Maria D. M. Veloso
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  63. Ima C. G. Vieira
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  64. G. Bruce Williamson
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  65. Kátia J. Zanini
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  66. Pedro H. S. Brancalion
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Contributions

The core team (A.F.R., L.P., F.B., R.C., G.H., I.H., C.C.J. and M.T.v.d.S.) conceived the study and contributed to the development of the research framework. A.F.R. and F.A.R.M. designed and performed the analyses, with support from L.P. and the core team. Data were collected or curated by all co-authors to build the 2ndFor network. A.F.R. curated the dataset and led the integration of the multi-site database for the current paper. A.F.R. led the writing of the manuscript. L.P., F.B., P.H.S.B., R.C., G.H., I.H., C.C.J. and M.T.v.d.S. contributed to the interpretation of results and critically revised the manuscript. All authors reviewed the manuscript, approved the final version and agree to be accountable for their contributions.

Corresponding author

Correspondence to
Angélica F. Resende.

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Competing interests

P.H.S.B. is a partner at Re.green, a Brazilian forest restoration company. The other authors declare no competing interests.

Peer review

Peer review information

Nature Plants thanks Meredith Martin, João Meira-Neto and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Table 1 Mean absolute density per target group per country
Full size table
Extended Data Table 2 Chronosequence metadata
Full size table
Extended Data Table 3 Species group definitions
Full size table

Extended Data Fig. 1 Native invasive species density and uses.

Maximum relative stem density and reported human uses for five native invasive species (including Psidium guajava, Solanum mauritianum, Leucaena leucocephala, Prosopis juliflora, and Vachellia farnesiana) in their country of occurrence.

Extended Data Fig. 2 Relative stem density of native species.

Modelled relationships of relative stem density versus time since abandonment for native invasive species, native potentially invasive species, and the combined group (N(P)IS) in dry and moist forests. Dots represent observed values. Lines represent model predictions (conditional mean), and shaded areas indicate 95% confidence intervals. Colours indicate groups: native invasive (orange), native potentially invasive (blue), and combined N(P)IS (black). Models were fitted using the native-group dataset (n = 1,419; dry = 651, moist = 768).

Extended Data Fig. 3 Relative richness of native species.

Modelled relationships of relative richness versus time since abandonment for native invasive species, native potentially invasive species, and the combined group (N(P)IS) in dry and moist forests. Dots represent observed values. Lines represent model predictions (conditional mean), and shaded areas indicate 95% confidence intervals. Colours indicate groups: native invasive (orange), native potentially invasive (blue), and combined N(P)IS (black). Models were fitted using the native-group dataset (n = 1,419; dry = 651, moist = 768).

Extended Data Fig. 4 Drivers of native species.

Averaged standardized regression coefficients showing the effects of environmental and social drivers (temperature, precipitation, soil organic carbon, CEC, landscape cover, and HDI) on the relative stem density (a) and richness (b) of native (potentially) invasive species groups. Points represent model estimates, and horizontal lines indicate 95% confidence intervals. Colours indicate groups: combined N(P)IS (black), native invasive (orange), and native potentially invasive (blue). Panels show results for dry (left) and moist (right) forests. Models were fitted using the native-group dataset (n = 1,419; dry = 651, moist = 768).

Supplementary information

Supplementary Information (download PDF )

Supplementary Figs. 1–4, Table 1, Methods and references.

Reporting Summary (download PDF )

Source data

Source Data Fig. 1 (download XLSX )

Statistical source data.

Source Data Fig. 2 (download XLSX )

Statistical source data.

Source Data Fig. 3 (download XLSX )

Statistical source data.

Source Data Fig. 4 (download XLSX )

Statistical source data.

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Resende, A.F., Poorter, L., Matos, F.A.R. et al. Non-native and invasive tree species are abundant in neotropical secondary forest but decline over time.
Nat. Plants (2026). https://doi.org/10.1038/s41477-026-02327-3

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Alan M. Wilson (1964–2026)

The Anthropocene and its rejection: toward an Anthropocenology