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The expansion of tree plantations across tropical biomes

Nature Sustainability volume 5, pages 681–688 (2022)Cite this article

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Abstract

Across the tropics, recent agricultural shifts have led to a rapid expansion of tree plantations, often into intact forests and grasslands. However, this expansion is poorly characterized. Here, we report tropical tree plantation expansion between 2000 and 2012, based on classifying nearly 7 million unique patches of observed tree cover gain using optical and radar satellite imagery. The resulting map was a subsample of all tree cover gain but we coupled it with an extensive random accuracy assessment (n = 4,269 points) to provide unbiased estimates of expansion. Most predicted gain patches (69.2%) consisted of small patches of natural regrowth (31.6 ± 11.9 Mha). However, expansion of tree plantations also dominated increases in tree cover across the tropics (32.2 ± 9.4 Mha) with 92% of predicted plantation expansion occurring in biodiversity hotspots and 14% in arid biomes. We estimate that tree plantations expanded into 9.2% of accessible protected areas across the humid tropics, most frequently in southeast Asia, west Africa and Brazil. Given international tree planting commitments, it is critical to understand how future tree plantation expansion will affect remaining natural ecosystems.

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Fig. 1: Pantropical distribution of natural regrowth and tree plantations.
Fig. 2: Estimated expansion of tree plantations and natural regrowth into terrestrial regions and biomes.
Fig. 3: Expansion of plantations into tropical protected areas.

Data availability

All data needed to replicate our results are available in the article, online or the supplementary information. Manually generated training data are available from the corresponding author, M.E.F., upon reasonable request. Predicted map outputs can be downloaded from the Global Forest Watch data repository: https://data.globalforestwatch.org/content/pantropical-tree-plantation-expansion-2000-2012/about

Code availability

All Python code needed to replicate our input data from Google Earth Engine are available on github at https://github.com/dohyung-kim/plantation. All R code for data analysis are available from the corresponding author, M.E.F., upon reasonable request, with the main R scripts available on github.

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Acknowledgements

We thank R. L. Chazdon, R. Crouzeilles, H. L. Beyer, B. C. Tice, S. Stehman and D. Lagomasino for their contributions to this project’s development. This research was supported by the National Aeronautics and Space Administration under grant no. 80NSSC21K0297.

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Author notes

  1. These authors contributed equally: Matthew E. Fagan, Do-Hyung Kim.

Authors and Affiliations

  1. Department of Geography and Environmental Systems, University of Maryland Baltimore County, Baltimore, MD, USA

    Matthew E. Fagan, Wesley Settle, Lexie Ferry, Justin Drew, Haven Carlson, Joshua Slaughter & Joshua Schaferbien

  2. United Nations Children’s Fund, New York, NY, USA

    Do-Hyung Kim

  3. Department of Geographical Sciences, University of Maryland, College Park, MD, USA

    Alexandra Tyukavina

  4. World Resources Institute, Washington, DC, USA

    Nancy L. Harris & Elizabeth Goldman

  5. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA

    Elsa M. Ordway

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

    Elsa M. Ordway

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  1. Matthew E. Fagan
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Contributions

M.E.F. and D.H.K. were responsible for conceptualization and formal analysis. M.E.F. undertook visualization, project administration and supervision. M.E.F., D.H.K. and A.T. developed the methodology. M.E.F., L.F., J.D., H.C., W.S., J. Slaughter, J. Schaferbien and A.T. conducted validation. N.L.H., E.G. and E.M.O. provided resources (datasets). M.E.F., D.H.K., N.L.H., A.T., E.G. and E.M.O. were responsible for writing.

Corresponding author

Correspondence to Matthew E. Fagan.

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The authors declare no competing interests.

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Peer review information

Nature Sustainability thanks Sean Sloan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Methods, Results, Figs. 1–13 and Tables 1–15.

Reporting Summary

Supplementary Data 1

The testing data used to assess model predictive accuracy is enclosed (“NatureSust_Fagan_test_fin_111520_allC_locsXY_selected2.csv”). The format is a comma-separated text data table (n = 2,000); because some large polygons were sampled more than once, there are only 1,881 unique rows. See the notes column for column name explanations; the X and Y columns describe the patch polygon centroids. The full polygons were used to assess accuracy. The vector polygon boundaries are available from the corresponding author upon request.

Supplementary Data 2

The independent map accuracy assessment data is enclosed (“strRandSampRef_allJoinALL_v5fBCGsel_NatureSustSuppData.csv”). The format is a comma-separated text data table (n = 4,269), with each row representing a stratified random point location. See the description column for column name explanations.

Supplementary Data 3

The land cover class conversion table used to reclassify the TMF map product to match our reference data is enclosed (“Reclass_moist_forest_analysis3_NatSustainSuppData.csv”). The format is a comma-separated text data table, with each row representing a TMF land cover transition class subtype. See the notes column for column name explanations.

Supplementary Data 4

The comparative accuracy assessment data used to assess the GFC and TMF map products across the humid biome is enclosed (“pointsAccA_selectedHansenTMF_fin_NatSustainSuppData.csv”). The format is a comma-separated text data table (n = 2,691), with each row representing a random point location. See the notes column for column name explanations.

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Fagan, M.E., Kim, DH., Settle, W. et al. The expansion of tree plantations across tropical biomes. Nat Sustain 5, 681–688 (2022). https://doi.org/10.1038/s41893-022-00904-w

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