Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Implications of zero-deforestation palm oil for tropical grassy and dry forest biodiversity

Nature Ecology & Evolution volume 7, pages 250–263 (2023)Cite this article

Subjects

Abstract

Many companies have made zero-deforestation commitments (ZDCs) to reduce carbon emissions and biodiversity losses linked to tropical commodities. However, ZDCs conserve areas primarily based on tree cover and aboveground carbon, potentially leading to the unintended consequence that agricultural expansion could be encouraged in biomes outside tropical rainforest, which also support important biodiversity. We examine locations suitable for zero-deforestation expansion of commercial oil palm, which is increasingly expanding outside the tropical rainforest biome, by generating empirical models of global suitability for rainfed and irrigated oil palm. We find that tropical grassy and dry forest biomes contain >50% of the total area of land climatically suitable for rainfed oil palm expansion in compliance with ZDCs (following the High Carbon Stock Approach; in locations outside urban areas and cropland), and that irrigation could double the area suitable for expansion in these biomes. Within these biomes, ZDCs fail to protect areas of high vertebrate richness from oil palm expansion. To prevent unintended consequences of ZDCs and minimize the environmental impacts of oil palm expansion, policies and governance for sustainable development and conservation must expand focus from rainforests to all tropical biomes.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Climatically suitable locations for rainfed oil palm expansion under ZDCs, by biome.
Fig. 2: Comparison of potential for rainfed, zero-deforestation oil palm expansion among biomes.
Fig. 3: Expected annual fresh fruit bunch (FFB) yields in locations climatically suitable for oil palm expansion under ZDCs, assuming high-fertilizer-input cultivation.
Fig. 4: Potential impacts of rainfed, zero-deforestation oil palm expansion on vertebrates.

Similar content being viewed by others

Data availability

Existing datasets analysed in the article are available at references given within the manuscript. The final models of climatic suitability for rainfed and irrigated oil palm cultivation, and summary data of suitability per ecoregion, are available at https://doi.org/10.17605/OSF.IO/2RH6N. Source data are provided with this paper.

Code availability

The code used to generate oil palm suitability models and conduct analyses is available at https://doi.org/10.17605/OSF.IO/2RH6N.

References

  1. Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A. & Hansen, M. C. Classifying drivers of global forest loss. Science 361, 1108–1111 (2018).

    Article  CAS  Google Scholar 

  2. Laurance, W. F., Sayer, J. & Cassman, K. G. Agricultural expansion and its impacts on tropical nature. Trends Ecol. Evol. 29, 107–116 (2014).

    Article  Google Scholar 

  3. Pendrill, F. et al. Agricultural and forestry trade drives large share of tropical deforestation emissions. Glob. Environ. Change 56, 1–10 (2019).

    Article  Google Scholar 

  4. Haupt, F., Bakhtary, H., Schulte, I., Galt, H. & Streck, C. Progress on Corporate Commitments and their Implementation (Tropical Forest Alliance, 2018); https://www.tropicalforestalliance.org/assets/Uploads/Progress-on-Corporate-Commitments-and-their-Implementation.pdf

  5. Austin, K. G. et al. Mapping and monitoring zero-deforestation commitments. Bioscience 71, 1079–1090 (2021).

    Article  Google Scholar 

  6. Leijten, F. C., Sim, S., King, H. & Verburg, P. H. Which forests could be protected by corporate zero deforestation commitments? A spatial assessment. Environ. Res. Lett. 15, 064021 (2020).

    Article  Google Scholar 

  7. Garrett, R. D. et al. Criteria for effective zero-deforestation commitments. Glob. Environ. Change https://doi.org/10.1016/j.gloenvcha.2018.11.003 (2019).

  8. Lehmann, C. E. R. & Parr, C. L. Tropical grassy biomes: linking ecology, human use and conservation. Phil. Trans. R. Soc. B https://doi.org/10.1098/rstb.2016.0329 (2016).

  9. Miles, L. et al. A global overview of the conservation status of tropical dry forests. J. Biogeogr. 33, 491–505 (2006).

    Article  Google Scholar 

  10. Gibbs, H. K. et al. Brazil’s soy moratorium. Science https://doi.org/10.1126/science.aaa0181 (2015).

  11. Jopke, P. & Schoneveld, G. C. Corporate Commitments to Zero Deforestation: An Evaluation of Externality Problems and Implementation Gaps (CIFOR, 2018); https://doi.org/10.17528/cifor/006827

  12. Parr, C. L., Lehmann, C. E. R., Bond, W. J., Hoffmann, W. A. & Andersen, A. N. Tropical grassy biomes: misunderstood, neglected, and under threat. Trends Ecol. Evol. https://doi.org/10.1016/j.tree.2014.02.004 (2014).

  13. Ratnam, J. et al. When is a ‘forest’ a savanna, and why does it matter? Glob. Ecol. Biogeogr. https://doi.org/10.1111/j.1466-8238.2010.00634.x (2011).

  14. Sanchez-Azofeifa, G. A. et al. Research priorities for neotropical dry forests. Biotropica 37, 477–485 (2005).

    Google Scholar 

  15. Vijay, V., Pimm, S. L., Jenkins, C. N. & Smith, S. J. The impacts of oil palm on recent deforestation and biodiversity loss. PLoS ONE 11, e0159668 (2016).

    Article  Google Scholar 

  16. Principles & Criteria for the Production of Sustainable Palm Oil (RSPO, 2018).

  17. Rosoman, G. et al. (eds) The HCS Approach Toolkit (HCS Approach Steering Group, 2017).

  18. Brown, E. & Senior, M. J. M. (eds) Common Guidance for the Identification of High Conservation Values (HCV Resource Network, 2017).

  19. Furumo, P. R. & Aide, T. M. Characterizing commercial oil palm expansion in Latin America: land use change and trade. Environ. Res. Lett. 12, 024008 (2017).

    Article  Google Scholar 

  20. Dinerstein, E. et al. An ecoregion-based approach to protecting half the terrestrial realm. BioScience https://doi.org/10.1093/biosci/bix014 (2017).

  21. Descals, A. et al. High-resolution global map of smallholder and industrial closed-canopy oil palm plantations. Earth Syst. Sci. Data 13, 1211–1231 (2021).

    Article  Google Scholar 

  22. Woittiez, L. S., van Wijk, M. T., Slingerland, M., van Noordwijk, M. & Giller, K. E. Yield gaps in oil palm: a quantitative review of contributing factors. Eur. J. Agron. 83, 57–77 (2017).

    Article  Google Scholar 

  23. Kuepper, B., Drost, S. & Piotrowski, M. Latin American Palm Oil Linked to Social Risks, Local Deforestation (Chain Reaction Research, 2021); https://chainreactionresearch.com/wp-content/uploads/2021/12/Latin-American-Palm-Oil-Linked-to-Social-Issues-Local-Deforestation-1.pdf

  24. Hoyle, D. et al. RSPO New Planting Procedures: Summary Report of ESIA, HCV Assessments and Management Plan (Terea, Proforest and Olam Palm Gabon, 2017).

  25. Universal Mill List (World Resources Institute, Rainforest Alliance, Proforest & Daemeter, 2018); https://data.globalforestwatch.org/documents/gfw::universal-mill-list/about

  26. Pirker, J., Mosnier, A., Kraxner, F., Havlík, P. & Obersteiner, M. What are the limits to oil palm expansion? Glob. Environ. Change 40, 73–81 (2016).

    Article  Google Scholar 

  27. Fischer, G. et al. Global Agro-Ecological Zones 4 (GAEZ v4) – Model Documentation (FAO, 2021); https://doi.org/10.4060/cb4744en

  28. Global Agro-Ecological Zoning Version 4 (GAEZ v4) (FAO & IIASA, 2021); http://www.fao.org/gaez/

  29. Tao, H. H. et al. Long-term crop residue application maintains oil palm yield and temporal stability of production. Agron. Sustain. Dev. https://doi.org/10.1007/s13593-017-0439-5 (2017).

  30. Wei, L., John Martin, J. J., Zhang, H., Zhang, R. & Cao, H. Problems and prospects of improving abiotic stress tolerance and pathogen resistance of oil palm. Plants 10, 2622 (2021).

    Article  CAS  Google Scholar 

  31. Corley, R. H. & Tinker, P. B. The Oil Palm (Wiley-Blackwell, 2016).

  32. Barona, E., Ramankutty, N., Hyman, G. & Coomes, O. T. The role of pasture and soybean in deforestation of the Brazilian Amazon. Environ. Res. Lett. 5, 024002 (2010).

    Article  Google Scholar 

  33. ten Kate, A., Kuepper, B. & Piotrowski, M. NDPE Policies Cover 83% of Palm Oil Refineries; Implementation at 78% (Chain Reaction Research, 2020); https://chainreactionresearch.com/wp-content/uploads/2020/04/NDPE-Policies-Cover-83-of-Palm-Oil-Refining-Market.pdf

  34. The Trase Yearbook: The State Of Forest Risk Supply Chains (Trase, 2020); https://insights.trase.earth/yearbook/summary

  35. Austin, K. G. et al. Shifting patterns of oil palm driven deforestation in Indonesia and implications for zero-deforestation commitments. Land Use Policy 69, 41–48 (2017).

    Article  Google Scholar 

  36. Furumo, P. R., Rueda, X., Rodríguez, J. S. & Parés Ramos, I. K. Field evidence for positive certification outcomes on oil palm smallholder management practices in Colombia. J. Clean. Prod. 245, 118891 (2020).

    Article  Google Scholar 

  37. Carlson, K. M. et al. Effect of oil palm sustainability certification on deforestation and fire in Indonesia. Proc. Natl Acad. Sci. USA 115, 121–126 (2018).

    Article  CAS  Google Scholar 

  38. Heilmayr, R., Carlson, K. M. & Benedict, J. J. Deforestation spillovers from oil palm sustainability certification. Environ. Res. Lett. 15, 075002 (2020).

    Article  CAS  Google Scholar 

  39. Impact (RSPO, 2022); https://www.rspo.org/impact

  40. Bastos Lima, M. G., Persson, U. M. & Meyfroidt, P. Leakage and boosting effects in environmental governance: a framework for analysis. Environ. Res. Lett. 14, 105006 (2019).

    Article  Google Scholar 

  41. Corley, R. H. V. How much palm oil do we need? Environ. Sci. Policy https://doi.org/10.1016/j.envsci.2008.10.011 (2009).

  42. FAOSTAT: Food and Agriculture Data (FAO, 2020); https://www.fao.org/faostat/en/

  43. Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth: a new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. BioScience 51, 933–938 (2001).

    Article  Google Scholar 

  44. Murphy, B. P., Andersen, A. N. & Parr, C. L. The underestimated biodiversity of tropical grassy biomes. Phil. Trans. R. Soc. B 371, 20150319 (2016).

    Article  Google Scholar 

  45. Smith, J. R., Hendershot, J. N., Nova, N. & Daily, G. C. The biogeography of ecoregions: descriptive power across regions and taxa. J. Biogeogr. https://doi.org/10.1111/jbi.13871 (2020).

  46. Klink, C. A. & Machado, R. B. Conservation of the Brazilian Cerrado. Conserv. Biol. 19, 707–713 (2005).

    Article  Google Scholar 

  47. Strassburg, B. B. N. et al. Moment of truth for the Cerrado hotspot. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-017-0099 (2017).

  48. le Polain de Waroux, Y. et al. The restructuring of South American soy and beef production and trade under changing environmental regulations. World Dev. 121, 188–202 (2019).

    Article  Google Scholar 

  49. Nepstad, L. S. et al. Pathways for recent Cerrado soybean expansion: extending the soy moratorium and implementing integrated crop livestock systems with soybeans. Environ. Res. Lett. 14, 044029 (2019).

    Article  Google Scholar 

  50. Searchinger, T. D. et al. High carbon and biodiversity costs from converting Africa’s wet savannahs to cropland. Nat. Clim. Change https://doi.org/10.1038/nclimate2584 (2015).

  51. Cardoso Da Silva, J. M. & Bates, J. M. Biogeographic patterns and conservation in the South American Cerrado: a tropical savanna hotspot. BioScience 52, 225–233 (2002).

    Article  Google Scholar 

  52. Poggio, L. et al. SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. SOIL 7, 217–240 (2021).

  53. Hill, T. C., Williams, M., Bloom, A. A., Mitchard, E. T. A. & Ryan, C. M. Are inventory based and remotely sensed above-ground biomass estimates consistent? PLoS ONE https://doi.org/10.1371/journal.pone.0074170 (2013).

  54. Ryan, C. M. et al. Ecosystem services from southern African woodlands and their future under global change. Phil. Trans. R. Soc. B https://doi.org/10.1098/rstb.2015.0312 (2016).

  55. Grace, J., Jose, J. S., Meir, P., Miranda, H. S. & Montes, R. A. Productivity and carbon fluxes of tropical savannas. J. Biogeogr. 33, 387–400 (2006).

    Article  Google Scholar 

  56. Scharlemann, J. P., Tanner, E. V., Hiederer, R. & Kapos, V. Global soil carbon: understanding and managing the largest terrestrial carbon pool. Carbon Manag. 5, 81–91 (2014).

    Article  CAS  Google Scholar 

  57. Quezada, J. C., Etter, A., Ghazoul, J., Buttler, A. & Guillaume, T. Carbon neutral expansion of oil palm plantations in the Neotropics. Sci. Adv. 5, eaaw4418 (2019).

    Article  CAS  Google Scholar 

  58. Aleman, J. C., Blarquez, O. & Staver, C. A. Land-use change outweighs projected effects of changing rainfall on tree cover in sub-Saharan Africa. Glob. Change Biol. https://doi.org/10.1111/gcb.13299 (2016).

  59. Espírito-Santo, M. M. et al. Understanding patterns of land-cover change in the Brazilian Cerrado from 2000 to 2015. Phil. Trans. R. Soc. B https://doi.org/10.1098/rstb.2015.0435 (2016).

  60. Overbeck, G. E. et al. Conservation in Brazil needs to include non-forest ecosystems. Divers. Distrib. https://doi.org/10.1111/ddi.12380 (2015).

  61. Hoekstra, J. M., Boucher, T. M., Ricketts, T. H. & Roberts, C. Confronting a biome crisis: global disparities of habitat loss and protection. Ecol. Lett. https://doi.org/10.1111/j.1461-0248.2004.00686.x (2005).

  62. RTRS Standard for Responsible Soy Production Version 3.1 (RTRS, 2017); https://responsiblesoy.org/wp-content/uploads/2019/08/RTRS%20Standard%20Responsible%20Soy%20production%20V3.1%20ING-LOW.pdf

  63. Batlle-Bayer, L., Batjes, N. H. & Bindraban, P. S. Changes in organic carbon stocks upon land use conversion in the Brazilian Cerrado: a review. Agric. Ecosyst. Environ. 137, 47–58 (2010).

    Article  CAS  Google Scholar 

  64. Rockström, J., Falkenmark, M., Lannerstad, M. & Karlberg, L. The planetary water drama: dual task of feeding humanity and curbing climate change. Geophys. Res. Lett. 39, LXXXXX (2012).

    Article  Google Scholar 

  65. Ocampo-Peñuela, N., Garcia-Ulloa, J., Ghazoul, J. & Etter, A. Quantifying impacts of oil palm expansion on Colombia’s threatened biodiversity. Biol. Conserv. https://doi.org/10.1016/j.biocon.2018.05.024 (2018).

  66. Gilroy, J. J. et al. Minimizing the biodiversity impact of Neotropical oil palm development. Glob. Change Biol. 21, 1531–1540 (2015).

    Article  Google Scholar 

  67. Bonn Challenge 2020 Report (IUCN, 2020); https://www.bonnchallenge.org/resources/bonn-challenge-2020-report

  68. Gilroy, J. J. et al. Cheap carbon and biodiversity co-benefits from forest regeneration in a hotspot of endemism. Nat. Clim. Change 4, 503–507 (2014).

    Article  Google Scholar 

  69. Evans, M. C. et al. Carbon farming via assisted natural regeneration as a cost-effective mechanism for restoring biodiversity in agricultural landscapes. Environ. Sci. Policy 50, 114–129 (2015).

    Article  CAS  Google Scholar 

  70. Hunter, M. C., Smith, R. G., Schipanski, M. E., Atwood, L. W. & Mortensen, D. A. Agriculture in 2050: recalibrating targets for sustainable intensification. BioScience https://doi.org/10.1093/biosci/bix010 (2017).

  71. Beyer, R. & Rademacher, T. Species richness and carbon footprints of vegetable oils: can high yields outweigh palm oil’s environmental impact? Sustainability 13, 1813 (2021).

    Article  Google Scholar 

  72. Lee, J. S. H., Ghazoul, J., Obidzinski, K. & Koh, L. P. Oil palm smallholder yields and incomes constrained by harvesting practices and type of smallholder management in Indonesia. Agron. Sustain. Dev. 34, 501–513 (2014).

    Article  Google Scholar 

  73. Murphy, D. J. The future of oil palm as a major global crop: opportunities and challenges. J. Oil Palm Res. 26, 1–24 (2014).

    Google Scholar 

  74. Giam, X., Koh, L. P. & Wilcove, D. S. Tropical crops: cautious optimism. Science https://doi.org/10.1126/science.346.6212.928-a (2014).

  75. Villoria, N. B., Golub, A., Byerlee, D. & Stevenson, J. Will yield improvements on the forest frontier reduce greenhouse gas emissions? A global analysis of oil palm. Am. J. Agric. Econ. 95, 1301–1308 (2013).

    Article  Google Scholar 

  76. Koh, L. P. & Lee, T. M. Sensible consumerism for environmental sustainability. Biol. Conserv. https://doi.org/10.1016/j.biocon.2011.10.029 (2012).

  77. Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).

    Article  Google Scholar 

  78. Harris, N., Goldman, E. & Gibbes, S. Spatial Database of Planted Trees (SDPT) Version 1.0 (World Resources Institute, 2019); https://data.globalforestwatch.org/datasets/tree-plantations

  79. Sutanudjaja, E. H. et al. PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model. Geosci. Model Dev. 11, 2429–2453 (2018).

    Article  Google Scholar 

  80. Global Land Cover (Copernicus, 2019); https://lcviewer.vito.be/

  81. Tsendbazar, N.-E. et al. Copernicus Global Land Operations ‘Vegetation and Energy’ ‘CGLOPS−1’ Validation Report. Moderate Dynamic Land Cover 100m Version 2 (WUR, 2019); https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS1_VR_LC100m-V2.0_I1.00.pdf

  82. Santoro, M. et al. GlobBiomass - global datasets of forest biomass. PANGAEA https://doi.org/10.1594/PANGAEA.894711 (2018).

  83. Santoro, M. et al. A detailed portrait of the forest aboveground biomass pool for the year 2010 obtained from multiple remote sensing observations. Geophys. Res. Abstr. https://doi.org/10.1002/joc.5086 (2018).

  84. Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science https://doi.org/10.1126/science.1244693 (2013).

  85. Gumbricht, T. et al. Tropical and Subtropical Wetlands Distribution Version 7 (CIFOR, 2017); https://doi.org/10.17528/CIFOR/DATA.00058

  86. The IUCN Red List of Threatened Species Version 2018−1 (IUCN, 2018); https://www.iucnredlist.org

  87. Bird Species Distribution Maps of the World Version 6.0 (BirdLife International & Handbook of the Birds of the World, 2016); http://datazone.birdlife.org/species/requestdis

  88. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2018).

  89. Silalertruksa, T. et al. Environmental sustainability of oil palm cultivation in different regions of Thailand: greenhouse gases and water use impact. J. Clean. Prod. 167, 1009–1019 (2017).

    Article  CAS  Google Scholar 

  90. Fourcade, Y., Engler, J. O., Rödder, D. & Secondi, J. Mapping species distributions with Maxent using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias. PLoS ONE 9, e97122 (2014).

    Article  Google Scholar 

  91. Liu, Z. et al. Shifts in the extent and location of rice cropping areas match the climate change pattern in China during 1980–2010. Reg. Environ. Change https://doi.org/10.1007/s10113-014-0677-x (2015).

  92. Singh, K., McClean, C. J., Büker, P., Hartley, S. E. & Hill, J. K. Mapping regional risks from climate change for rainfed rice cultivation in India. Agric. Syst. 156, 76–84 (2017).

    Article  Google Scholar 

  93. Estes, L. D. et al. Comparing mechanistic and empirical model projections of crop suitability and productivity: implications for ecological forecasting. Glob. Ecol. Biogeogr. https://doi.org/10.1111/geb.12034 (2013).

  94. Thuiller, W., Georges, D., Engler, R. & Breiner, F. biomod2: Ensemble Platform for Species Distribution Modelling (2016).

  95. Hernandez, P. A., Graham, C. H., Master, L. L. & Albert, D. L. The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 29, 773–785 (2006).

    Article  Google Scholar 

  96. Merow, C., Smith, M. J., Silander, J. A., Merow, C. & Silander, J. A. A practical guide to Maxent for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36, 1058–1069 (2013).

    Article  Google Scholar 

  97. Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Modell. https://doi.org/10.1016/j.ecolmodel.2005.03.026 (2006).

  98. VanDerWal, J., Shoo, L. P., Graham, C. & Williams, S. E. Selecting pseudo-absence data for presence-only distribution modeling: how far should you stray from what you know? Ecol. Modell. 220, 589–594 (2009).

    Article  Google Scholar 

  99. Hirzel, A. H., Le Lay, G., Helfer, V., Randin, C. F. & Guisan, A. Evaluating the ability of habitat suitability models to predict species presences. Ecol. Modell. 199, 142–152 (2006).

    Article  Google Scholar 

  100. Engler, R., Guisan, A. & Rechsteiner, L. An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data. J. Appl. Ecol. https://doi.org/10.1111/j.0021-8901.2004.00881.x (2004).

  101. Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. https://doi.org/10.1111/j.1365-2664.2006.01214.x (2006).

  102. Global Spatially-Disaggregated Crop Production Statistics Data for 2010 Version 1.1. (International Food Policy Research Institute, 2019); https://doi.org/10.7910/DVN/PRFF8V/M2EMBN

  103. Hofste, R. W. et al. Aqueduct 3.0: Updated Decision-Relevant Global Water Risk Indicators (World Resources Institute, 2019); https://www.wri.org/research/aqueduct-30-updated-decision-relevant-global-water-risk-indicators

  104. Carr, M. K. V. The water relations and irrigation requirements of oil palm (Elaeis guineensis): a review. Exp. Agric. 47, 629–652 (2011).

    Article  Google Scholar 

  105. Yusop, Z., Hui, C. M., Garusu, G. J. & Katimon, A. Estimation of evapotranspiration in oil palm catchments by short-time period water-budget method. Malays. J. Civ. Eng. 20, 160–174 (2008).

    Google Scholar 

  106. Hargreaves, G. H. & Allen, R. G. History and evaluation of Hargreaves evapotranspiration equation. J. Irrig. Drain. Eng. 129, 53–63 (2003).

    Article  Google Scholar 

  107. Trabucco, A. & Zomer, R. J. Global aridity index and potential evapotranspiration (ET0) climate database v2. Figshare https://doi.org/10.6084/m9.figshare.7504448.v3 (2019).

  108. Protected Planet: The World Database on Protected Areas (WDPA) (UNEP-WCMC & IUCN, 2020); www.protectedplanet.net/en/thematic-areas/wdpa

  109. Dudley, N. (ed.) Guidelines for Applying Protected Area Management Categories (IUCN, 2008).

  110. Juffe-Bignoli, D. et al. World Database on Protected Areas User Manual 1.5 (UNEP-WCMC, 2017); https://www.protectedplanet.net/en/resources/wdpa-manual

  111. Chave, J. J. et al. Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145, 87–99 (2005).

    Article  CAS  Google Scholar 

  112. Jetz, W., Wilcove, D. S. & Dobson, A. P. Projected impacts of climate and land-use change on the global diversity of birds. PLoS Biol. https://doi.org/10.1371/journal.pbio.0050157 (2007).

  113. Beyer, R. M. & Manica, A. Historical and projected future range sizes of the world’s mammals, birds, and amphibians. Nat. Commun. 11, 5633 (2020).

    Article  CAS  Google Scholar 

  114. Beyer, R. M. & Manica, A. Global and country-level data of the biodiversity footprints of 175 crops and pasture. Data Brief 36, 106982 (2021).

    Article  CAS  Google Scholar 

  115. Cobertura de la Tierra 100K Periodo 2018 (IDEAM, Instituto de Hidrología, Meteorología y Estudios Ambientales, 2021); http://www.siac.gov.co/catalogo-de-mapas

  116. Souza, C. M. et al. Reconstructing three decades of land use and land cover changes in Brazilian biomes with Landsat archive and Earth Engine. Remote Sens. 12, 2735 (2020).

    Article  Google Scholar 

  117. MapBiomas Project - Collection 6 of the Annual Series of Land Use and Land Cover Maps of Brazil (MapBiomas, 2021); https://plataforma.brasil.mapbiomas.org/

  118. Veldman, J. W. & Putz, F. E. Grass-dominated vegetation, not species-diverse natural savanna, replaces degraded tropical forests on the southern edge of the Amazon Basin. Biol. Conserv. https://doi.org/10.1016/j.biocon.2011.01.011 (2011).

  119. Portillo-Quintero, C. A. & Sánchez-Azofeifa, G. A. Extent and conservation of tropical dry forests in the Americas. Biol. Conserv. https://doi.org/10.1016/j.biocon.2009.09.020 (2010).

  120. Veldman, J. W. et al. Toward an old-growth concept for grasslands, savannas, and woodlands. Front. Ecol. Environ. https://doi.org/10.1890/140270 (2015).

  121. Zaloumis, N. P. & Bond, W. J. Reforestation or conservation? The attributes of old growth grasslands in South Africa. Phil. Trans. R. Soc. B https://doi.org/10.1098/rstb.2015.0310 (2016).

  122. Garnett, S. T. et al. A spatial overview of the global importance of Indigenous lands for conservation. Nat. Sustain. https://doi.org/10.1038/s41893-018-0100-6 (2018).

  123. Djoudi, H., Vergles, E., Blackie, R. R., Koame, C. K. & Gautier, D. Dry forests, livelihoods and poverty alleviation: understanding current trends. Int. For. Rev. https://doi.org/10.1505/146554815815834868 (2015).

  124. Ground-Truthing to Improve Due Diligence on Human Rights in Deforestation-Risk Supply Chains (Forest Peoples Programme, 2020); https://www.forestpeoples.org/en/ground-truthing-to-improve-due-diligence

  125. Drost, S., Rijk, G. & Piotrowski, M. Oil Palm Growers Exposed to USD 0.4-5.9B in Social Compensation Risk (Chain Reaction Research, 2019); https://chainreactionresearch.com/wp-content/uploads/2019/12/Social-compensation-risks-for-palm-growers-4.pdf

Download references

Acknowledgements

S.F. was supported by a joint studentship from Unilever and the University of York. We are very grateful to R. van Beek for providing the hydrological data (monthly water demand and supply) at 5 arcmin resolution. We thank C. Wheatley and C. Beale for assistance in running oil palm suitability models and analysing results, and D. Dent, A. Hodge and C. Thomas helpful comments during development of the Article.

Author information

Authors and Affiliations

  1. Leverhulme Centre for Anthropocene Biodiversity, Department of Biology, University of York, York, UK

    Susannah Fleiss, Philip J. Platts & Jane K. Hill

  2. School of Environmental Sciences, University of Liverpool, Liverpool, UK

    Catherine L. Parr

  3. Department of Zoology & Entomology, University of Pretoria, Pretoria, South Africa

    Catherine L. Parr

  4. School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg, South Africa

    Catherine L. Parr

  5. BeZero Carbon Ltd, London, UK

    Philip J. Platts

  6. Department of Environment and Geography, University of York, York, UK

    Philip J. Platts & Colin J. McClean

  7. Climate Change Specialist Group, Species Survival Commission, International Union for Conservation of Nature, Gland, Switzerland

    Philip J. Platts

  8. Department of Zoology, University of Cambridge, Cambridge, UK

    Robert M. Beyer

  9. Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany

    Robert M. Beyer

  10. Safety and Environmental Assurance Centre, Unilever R&D, Sharnbrook, UK

    Henry King

  11. Department of Biology, University of Oxford, Oxford, UK

    Jennifer M. Lucey

Authors
  1. Susannah Fleiss
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Catherine L. Parr
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Philip J. Platts
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Colin J. McClean
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Robert M. Beyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Henry King
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jennifer M. Lucey
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jane K. Hill
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.F., J.K.H., C.L.P., J.M.L. and H.K. conceived the study; S.F., C.J.M. and P.J.P. designed the models of oil palm suitability; C.L.P. conducted the biome classification; R.M.B. conducted refinements of species range maps; S.F. ran the suitability models, conducted the analyses and led the writing of the manuscript. All authors contributed critically to drafts of the paper and finalized the text.

Corresponding author

Correspondence to Susannah Fleiss.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Ecology & Evolution thanks the anonymous reviewers for their contribution to the peer review of this work.Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Boxplots of aboveground carbon stocks and canopy closure for all non-cultivated land in the tropics (including primary vegetation, secondary vegetation and pasture, and excluding cropland, urban areas and tree plantations), for each biome.

Central bars show the median, lower and upper hinges show the first and third quartiles respectively, whiskers extend to the maximum and minimum values within 1.5*inter-quartile range, and outliers are plotted individually. x-axis labels denote total areas of non-cultivated land of each biome (across the tropics) and sample sizes of individual ~10-km grid-cells. Dashed lines represent the two sets of protection thresholds for zero-deforestation under the High Carbon Stock Approach (see main text Methods). Throughout the Main Article, we report results based on the lower-value thresholds, representing ‘greater habitat protection’ under zero-deforestation commitments.

Source data

Extended Data Fig. 2 Comparison of areas projected as suitable for oil palm cultivation, between an agro-ecological model26 and the species distribution model presented in this article.

(a) For the species distribution model thresholded at Minimal Predicted Area95; (b) for the species distribution model thresholded at Minimal Predicted Area99; (c) for the species distribution model thresholded at Minimal Predicted Area100. We have reported results based on Minimal Predicted Area99 in the Main Article, and provide sensitivity analyses based on the other suitability thresholds and the agro-ecological model in Supplementary Information 3–5.

Extended Data Fig. 3 Climatically-suitable locations for rainfed and irrigated oil palm expansion under zero-deforestation commitments (ZDCs), by biome, assuming that up to 50% of surplus available water could be applied for irrigation.

(a): Neotropics; (b): tropical Africa; (c): tropical Asia and Australasia.

Extended Data Fig. 4 Climatically-suitable locations for rainfed and irrigated oil palm expansion under zero-deforestation commitments (ZDCs), by biome, assuming that up to 100% of surplus available water could be applied for irrigation.

(a): Neotropics; (b): tropical Africa; (c): tropical Asia and Australasia.

Extended Data Table 1 Biome classification for the 25 tropical ecoregions that we reclassified from the original Terrestrial Ecoregions of the World dataset20, based on our knowledge of these habitats, and the classification used in a previous study44
Full size table

Supplementary information

Supplementary Information

Supplementary Results, Discussion and Methods, including Supplementary Figures 1–25 and Supplementary Tables 1–9.

Reporting Summary

Peer Review File

Supplementary Data 1

Raster source data (.tif format) for Fig. 1 and Extended Data Figs. 2–4. All rasters are of extent −180° to 180° longitude, −23.5° to 23.5° latitude; 5 arcmin resolution; Geographic Coordinate System WGS 1984. Fleiss_Fig1_Source_Data.tif—Cells with a value of 0–100 are climatically suitable for oil palm expansion, and those with no value are unsuitable. Value classes suitable for oil palm expansion: 0 existing cropland, tree plantations or urban areas (all biomes); 3 ‘other’ biome; 5 tropical dry forest biome; 7 tropical moist forest biome; 11 tropical grassy biome; 20 locations protected by ZDCs (all biomes); 100 locations in IUCN class I or II protected areas (all biomes). Fleiss_ExDatFig2a_Source_Data.tif, Fleiss_ExDatFig2b_Source_Data.tif, Fleiss_ExDatFig2c_Source_Data.tif—Cell values: 0 unsuitable for oil palm cultivation (according to both the agro-ecological model and the species distribution model); 1 suitable for oil palm cultivation according to the agro-ecological model only; 2 suitable for oil palm cultivation according to the species distribution model only; 3 suitable for oil palm cultivation according to both models. Fleiss_ExDatFig3_Source_Data.tif, Fleiss_ExDatFig4_Source_Data.tif—See Source Data for Fig. 1 for suitable locations for rainfed oil palm expansion. For locations suitable for irrigated expansion: cells with a value of 0–100 are climatically suitable for oil palm expansion under irrigation, and those with no value are unsuitable. Value classes suitable for oil palm expansion: 0 existing cropland, tree plantations or urban areas (all biomes); 3 ‘other’ biome; 5 tropical dry forest biome; 7 tropical moist forest biome; 11 tropical grassy biome; 20 locations protected by ZDCs (all biomes); 100 locations in IUCN class I or II protected areas (all biomes).

Supplementary Data 2

Statistical source data for Supplementary Figures.

Source data

Source Data Fig. 2

Statistical source data

Source Data Fig. 3

Statistical source data

Source Data Fig. 4

Statistical source data

Source Data Extended Data Fig. 1

Statistical source data

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fleiss, S., Parr, C.L., Platts, P.J. et al. Implications of zero-deforestation palm oil for tropical grassy and dry forest biodiversity. Nat Ecol Evol 7, 250–263 (2023). https://doi.org/10.1038/s41559-022-01941-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41559-022-01941-6

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing