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Risks to global biodiversity and Indigenous lands from China’s overseas development finance

Nature Ecology & Evolution volume 5, pages 1520–1529 (2021)Cite this article

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Abstract

China has become one of the world’s largest lenders in overseas development finance. Development projects, such as roads, railways and power plants, often drive biodiversity loss and infringe on Indigenous lands, yet the risks implicit in China’s overseas development finance are poorly understood. Here we examine the extent to which projects financed by China’s policy banks between 2008 and 2019 occur within and adjacent to areas where large-scale investment can present considerable risks to biodiversity and Indigenous peoples. Further, we compare these risks with those posed by similar projects financed by the World Bank, previously the world’s largest source of development finance. We found that 63% of China-financed projects overlap with critical habitats, protected areas or Indigenous lands, with up to 24% of the world’s threatened birds, mammals, reptiles and amphibians potentially impacted by the projects. Hotspots of the risks are primarily distributed in northern sub-Saharan Africa, Southeast Asia and parts of South America. Overall, China’s development projects pose greater risks than those of the World Bank, particularly within the energy sector. These results provide an important global outlook of socio-ecological risks that can guide strategies for greening China’s development finance around the world.

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Fig. 1: Spatial overlap of China’s DFI projects with socio-ecologically sensitive areas.
Fig. 2: Global distribution of the risks to biodiversity and Indigenous lands from China’s DFI loans.
Fig. 3: Comparison of integrated risks to biodiversity and Indigenous lands between projects financed by Chinese DFIs and the World Bank across sectors (agriculture, energy, extraction and transportation).

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Data availability

The global screening layer of critical habitats is publicly available from the United Nations Environment Programme World Conservation Monitoring Centre41 and the boundaries of protected areas are available from the World Database on Protected Areas44. The spatial ranges of threatened species are available from the IUCN data repository (https://www.iucnredlist.org/resources/spatial-data-download). The Human Footprint data can be downloaded from the Dryad Digital Repository (https://datadryad.org/stash/dataset/doi:10.5061/dryad.052q5). The layer of Indigenous people’s lands can be requested from the corresponding author of the dataset12. The geospatial data of China’s overseas development finance can be requested from the corresponding author of the dataset via the Open Science Framework repository64. The geospatial data of the loans financed by the World Bank between 2008 and 2014 are available from AidData62. Data on the loans financed by the World Bank between 2015 and 2019 are available from the website of the World Bank61. Risk scores for each loan considered in this analysis are available upon reasonable request from the corresponding author.

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Acknowledgements

We acknowledge the Massachusett people, Traditional Owners of the land on which we live and work, and pay our respects to their Elders past, present and emerging. We thank D. Narain, J. Liu and Q. Huang for their constructive comments on an early version of the manuscript. We thank H. Lo, K. Wang, M. Benaderet, N. Fischer, S. Liu and Y. Chang for research assistance. K.P.G. received funding for this project from the Climate and Land Use Alliance, David and Lucile Packard Foundation, Charles Stewart Mott Foundation and Rockefeller Brothers Fund.

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  1. These authors contributed equally: Hongbo Yang, B. Alexander Simmons.

Authors and Affiliations

  1. Global Development Policy Center, Boston University, Boston, MA, USA

    Hongbo Yang, B. Alexander Simmons, Rebecca Ray, Xinyue Ma & Kevin P. Gallagher

  2. Department of Earth and Environment, Boston University, Boston, MA, USA

    Christoph Nolte, Suchi Gopal & Yaxiong Ma

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Contributions

H.Y., B.A.S., R.R. and K.P.G. designed the research with contributions from C.N., S.G., Y.M. and X.M.; H.Y., R.R. and Y.M. compiled the data. H.Y. and B.A.S. performed the analyses and interpreted the results with support from R.R. and K.P.G.; H.Y. and B.A.S. wrote the manuscript. All authors reviewed and commented on the manuscript.

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Correspondence to Kevin P. Gallagher.

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Peer review information Nature Ecology & Evolution thanks Victor Galaz, Divya Narain and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Overlap of project sites of Chinese DFI loans with sensitive social and ecological areas.

Global distribution of project locations of Chinese DFI loans and their overlap with (a) critical habitats, (b) protected areas, and (c) Indigenous peoples’ lands. *Projects outside Indigenous lands are based on the absence of existing, verified data and does not necessarily indicate the absence of lands managed and/or controlled by Indigenous peoples.

Extended Data Fig. 2 Comparison of loan-level integrated risks of China’s overseas DFI portfolio.

Global distribution of project locations of Chinese DFI loans during 2008-2019 according to their (a) maximum and (b) mean risks to biodiversity and Indigenous lands.

Extended Data Fig. 3 Relationship between country-level average risks and the risks posed by Chinese DFI loans.

Comparison of national average risks to biodiversity and Indigenous lands across the landscape and the (a-b) mean and (c-d) maximum risks posed by their Chinese DFI loans. Mean and maximum risks are represented as the average per loan. Countries whose DFI portfolio poses similar levels of risk to what we would expect at random within the country lie closest to the red line (slope m = 1). Countries are indicated by their three-digit ISO code.

Extended Data Fig. 4 Comparison of the risk per site to critical habitats, protected areas, Indigenous lands, and threatened species across different sectors.

The mean risk per site to critical habitats (a), protected areas (b), Indigenous lands (c) were measured as whether the site is overlapped with those sensitive areas (Yes: 100%; No: 0%). The risk per site to threatened species (d) was measured as the site’s weighted species richness value (number of species whose range intersect the site weighted by human footprint index, see methods). Error bars represent the standard error of the mean.

Extended Data Fig. 5 Comparison of the mean risk per loan to critical habitats, protected areas, Indigenous lands, and threatened species across different sectors.

The mean risk per loan to critical habitats (a), protected areas (b), Indigenous lands (c) were measured using the percentages of the loan’s project sites overlap with those sensitive areas. The mean risk per loan to threatened species (d) was measured as the mean weighted species richness values across the loan’s project sites. Error bars represent the standard error of the mean.

Extended Data Fig. 6 Comparison of the maximum risk per loan to critical habitats, protected areas, Indigenous lands, and threatened species across different sectors.

The maximum risk per loan to critical habitats (a), protected areas (b), Indigenous lands (c) were measured as whether the loan has any project site overlap with those sensitive areas (Yes: 100%; No: 0%). The maximum risk per loan to threatened species (d) was measured as the maximum weighted species richness value across the loan’s project sites. Error bars represent the standard error of the mean.

Extended Data Fig. 7 Relationship between mean and maximum integrated risks of DFI loans.

Similarities and discrepancies between loan-level mean and maximum integrated risks to biodiversity and Indigenous lands for (a-b) Chinese DFI loans and (c-d) World Bank loans. Color intensity reflects the density of DFI loans. Loans whose overall and maximum risks are equivalent lie along the solid line (slope m = 1). Dashed lines reflect the quantiles used to identify risk categories.

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Yang, H., Simmons, B.A., Ray, R. et al. Risks to global biodiversity and Indigenous lands from China’s overseas development finance. Nat Ecol Evol 5, 1520–1529 (2021). https://doi.org/10.1038/s41559-021-01541-w

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