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Freshwater biodiversity impacts of global hydropower dams

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Abstract

Hydropower expansion creates tension between renewable energy goals and freshwater ecosystem health. However, the global impacts of dams across the full spectrum of freshwater biodiversity remain poorly quantified. Here, we combine remote sensing and global threatened species datasets to assess dam-related risk patterns for fish, mollusks, mammals, odonates, and amphibians. We show that threatened freshwater species are consistently more common near dams than elsewhere, with mammals showing the highest exposure. Most species whose risk status changed between 1996 and 2022 shifted toward higher threat levels in dam-influenced areas affected by habitat loss and reduced river connectivity. Planned future dams, concentrated in Global South countries, may further elevate extinction risk, particularly for critically endangered fish. These findings support sustainable planning that balances energy development with freshwater conservation.

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Data availability

The datasets used in this study are publicly available. Dam data were obtained from the global dam tracker (GDAT; accessed 30 December 2024). Species conservation status and range data were obtained from the IUCN Red List (accessed 30 December 2024; subject to IUCN terms of use). River connectivity data were obtained from the global free-flowing rivers dataset (Grill et al. 2019; accessed 30 December 2024). The Source data underlying the figures and tables, and other derived and aggregated datasets supporting the findings of this study, are publicly available via Zenodo (https://doi.org/10.5281/zenodo.18348239).18348239. Original third-party spatial datasets (e.g., IUCN species range polygons) are not redistributed due to licensing restrictions; the Zenodo repository provides derived outputs sufficient to reproduce the analyses and visualizations reported in this study.

Code availability

Custom code used for data processing and analysis is available from the corresponding authors upon reasonable request.

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Acknowledgements

This work was funded by the National Natural Science Foundation of China (42371311, 42330109), the National Key R&D Program of China (2024YFD1600700, 2024YFD1600701), the Science and Technology Department of Gansu Province (23JRRA1122), Henan Province International Science and Technology Cooperation Program (252102521024), the Youth Innovation Promotion Association of Chinese Academy of Sciences (2021227), the Natural Science Foundation of Jilin Province (20240101016JJ).

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Authors and Affiliations

  1. Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Heilongjiang Province Collaborative Innovation Center of Cold Region Ecological Safety, Harbin Normal University, Harbin, China

    Na Ding & Miao Li

  2. Faculty of Geographical Science and Engineering, Henan University, Zhengzhou, China

    Na Ding, Zunyi Xie, Beiming Cai, Qinghe Zhao, Guanpeng Dong & Changhong Miao

  3. State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China

    Na Ding, Zongming Wang, Jianguo Li, Mingming Jia & Kaishan Song

  4. Climate Change and Carbon Neutrality Lab, Henan University, Kaifeng, China

    Zunyi Xie, Guanpeng Dong & Changhong Miao

  5. School of Environment, The University of Queensland, Brisbane, QLD, Australia

    Zunyi Xie & Eve McDonald-Madden

  6. Department of Civil Engineering, Monash University, Clayton, VIC, Australia

    Xiaoming Wang

  7. Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai, China

    Hongkai Gao

  8. CSIRO, Environment, Waite Campus, Adelaide, SA, Australia

    Sicong Gao

  9. Centre for Applied Water Science, University of Canberra, Canberra, ACT, Australia

    Sicong Gao

  10. Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng, China

    Guanpeng Dong & Changhong Miao

  11. System Earth Science, Maastricht University, Venlo, The Netherlands

    Christopher J. O’Bryan

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  1. Na Ding
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Contributions

Na Ding: conceptualization, data curation, methodology, formal analysis, visualization, writing—original draft. Zunyi Xie: conceptualization, methodology, supervision, writing—review and editing. Xiaoming Wang: methodology, validation, writing—review and editing. Zongming Wang: resources, supervision, writing—review and editing. Miao Li: conceptualization, supervision, funding acquisition, writing—review and editing. Beiming Cai: data curation, validation, writing—review and editing. Qinghe Zhao: data curation, writing—review and editing. Eve McDonald-Madden: interpretation, writing—review and editing. Jianguo Li: interpretation, writing—review and editing. Hongkai Gao: data curation, writing—review and editing. Sicong Gao: methodology, validation, writing—review and editing. Mingming Jia: data curation, writing—review and editing. Kaishan Song: resources, writing—review and editing. Guanpeng Dong: methodology, visualization, writing—review and editing. Changhong Miao: supervision, funding acquisition, writing—review and editing. Christopher J. O’Bryan: conceptualization, methodology, supervision, writing—review and editing.

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Zunyi Xie or Miao Li.

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Ding, N., Xie, Z., Wang, X. et al. Freshwater biodiversity impacts of global hydropower dams.
Commun Earth Environ (2026). https://doi.org/10.1038/s43247-026-03263-y

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