in

Halting genetic diversity loss, from local to international action and policy


Abstract

Within-population genetic diversity underpins wild population resilience and in turn species and ecosystem resilience. The rapidly accelerating biodiversity crisis is motivating the use of both legacy and new datasets, from molecular data and ecological proxies, to inform genetic management and policy. In this Review, we synthesize examples of the integration of genetic principles across data, management and policy scales and illustrate how emerging strategies can halt the erosion of genetic diversity. Biodiversity conservation science increasingly invokes large, heterogeneous, aggregate datasets to identify eco-evolutionary processes that drive change as well as set priorities for policymakers and land managers. Deploying this knowledge to address issues that erode within-population genetic resilience is essential to biodiversity conservation. With careful appreciation of population genetic principles, all available data, from DNA-based studies to ecosystem monitoring, can be recruited towards comprehensive conservation genetics, supporting action across levels of governance. A critical mass of highly diverse datasets and knowledge types is increasingly contributing to legislation, policy and guidelines to monitor genetic processes in nature and, ultimately, protect the richness and resilience of biodiversity.

Access through your institution

Buy or subscribe

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

Access options

Access through your institution

Buy this article

USD 39.95

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

Fig. 1: Global patterns of temporal genetic diversity change across realms, threats and conservation actions.
The alternative text for this image may have been generated using AI.
Fig. 2: The genetic thinking concept and its application to a real-world case study of the Tasmanian devil.
The alternative text for this image may have been generated using AI.
Fig. 3: Genetic, demographic and ecological processes reciprocally influence each other to shape levels of biodiversity.
The alternative text for this image may have been generated using AI.
Fig. 4: Estimating genetic diversity parameters.
The alternative text for this image may have been generated using AI.
Fig. 5: Governance levels and implementation mechanisms for conserving genetic diversity.
The alternative text for this image may have been generated using AI.

Similar content being viewed by others

Global meta-analysis shows action is needed to halt genetic diversity loss

Genome engineering in biodiversity conservation and restoration

Monitoring of species’ genetic diversity in Europe varies greatly and overlooks potential climate change impacts

References

  1. Des Roches, S., Pendleton, L. H., Shapiro, B. & Palkovacs, E. P. Conserving intraspecific variation for nature’s contributions to people. Nat. Ecol. Evol. 5, 574–582 (2021).

    Article 

    Google Scholar 

  2. Frankham, R. Genetics and extinction. Biol. Conserv. 126, 131–140 (2005).

    Article 

    Google Scholar 

  3. Exposito-Alonso, M. et al. Genetic diversity loss in the Anthropocene. Science 377, 1431–1435 (2022).

    Article 
    CAS 

    Google Scholar 

  4. Shaw, R. E. et al. Global meta-analysis shows action is needed to halt genetic diversity loss. Nature 638, 704–710 (2025).

    Article 
    CAS 

    Google Scholar 

  5. Leigh, D. M., Hendry, A. P., Vázquez-Domínguez, E. & Friesen, V. L. Estimated six per cent loss of genetic variation in wild populations since the industrial revolution. Evol. Appl. 12, 1505–1512 (2019).

    Article 

    Google Scholar 

  6. Frankel, O. H. Genetic conservation: our evolutionary responsibility. Genetics 78, 53–65 (1974).

    Article 
    CAS 

    Google Scholar 

  7. Franklin, I. R. in Conservation Biology: An Evolutionary-Ecological Perspective (eds Soule, M. E. and Wilcox, B. A.) 135–149 (Sinauer, 1980).

  8. Frankel, O. H. & Soulé, M. E. Conservation and Evolution (Cambridge Univ. Press, 1981).

  9. Neve, P., Vila-Aiub, M. & Roux, F. Evolutionary-thinking in agricultural weed management. New Phytol. 184, 783–793 (2009).

    Article 

    Google Scholar 

  10. Sgrò, C. M., Lowe, A. J. & Hoffmann, A. A. Building evolutionary resilience for conserving biodiversity under climate change. Evol. Appl. 4, 326–337 (2010).

    Article 

    Google Scholar 

  11. Ramsay, M., Brunner, H. G. & Djikeng, A. Leveraging genomic diversity to promote human and animal health. Commun. Biol. 2, 463 (2019).

    Article 

    Google Scholar 

  12. Laikre, L. et al. Post-2020 goals overlook genetic diversity. Science 367, 1083–1085 (2020).

    Article 

    Google Scholar 

  13. Taft, H. R. et al. Research–management partnerships: an opportunity to integrate genetics in conservation actions. Conserv. Sci. Pract. 2, e218 (2020).

    Article 

    Google Scholar 

  14. Taylor, H. R., Dussex, N. & van Heezik, Y. Bridging the conservation genetics gap by identifying barriers to implementation for conservation practitioners. Glob. Ecol. Conserv. 10, 231–242 (2017).

    Google Scholar 

  15. Torres-Florez, J. P. et al. The coming of age of conservation genetics in Latin America: what has been achieved and what needs to be done. Conserv. Genet. 19, 1–15 (2018).

    Article 
    CAS 

    Google Scholar 

  16. Bertola, L. D. et al. A pragmatic approach for integrating molecular tools into biodiversity conservation. Conserv. Sci. Pract. 6, e13053 (2024).

    Article 

    Google Scholar 

  17. Kershaw, F. et al. The coalition for conservation genetics – working across organizations to build capacity and achieve change in policy and practice. Conserv. Sci. Pract. 4, e12635 (2022).

    Article 

    Google Scholar 

  18. Frankham, R. et al. A Practical Guide for Genetic Management of Fragmented Animal and Plant Populations (Oxford Univ. Press, 2019).

  19. Schwartz, M. K., Luikart, G. & Waples, R. S. Genetic monitoring as a promising tool for conservation and management. Trends Ecol. Evol. 22, 25–33 (2007).

    Article 

    Google Scholar 

  20. Hvilsom, C. et al. Selecting Species and Populations for Monitoring of Genetic Diversity (IUCN, 2022).

  21. Manel, S. & Holderegger, R. Ten years of landscape genetics. Trends Ecol. Evol. 28, 614–621 (2013).

    Article 

    Google Scholar 

  22. Santiago, E. et al. Recent demographic history inferred by high-resolution analysis of linkage disequilibrium. Mol. Biol. Evol. 37, 3642–3653 (2020).

    Article 
    CAS 

    Google Scholar 

  23. Hoban, S. et al. Global genetic diversity status and trends: towards a suite of essential biodiversity variables (EBVs) for genetic composition. Biol. Rev. 97, 1511–1538 (2022).

    Article 

    Google Scholar 

  24. Ashley, M. V. et al. Evolutionarily enlightened management. Biol. Conserv. 111, 115–123 (2003).

    Article 

    Google Scholar 

  25. Cook, C. N. & Sgrò, C. M. Aligning science and policy to achieve evolutionarily enlightened conservation. Conserv. Biol. 31, 501–512 (2017).

    Article 

    Google Scholar 

  26. Hoban, S. et al. Global commitments to conserving and monitoring genetic diversity are now necessary and feasible. BioScience 71, 964–976 (2021).

    Article 

    Google Scholar 

  27. Hoban, S. et al. DNA-based studies and genetic diversity indicator assessments are complementary approaches to conserving evolutionary potential. Conserv. Genet. 25, 1147–1153 (2024).

    Article 

    Google Scholar 

  28. Schmidt, T. L., Thia, J. A. & Hoffmann, A. A. How can genomics help or hinder wildlife conservation? Annu. Rev. Anim. Biosci. 12, 45–68 (2024).

    Article 

    Google Scholar 

  29. Gutierrez, R. J. & Carey, A. B. (eds). Ecology and Management of the Spotted Owl in the Pacific Northwest (U.S. Department of Agriculture, Forest Service, 1985).

  30. Hung, T. H. et al. Range-wide differential adaptation and genomic offset in critically endangered Asian rosewoods. Proc. Natl Acad. Sci. USA 120, e2301603120 (2023).

    Article 
    CAS 

    Google Scholar 

  31. Hartvig, I. et al. Conservation genetics of the critically endangered Siamese rosewood (Dalbergia cochinchinensis): recommendations for management and sustainable use. Conserv. Genet. 21, 677–692 (2020).

    Article 
    CAS 

    Google Scholar 

  32. Hedrick, P. W. Genetics of Populations 2nd edn (Jones and Bartlett Publishers, 2000).

  33. Stange, M., Barrett, R. D. H. & Hendry, A. P. The importance of genomic variation for biodiversity, ecosystems and people. Nat. Rev. Genet. 22, 89–105 (2021).

    Article 
    CAS 

    Google Scholar 

  34. Pelletier, F., Garant, D. & Hendry, A. P. Eco-evolutionary dynamics. Philos. Trans. R. Soc. B Biol. Sci. 364, 1483–1489 (2009).

    Article 
    CAS 

    Google Scholar 

  35. Frankham, R., Ballou, J. D. & Briscoe, D. A. Introduction to Conservation Genetics 2nd edn (Cambridge Univ. Press, 2010).

  36. Pemberton, D. in Saving the Tasmanian Devil: Recovery Through Science-Based Management (eds C. J. Hogg et al.) 11–22 (CSIRO Publishing, 2019).

  37. Hogg, C. J. et al. (eds) Saving the Tasmanian Devil: Recovery Through Science-Based Management (CSIRO Publishing, 2019).

  38. Schraven, A. L. et al. Temporal changes in Tasmanian devil genetic diversity at sites with and without supplementation. Mol. Ecol. 34, e17671 (2025).

    Article 

    Google Scholar 

  39. Shaw, R. E. et al. Building meaningful collaboration in conservation genetics and genomics. Conserv. Genet. 25, 1127–1145 (2024).

    Article 

    Google Scholar 

  40. Alter, S. E., Rynes, E. & Palumbi, S. R. DNA evidence for historic population size and past ecosystem impacts of gray whales. Proc. Natl Acad. Sci. USA 104, 15162–15167 (2007).

    Article 
    CAS 

    Google Scholar 

  41. Gurgel, C. F. D., Camacho, O., Minne, A. J. P., Wernberg, T. & Coleman, M. A. Marine heatwave drives cryptic loss of genetic diversity in underwater forests. Curr. Biol. 30, 1199–1206.e2 (2020).

    Article 
    CAS 

    Google Scholar 

  42. Kleinman-Ruiz, D. et al. Genetic evaluation of the Iberian lynx ex situ conservation programme. Heredity 123, 647–661 (2019).

    Article 

    Google Scholar 

  43. Lan, T. et al. Revealing extensive inbreeding and less efficient purging of deleterious mutations in wild Amur tigers in China. J. Genet. Genomics 52, 641–649 (2025).

    Article 

    Google Scholar 

  44. Zarri, L. J., Palkovacs, E. P., Post, D. M., Therkildsen, N. O. & Flecker, A. S. The evolutionary consequences of dams and other barriers for riverine fishes. BioScience 72, 431–448 (2022).

    Article 

    Google Scholar 

  45. Halford, G. et al. Genomic monitoring of a reintroduced butterfly uncovers contrasting founder lineage survival. Evol. Appl. 18, e70074 (2025).

    Article 

    Google Scholar 

  46. Ritchie, A. L. & Krauss, S. L. A genetic assessment of ecological restoration success in Banksia attenuata. Restor. Ecol. 20, 441–449 (2012).

    Article 

    Google Scholar 

  47. Leigh, D. M. et al. Opportunities and challenges of macrogenetic studies. Nat. Rev. Genet. 22, 791–807 (2021).

    Article 
    CAS 

    Google Scholar 

  48. Hoban, S. et al. Too simple, too complex, or just right? Advantages, challenges, and guidance for indicators of genetic diversity. BioScience 74, 269–280 (2024).

    Article 

    Google Scholar 

  49. Mastretta-Yanes, A. et al. Multinational evaluation of genetic diversity indicators for the Kunming-Montreal Global Biodiversity Framework. Ecol. Lett. 27, e14461 (2024).

    Article 

    Google Scholar 

  50. Miller, B. P. et al. A framework for the practical science necessary to restore sustainable, resilient, and biodiverse ecosystems. Restor. Ecol. 25, 605–617 (2017).

    Article 

    Google Scholar 

  51. Waples, R. S. The idiot’s guide to effective population size. Mol. Ecol. 34, e17670 (2025).

    Article 

    Google Scholar 

  52. Wright, S. Evolution in Mendelian populations. Genetics 16, 97–159 (1931).

    Article 
    CAS 

    Google Scholar 

  53. Frankham, R. Effective population size/adult population size ratios in wildlife: a review. Genet. Res. 66, 95–107 (1995).

    Article 

    Google Scholar 

  54. Mergeay, J. et al. Estimating the effective size of European wolf populations. Evol. Appl. 17, e70021 (2024).

    Article 

    Google Scholar 

  55. Ardren, W. R. & Kapuscinski, A. R. Demographic and genetic estimates of effective population size (Ne) reveals genetic compensation in steelhead trout. Mol. Ecol. 12, 35–49 (2003).

    Article 
    CAS 

    Google Scholar 

  56. Schuman, M. C. et al., Monitor indicators of genetic diversity from space using Earth observation data. Preprint at EcoEvoRxiv https://doi.org/10.32942/X2ZP53 (2023).

  57. Güntsch, A. et al. National biodiversity data infrastructures: ten essential functions for science, policy, and practice. BioScience 75, 139–151 (2025).

    Article 

    Google Scholar 

  58. Callaghan, C. T. et al. Three frontiers for the future of biodiversity research using citizen science data. BioScience 71, 55–63 (2020).

    Google Scholar 

  59. Rayne, A. et al. Weaving place-based knowledge for culturally significant species in the age of genomics: looking to the past to navigate the future. Evol. Appl. 15, 751–772 (2022).

    Article 

    Google Scholar 

  60. Lalueza-Fox, C. Museomics. Curr. Biol. 32, R1214–R1215 (2022).

    Article 
    CAS 

    Google Scholar 

  61. Card, D. C., Shapiro, B., Giribet, G., Moritz, C. & Edwards, S. V. Museum genomics. Annu. Rev. Genet. 55, 633–659 (2021).

    Article 
    CAS 

    Google Scholar 

  62. Clark, R. D. et al. The practice and promise of temporal genomics for measuring evolutionary responses to global change. Mol. Ecol. Resour. 25, e13789 (2025).

    Article 
    CAS 

    Google Scholar 

  63. Jackson, H. A. et al. Genomic erosion in a demographically recovered bird species during conservation rescue. Conserv. Biol. 36, e13918 (2022).

    Article 

    Google Scholar 

  64. Frankham, R. Suggested improvements to proposed genetic indicator for CBD. Conserv. Genet. 22, 531–532 (2021).

    Article 

    Google Scholar 

  65. Koricheva, J., Gurevitch, J. & Mengersen, K. Handbook of Meta-Analysis in Ecology and Evolution (Princeton Univ. Press, 2013).

  66. Senior, A. M. et al. Heterogeneity in ecological and evolutionary meta-analyses: its magnitude and implications. Ecology 97, 3293–3299 (2016).

    Article 

    Google Scholar 

  67. Noble, D. W. A., Lagisz, M., O’Dea, R. E. & Nakagawa, S. Nonindependence and sensitivity analyses in ecological and evolutionary meta-analyses. Mol. Ecol. 26, 2410–2425 (2017).

    Article 

    Google Scholar 

  68. Lewis, S. & Clarke, M. Forest plots: trying to see the wood and the trees. BMJ 322, 1479–1480 (2001).

    Article 
    CAS 

    Google Scholar 

  69. Nakagawa, S. et al. Methods for testing publication bias in ecological and evolutionary meta-analyses. Methods Ecol. Evol. 13, 4–21 (2022).

    Article 

    Google Scholar 

  70. Caldwell, I. R. et al. Global trends and biases in biodiversity conservation research. Cell Rep. Sustain. 1, 100082 (2024).

    Google Scholar 

  71. Paz‐Vinas, I. et al. Sparse genetic data limit biodiversity assessments in protected areas globally. Front. Ecol. Environ. 23, e2867 (2025).

    Article 

    Google Scholar 

  72. dos Santos, J. W. et al. Drivers of taxonomic bias in conservation research: a global analysis of terrestrial mammals. Anim. Conserv. 23, 679–688 (2020).

    Article 

    Google Scholar 

  73. Hickisch, R. et al. Effects of publication bias on conservation planning. Conserv. Biol. 33, 1151–1163 (2019).

    Article 
    CAS 

    Google Scholar 

  74. Sayers, E. W. et al. GenBank 2025 update. Nucleic Acids Res. 53, D56–D61 (2024).

    Article 

    Google Scholar 

  75. Blanchet, S., Prunier, J. G. & De Kort, H. Time to go bigger: emerging patterns in macrogenetics. Trends Genet. 33, 579–580 (2017).

    Article 
    CAS 

    Google Scholar 

  76. Leigh, D. M. et al. Nat. Ecol. Evol. 8, 1224–1232 (2024).

  77. Forsdick, N. J. et al. Journeying towards best practice data management in biodiversity genomics. Mol. Ecol. Resour. 25, e13880 (2025).

    Article 
    CAS 

    Google Scholar 

  78. Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).

    Article 

    Google Scholar 

  79. Romiguier, J. et al. Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature 515, 261–263 (2014).

    Article 
    CAS 

    Google Scholar 

  80. Schmidt, C., Hoban, S. & Jetz, W. Conservation macrogenetics: harnessing genetic data to meet conservation commitments. Trends Genet. 39, 816–829 (2023).

    Article 
    CAS 

    Google Scholar 

  81. Chichorro, F. et al. Trait-based prediction of extinction risk across terrestrial taxa. Biol. Conserv. 274, 109738 (2022).

    Article 

    Google Scholar 

  82. Karachaliou, E., Schmidt, C., de Greef, E., Docker, M. F. & Garroway, C. J. Urbanisation is associated with reduced genetic diversity in marine fish populations. Mol. Ecol. 34, e17711 (2025).

    Article 

    Google Scholar 

  83. Baranzelli, M. C., Cosacov, A., Sede, S. M., Nicola, M. V. & Sérsic, A. N. Anthropocene refugia in Patagonia: a macrogenetic approach to safeguarding the biodiversity of flowering plants. Biol. Conserv. 268, 109492 (2022).

    Article 

    Google Scholar 

  84. Stevenson, S. L. et al. Matching biodiversity indicators to policy needs. Conserv. Biol. 35, 522–532 (2021).

    Article 

    Google Scholar 

  85. Affinito, F., Williams, J. M., Campbell, J. E., Londono, M. C. & Gonzalez, A. Progress in developing and operationalizing the Monitoring Framework of the Global Biodiversity Framework. Nat. Ecol. Evol. 8, 2163–2171 (2024).

    Article 

    Google Scholar 

  86. Green, E. J. et al. Relating characteristics of global biodiversity targets to reported progress. Conserv. Biol. 33, 1360–1369 (2019).

    Article 

    Google Scholar 

  87. Khoury, C. K. et al. Comprehensiveness of conservation of useful wild plants: an operational indicator for biodiversity and sustainable development targets. Ecol. Indic. 98, 420–429 (2019).

    Article 

    Google Scholar 

  88. Convention on Biological Diversity. Decision adopted by the Conference of the Parties to the Convention on Biological Diversity: 15/5 monitoring framework for the Kunming-Montreal Global Biodiversity Framework. CBD https://www.cbd.int/doc/decisions/cop-15/cop-15-dec-05-en.pdf (2022).

  89. Convention on Biological Diversity. Decision adopted by the Conference of the Parties to the Convention on Biological Diversity: 15/4 Kunming-Montreal Global Biodiversity Framework. CBD https://www.cbd.int/doc/decisions/cop-15/cop-15-dec-04-en.pdf (2022).

  90. Food and Agriculture Organization of the United Nations. The State of the World’s Biodiversity for Food and Agriculture (FAO, 2019).

  91. IPBES Secretariat. Summary for Policymakers of the Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES, 2019).

  92. CITES. Seventy-seventh meeting of the Standing Committee, CITES Strategic Vision. CITES https://cites.org/sites/default/files/documents/SC/77/agenda/E-SC77-16.pdf (2023).

  93. da Silva, J. M. et al. Conserving genetic and genomic diversity in accordance with the Global Biodiversity Framework. Annu. Rev. Anim. Biosci. 14, 399–428 (2025).

    Article 

    Google Scholar 

  94. International Union for Conservation of Nature. Global Species Action Plan: Supporting Implementation of the Kunming-Montreal Global Biodiversity Framework (IUCN, 2023).

  95. McLaughlin, C. M., Hinshaw, C., Sandoval-Arango, S., Zavala-Paez, M. & Hamilton, J. A. Redlisting genetics: towards inclusion of genetic data in IUCN Red List assessments. Conserv. Genet. 26, 213–223 (2025).

    Article 

    Google Scholar 

  96. Convention on Biological Diversity. On-line reporting tool for NBSAPs and national reports. CBD https://ort.cbd.int/knowledge-base (2025).

  97. Hoban, S. et al. How can biodiversity strategy and action plans incorporate genetic diversity and align with global commitments? BioScience 75, 47–60 (2025).

    Article 

    Google Scholar 

  98. Pierson, J. C. et al. Genetic factors in threatened species recovery plans on three continents. Front. Ecol. Env. 14, 433–440 (2016).

    Article 

    Google Scholar 

  99. Fisheries and Aquaculture Management Division. Aquaculture Development 3. Genetic Resource Management: FAO Technical Guidelines for Responsible Fisheries (FAO, 2008).

  100. Shapiro, B. I. et al. Ethiopia Livestock Master Plan: Roadmaps for Growth and Transformation. A Contribution to the Growth and Transformation Plan II (2015-2020) (International Livestock Research Institute, 2015).

  101. Bell-James, J. & Watson, J. E. M. Ambitions in national plans do not yet match bold international protection and restoration commitments. Nat. Ecol. Evol. 9, 417–424 (2025).

    Article 

    Google Scholar 

  102. Pearman, P. B. et al. Monitoring of species’ genetic diversity in Europe varies greatly and overlooks potential climate change impacts. Nat. Ecol. Evol. 8, 267–281 (2024).

    Article 

    Google Scholar 

  103. Hollingsworth, P. M. et al. Scotland’s Biodiversity Progress to 2020 Aichi Targets: Aichi Target 13 – Genetic Diversity Maintained – Supplementary Report 2020 (Scottish Natural Heritage, 2020).

  104. Fischer, M. C. et al. Pilotstudie für ein Monitoring der genetischen Vielfalt in der Schweiz. ETH Zurich Institute of Integrative Biology, https://www.research-collection.ethz.ch/handle/20.500.11850/661655 (2023).

  105. Willi, Y. et al. Conservation genetics as a management tool: the five best-supported paradigms to assist the management of threatened species. Proc. Natl Acad. Sci. USA 119, e2105076119 (2021).

    Article 

    Google Scholar 

  106. Waples, R. S. Definition of ‘species’ under the Endangered Species Act: application to Pacific salmon. noaa.gov https://repository.library.noaa.gov/view/noaa/48852 (1991).

  107. Wild Salmon Center. In California, a big step forward for spring Chinook. wildsalmoncenter.org https://wildsalmoncenter.org/2021/06/24/in-california-a-big-step-forward-for-spring-chinook/ (2015).

  108. Shaffer, H. B. et al. Landscape genomics to enable conservation actions: the California conservation genomics project. J. Hered. 113, 577–588 (2022).

    Article 

    Google Scholar 

  109. Bradby, K., Keesing, A. & Wardell-Johnson, G. Gondwana link: connecting people, landscapes, and livelihoods across southwestern Australia. Restor. Ecol. 24, 827–835 (2016).

    Article 

    Google Scholar 

  110. Cristina Carrillo Hernández, A., Ortega-Argueta, A., María Gama Campillo, L., Bello-Baltazar, E. & Rioja Nieto, R. Effectiveness of management of the Mesoamerican Biological Corridor in Mexico. Landsc. Urban Plan. 226, 104504 (2022).

    Article 

    Google Scholar 

  111. Aryal, A. et al. Biological diversity and management regimes of the Northern Barandabhar Forest Corridor: an essential habitat for ecological connectivity in Nepal. Trop. Conserv. Sci. 5, 38–49 (2012).

    Article 

    Google Scholar 

  112. Hilty, J. A., Chester, C. C., Wright, P. A. & Zenkewich, K., Uniting hearts and lands: advancing conservation and restoration across the Yellowstone to Yukon region. Front. Conserv. Sci. 4, 1264460 (2024).

    Article 

    Google Scholar 

  113. Millar, M. A. et al. Evaluating restoration outcomes through assessment of pollen dispersal, mating system, and genetic diversity. Restor. Ecol. 29, e13335 (2021).

    Article 

    Google Scholar 

  114. Krauss, S. L. & Anthony, J. M. The potential impact of mining on population genetic variation in the Banded Ironstone Formation endemic Tetratheca erubescens (Elaeocarpaceae). Aust. J. Bot. 67, 172–182 (2019).

    Article 
    CAS 

    Google Scholar 

  115. Elliott, C. P., Tomlinson, S., Lewandrowski, W. & Miller, B. P. Species distribution and habitat attributes guide translocation planning of a threatened short-range endemic plant. Glob. Ecol. Conserv. 51, e02915 (2024).

    Google Scholar 

  116. Jahner, J. P. et al. The genetic legacy of 50 years of desert bighorn sheep translocations. Evol. Appl. 12, 198–213 (2019).

    Article 

    Google Scholar 

  117. Rick, K. et al. Population genomic diversity and structure in the golden bandicoot: a history of isolation, extirpation, and conservation. Heredity 131, 374–386 (2023).

    Article 

    Google Scholar 

  118. Colding, J., Giusti, M., Haga, A., Wallhagen, M. & Barthel, S. Enabling relationships with nature in cities. Sustainability 12, 4394 (2020).

    Article 

    Google Scholar 

  119. Noreen, A. M. E., Niissalo, M. A., Lum, S. K. Y. & Webb, E. L. Persistence of long-distance, insect-mediated pollen movement for a tropical canopy tree species in remnant forest patches in an urban landscape. Heredity 117, 472–480 (2016).

    Article 
    CAS 

    Google Scholar 

  120. Finnerty, P. B. et al. Urban rewilding to combat global biodiversity decline. BioScience 75, 545–558 (2025).

    Article 

    Google Scholar 

  121. O’Garra, T., Kuz, V., Deneault, A., Orr, C. & Chan, S. Early engagement and co-benefits strengthen cities’ climate commitments. Nat. Cities 1, 315–324 (2024).

    Article 

    Google Scholar 

  122. UN-HABITAT. Supporting local action for biodiversity: the role of national governments. United Nations Human Settlements Programme (UN-HABITAT). unhabitat.org https://unhabitat.org/supporting-local-action-for-biodiversity (2010).

  123. Thomas, I. G. Environmental policy and local government in Australia. Local Environ. 15, 121–136 (2010).

    Article 

    Google Scholar 

  124. Daniel, P., Doak, D. F. & Steinberg, P. The role of local government in the conservation of rare species. Conserv. Biol. 10, 1538–1548 (1996).

    Article 

    Google Scholar 

  125. Pärli, R. et al. Developing a monitoring program of genetic diversity: what do stakeholders say? Conserv. Genet. 22, 673–684 (2021).

    Article 

    Google Scholar 

  126. Elliot, V., Jonäll, K., Paananen, M., Bebbington, J. & Michelon, G. Biodiversity reporting: standardization, materiality, and assurance. Curr. Opin. Environ. Sustain. 68, 101435 (2024).

    Article 

    Google Scholar 

  127. Rainey, H. J. et al. A review of corporate goals of no net loss and net positive impact on biodiversity. Oryx 49, 232–238 (2015).

    Article 

    Google Scholar 

  128. Sonter, L. J., Ali, S. H. & Watson, J. E. M. Mining and biodiversity: key issues and research needs in conservation science. Proc. Biol. Sci. 285, 20181926 (2018).

    Google Scholar 

  129. Chandler, M. et al. Contribution of citizen science towards international biodiversity monitoring. Biol. Conserv. 213, 280–294 (2017).

    Article 

    Google Scholar 

  130. Buckley, S. J. et al. A community-driven captive-breeding and reintroduction program maintains genetic diversity in a threatened freshwater fish. Conserv. Sci. Pract. 6, e13054 (2024).

    Article 

    Google Scholar 

  131. Tyagi, A., Godbole, M., Vanak, A. T. & Ramakrishnan, U. Citizen science facilitates first ever genetic detection of wolf-dog hybridization in Indian savannahs. Ecol. Evol. 13, e10100 (2023).

    Article 

    Google Scholar 

  132. Hawkins, C., Baars, C., Hesterman, H., Hocking, G. & Jones, M. Emerging disease and population decline of an island endemic, the Tasmanian devil Sarcophilus harrisii. Biol. Conserv. 131, 307–324 (2006).

    Article 

    Google Scholar 

  133. Priddel, D., Carlile, N., Humphrey, M., Fellenberg, S. & Hiscox, D. Rediscovery of the ‘extinct’ Lord Howe Island stick-insect (Dryococelus australis (Montrouzier)) (Phasmatodea) and recommendations for its conservation. Biodivers. Conserv. 12, 1391–1403 (2003).

    Article 

    Google Scholar 

  134. Peter, M., Diekötter, T., Höffler, T. & Kremer, K. Biodiversity citizen science: outcomes for the participating citizens. Peopl. Nat. 3, 294–311 (2021).

    Article 

    Google Scholar 

  135. Czyż, E. A. et al. Intraspecific genetic variation of a Fagus sylvatica population in a temperate forest derived from airborne imaging spectroscopy time series. Ecol. Evol. 10, 7419–7430 (2020).

    Article 

    Google Scholar 

  136. Mc Cartney, A. M. et al. Indigenous peoples and local communities as partners in the sequencing of global eukaryotic biodiversity. npj Biodivers. 2, 8 (2023).

    Article 

    Google Scholar 

  137. Hogg, C. J. Translating genomic advances into biodiversity conservation. Nat. Rev. Genet. 25, 362–373 (2024).

    Article 
    CAS 

    Google Scholar 

  138. Griffith, J. et al. BON in a box: an open and collaborative platform for biodiversity monitoring, indicator calculation, and reporting. BioScience 76, 345–358 (2026).

    Article 

    Google Scholar 

  139. Mastretta-Yanes, A. et al. Guideline materials and documentation for the genetic diversity indicators of the monitoring framework for the Kunming-Montreal Global Biodiversity Framework. Biodivers. Inform. 18, 24–27 (2024).

    Article 

    Google Scholar 

  140. Wright, S. The effects of inbreeding and crossbreeding on guinea pigs III: crosses between highly inbred families. Bull. US Dept. Agric. 1121, 1–60 (1922).

    Google Scholar 

  141. Fisher, R. A. The Genetical Theory of Natural Selection (Oxford Univ. Press, 1930).

  142. Fedorca, A. et al. Dealing with the complexity of effective population size in conservation practice. Evol. Appl. 17, e70031 (2024).

    Article 

    Google Scholar 

  143. Kirin, M. et al. Genomic runs of homozygosity record population history and consanguinity. PLoS ONE 5, e13996 (2010).

    Article 

    Google Scholar 

  144. Grossen, C., Guillaume, F., Keller, L. F. & Croll, D. Purging of highly deleterious mutations through severe bottlenecks in Alpine ibex. Nat. Commun. 11, 1001 (2020).

    Article 
    CAS 

    Google Scholar 

  145. Ebenezer, T. E. et al. Africa: sequence 100,000 species to safeguard biodiversity. Nature 603, 388–392 (2022).

    Article 
    CAS 

    Google Scholar 

  146. Vilaça, S. T. et al. Leveraging genomes to support conservation and bioeconomy policies in a megadiverse country. Cell Genom. 4, 100678 (2024).

    Article 

    Google Scholar 

  147. Lawson, L. P. et al. Slow motion extinction: inbreeding, introgression, and loss in the critically endangered mangrove finch (Camarhynchus heliobates). Conserv. Genet. 18, 159–170 (2017).

    Article 

    Google Scholar 

  148. Zarza, E., Reynoso, V. H., Faria, C. M. A. & Emerson, B. C. Introgressive hybridization in a spiny-tailed iguana, Ctenosaura pectinata, and its implications for taxonomy and conservation. PeerJ 7, e6744 (2019).

    Article 

    Google Scholar 

  149. Thomas, N. E., Chadwick, E. A., Bruford, M. W. & Hailer, F. Spatio-temporal changes in effective population size in an expanding metapopulation of Eurasian otters. Evol. Appl. 18, e70067 (2025).

    Article 

    Google Scholar 

  150. Pickup, M. & Young, A. G. Population size, self-incompatibility and genetic rescue in diploid and tetraploid races of Rutidosis leptorrhynchoides (Asteraceae). Heredity 100, 268–274 (2008).

    Article 
    CAS 

    Google Scholar 

  151. Stuart, O. P., Cleave, R., Pearce, K., Magrath, M. J. L. & Mikheyev, A. S. Gene flow stimulates recovery of reproductive fitness in a captive bred insect. Insect Conserv. Divers. 18, 743–756 (2024).

    Article 

    Google Scholar 

  152. Stuart, O. P., Cleave, R., Pearce, K., Magrath, M. J. L. & Mikheyev, A. S. Purging of highly deleterious mutations through an extreme bottleneck. Mol. Biol. Evol. 42, msaf079 (2025).

    Article 
    CAS 

    Google Scholar 

  153. Lundmark, C., Sandström, A., Andersson, K. & Laikre, L. Monitoring the effects of knowledge communication on conservation managers’ perception of genetic biodiversity – a case study from the Baltic Sea. Mar. Policy 99, 223–229 (2019).

    Article 

    Google Scholar 

  154. Buck, M. & Hamilton, C. The Nagoya Protocol on access to genetic resources and the fair and equitable sharing of benefits arising from their utilization to the convention on biological diversity. Rev. Eur. Comp. Int. Environ. Law 20, 47–61 (2011).

    Article 

    Google Scholar 

  155. Carroll, S. R. et al. The CARE principles for Indigenous data governance. Data Sci. J. 19, 43 (2020).

    Article 

    Google Scholar 

  156. Te Aika, B. et al. Aotearoa genomic data repository: an āhuru mōwai for taonga species sequencing data. Mol. Ecol. Resour. 25, e13866 (2025).

    Article 

    Google Scholar 

  157. Dawson, N. M. et al. The role of Indigenous peoples and local communities in effective and equitable conservation. Ecol. Soc. 26, 19 (2021).

    Article 

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed substantially to discussion of the content and contributed to drafting sections of the manuscript. R.E.S., C.P.E., D.J.C., K.M.O. and C.E.G. led the development of display items with feedback from all other authors. R.E.S. and C.E.G. led the compilation of the final draft. All authors reviewed the manuscript before submission.

Corresponding author

Correspondence to
Catherine E. Grueber.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Biodiversity thanks Paul Hohenlohe, Kathrin Theissingerand and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

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

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

Cite this article

Shaw, R.E., Elliott, C.P., Coates, D.J. et al. Halting genetic diversity loss, from local to international action and policy.
Nat. Rev. Biodivers. (2026). https://doi.org/10.1038/s44358-026-00162-0

Download citation

  • Accepted:

  • Published:

  • Version of record:

  • DOI: https://doi.org/10.1038/s44358-026-00162-0


Source: Ecology - nature.com

Cattle-induced homogenization of microbial communities weakens the influence of geochemical gradients in small water bodies

Semi-automated detection of cleaning interactions using supervised machine learning