An international consortium, whose members include INRAE, Claude Bernard Lyon 1 University, and the Occitania Conservatory for Natural Spaces, designed these indicators and evaluated the broad-scale feasibility of their implementation across 9 countries with data for over 900 species. Published in Ecology Letters, the consortium’s results show that the two indicators are quick and affordable to estimate. Among the species assessed, 58% have no populations large enough to maintain genetic diversity, meaning the long-term viability of all their populations is at risk. Starting in 2026, the framework’s 196 signatories will need to use these indicators when reporting on their efforts to conserve genetic diversity. To facilitate indicator adoption, informational workshops will be organised in France in collaboration with local and national stakeholders involved in biodiversity management.
Preserving and restoring biodiversity requires characterising and conserving species genetic biodiversity. Indeed, insufficient levels of genetic diversity can lead to species decline and, ultimately, extinction. Adopted in 2022, the Kunming-Montreal Global Biodiversity Framework (GBF) is a UN Convention of Biological Diversity (CBD) strategy. It is the first of the latter to focus on protecting the genetic diversity of all wild and domesticated species, with a view to ensuring their long-term viability. Starting in 2026, the GBF’s 196 signatories, including France and the EU, will have to submit progress reports on their efforts to conserve species genetic diversity. To facilitate this task, an international scientific consortium has developed two genetic diversity indicators that can be estimated using population-level data1, which may or may not be based on DNA. These indicators were evaluated via peer review and were adopted for use by the GBF. To evaluate the feasibility of employing these indicators with populations of wild species, researchers carried out a broad-scale test in nine countries with a range of biodiversity levels and socioeconomic conditions: Australia, Belgium, Colombia, France, Japan, Mexico, South Africa, Sweden, and the US.
Exploiting existing population-level data
All living species comprise one or more geographically distinct […]