A data-driven approach for the assessment of proxy-based genetic diversity indicators

Safeguarding genetic diversity is a key objective of the Kunming–Montreal Global Biodiversity Framework. How to assess genetic diversity indicators in a way that supports reliable and efficient long-term monitoring remains an open challenge, as existing approaches often depend on manual species selection and expert judgment. Here, we present an automated, data-driven approach to infer the two genetic diversity indicators under Headline Indicator A.4 of the Convention on Biological Diversity (CBD): the proportion of populations with effective population size (N_e) over 500 (N_e500) and the proportion of populations maintained (PM) across species. Our approach integrates national species occurrence records for the PM indicator and species density estimates from long-term national species and habitat monitoring programs for the N_e500 indicator. Species are selected using a rarefaction-based assessment of data quantity and spatial distribution, and populations are inferred using a spatial clustering approach. To assess the N_e500 indicator, we estimate suitable area for each population from land-cover data and census population size (N_c) by applying species-specific density estimates. N_e is then inferred using taxon-specific N_e/N_c ratios. The PM indicator is assessed by comparing the spatial distribution of contemporary populations with historical data to estimate population losses over time. We applied our newly developed approach to Swiss biodiversity data to test its feasibility and scalability for national proxy-based genetic diversity indicator assessment. Of 23,274 species with occurrence data, 3,154 (13.5%) had sufficient data to assess PM. We estimated PM to be 0.6 relative to the period before 2000. N_e500 was assessed for 1,123 species, with an estimate of 0.8 for the period 2011–2020. We further compared our proxy-based indicators with DNA-based indicators for five species (Dianthus carthusianorum, Emberiza citrinella, Epidalea calamita, Eriophorum vaginatum, Melitaea diamina) from whole-genome sequencing data. DNA-based N_e and N_e500 indicator values differed substantially from proxy-based estimates and provided more refined insights into N_e changes over the past century than proxy-based ones. In contrast, the proxy-based approach enabled rapid, affordable, broad-scale assessment of genetic indicators. We advocate combining DNA- and proxy-based genetic diversity assessments for effective monitoring to safeguard ecosystem resilience and species’ adaptive potential.