Assesses genetic diversity indicators in South African mammals, suggesting effective monitoring strategies for conservation.
Parties to the Convention on Biological Diversity are required to report on progress towards the Kunming–Montreal Global Biodiversity Framework (KMGBF), which for the first time includes two population genetic indicators to track the maintenance of populations and their effective population size, addressing Goal A (reducing threats to biodiversity) and Target 4 (halting extinctions and safeguarding genetic diversity). Operationalising these indicators at national scale, particularly for complete taxonomic groups, remains challenging. Here, we present the first comprehensive, national-scale assessment of these genetic indicators for all South African mammals ( n = 320 taxa). Leveraging regional Red Listing processes, published and non-public datasets, and expert elicitation, we conducted 320 genetic assessments, achieving coverage of 96% for the Populations Maintained indicator and 45% for the Ne 500 indicator. Nationally, most mammal populations are maintained (∼98%), and ∼ 75% exceed the Ne 500 threshold, indicating generally strong genetic status. However, disaggregated analyses based on threat status revealed substantial heterogeneity, with some Least Concern, Vulnerable and Near Threatened taxa having low Ne 500 values, highlighting populations at risk of undetected genetic erosion. Differences among taxonomic orders likely reflect life-history traits, population structure, and management contexts. Accounting for transboundary populations increased Ne estimates, highlighting the importance of biologically meaningful population delineation. These findings demonstrate that broad taxonomic coverage, structured data mobilization, and integration with existing assessment frameworks enable practical, policy-relevant genetic monitoring. Our study provides a scalable approach for operationalising genetic indicators, informing conservation prioritisation, and supporting national commitments under the KMGBF.
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Silva et al. (2026) studied this question.
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