Leveraging Red List data to estimate genetic diversity indicators: improved workflows to support the GBF

The Kunming-Montreal Global Biodiversity Framework is a milestone because, for the first time, conservation goals come with a clear monitoring system and —also for the first time— incorporate the genetic level. Yet with 23 Targets, 26 headline indicators and more than 300 optional indicators, monitoring burden represents a concern for practitioners. Many indicators share similar raw data or are part of established processes and therefore could, and should, result in more streamlined reporting efforts. However, in practice this potential benefit rarely materialises due to disconnected approaches.This disconnect is exemplified in Target 4: “Halt Species Extinction, Protect Genetic Diversity, and Manage Human-Wildlife Conflicts”, monitored by the headline indicators “A.3 Red list Index”, and “A.4 The proportion of populations within species with an effective population size (Ne) > 500” (“Ne 500” indicator). Providing different but complementary conservation messages, the Red List Index measures extinction risk at the species level, and the Ne 500 indicator measures whether populations within species can maintain their genetic diversity.Both Red List assessment and generation of the Ne 500 indicator (in the absence of genetic data) incorporate population data derived from similar but varied information sources, ranging from scientific papers to the expertise of local knowledge holders. Since Red List assessment is an ongoing, well-established global practice, leveraging the data aggregated through the Red List workflow to generate genetic diversity indicators (GDI), as well as the Red List Index, could not only make monitoring more efficient, but ensure that genetic diversity is no longer overlooked.Here, we demonstrate that since both indicators share population data requirements, indicator generation can be built into existing workflows for Red List assessment, even when considering examples for taxa where population data are often challenging to compile. We suggest a complementary approach to Red List assessment and GDI estimation is possible, straightforward, and offers an excellent opportunity to consolidate reporting against Target 4 of the GBF, improving monitoring and generating novel conservation insights. However, a complementary approach is most practical and encouraged when undertaking global Red List assessment of country endemic species and/or when engaging in national Red List assessment initiatives.