Population density and genetic diversity are positively correlated in wild felids globally

Abstract

AimInsights into the biological and evolutionary traits of species, and their ability to cope with global changes, can be gained by studying genetic diversity within species. A cornerstone hypothesis in evolutionary and conservation biology suggests that genetic diversity decreases with decreasing population size, however, population size is difficult to estimate in threatened species with large distribution ranges, and evidence for this is limited to few species. To address this gap, we tested this hypothesis across multiple closely related species at a global scale using population density which is a more accessible measure.LocationGlobal.Time PeriodContemporary.Major Taxa StudiedWild felids in their natural habitats.MethodsWe obtained data from published estimates of population density assessed via camera trap and within‐population genetic diversity generated from microsatellite markers on 18 felid species across 41 countries from 354 studies. We propose a novel method to standardize population density estimates and to spatially join data using K‐means clustering. Linear mixed‐effect modelling was applied to account for confounding factors such as body mass, generation length and sample size used for the genetic estimates.ResultsWe found a significant positive correlation between population density and genetic diversity, particularly observed heterozygosity and allelic richness. While the confounding factors did not affect the main results, long generation length and large sample size were significantly associated with high genetic diversity. Body mass had no effect on genetic diversity, likely because large‐bodied species were over‐represented in our data sets.Main ConclusionsOur study emphasizes how recent demographic processes shape neutral genetic diversity in threatened and small populations where extinction vortex is a risk. Although caution is needed when interpreting the small population density effect in our findings, our methodological framework shows promising potential to identify which populations require actions to conserve maximal genetic variation.