Habitat destruction is one of the greatest threats to biodiversity worldwide, yet the effects of habitat loss and fragmentation on genetic diversity remain unclear. Tak has coauthored a new study published in Biological Conservation that provides new insights on this topic, using mathematical analyses and simulations of population genetic models. The study was led by Qian Tang, who is a Senior Research Fellow from Frank Rheindt’s Avian Evolution Lab at NUS.

The study found that for model bird species with different dispersal abilities, the amount of habitat lost had greater negative effects on population-level genetic diversity than did the degree of habitat fragmentation over timescales of a few hundred years. This was because the amount of habitat lost had the biggest negative impact on population sizes, which led to increases in genetic drift. The loss of genetic diversity manifested itself slowly over several decades, due to genetic drift acting slowly to remove alleles at the population level. This time lag provided a window of opportunity to rebuild populations and reduce the genetic extinction debt. However, loss of genetic diversity occurred more quickly at the subpopulation level due to spatial isolation of individuals and associated inbreeding, which accelerated loss of alleles in subpopulations via genetic drift. Species with higher dispersal abilities were more affected by habitat loss and fragmentation because they were more likely to disperse to areas with unsuitable habitat.  

The study also used modelling to examine a case study of how habitat destruction reduced genetic diversity in populations of malleefowl (Leipoa ocellata) in South Australia. The empirical trends in genetic diversity under different levels of habitat loss and fragmentation broadly matched those found for the model bird species. In addition, the modelling exercise revealed that small sample sizes blurred the effects of habitat loss and fragmentation, suggesting that caution should be taken when interpreting results from empirical studies with sparse sampling.