Comparative landscape genomics has arrived with a splash

Comparative methods are central for understanding the distribution of biodiversity. Assessing spatial variation of multiple species can identify biodiversity drivers across landscapes, including on the genetic level. Molecular ecology approaches have expanded in spatial precision, from phylogeography to landscape genetics, as have molecular tools that now allow genome-scale inferences for virtually any organism. These welcome increases in genomic data richness, however, have not been matched by growth in the multispecies dimension, and empirical studies continue to focus predominantly on single species. In this issue of Molecular Ecology, Zbinden et al. (Molecular Ecology, 2022, 32) present a landmark achievement for comparative landscape genomics, surveying an impressive 31 species of fishes, sampled from 75 locations in the White River Basin and genotyping each species for thousands of SNPs. Zbinden et al. (Molecular Ecology, 2022, 32) draw upon the statistical tools of landscape genetics to comprehensively interrogate four hypotheses-that populations of multiple freshwater fish species are isolated by river distance, barriers to dispersal, stream hierarchy or environment. Stream hierarchy overwhelmingly predicts population structure within co-distributed fish species pointing to commonalities among species at the large landscape scale (100s of km). The tight alignment between intraspecific genetic spatial structure and stream hierarchies, moreover, provides clear validation for conservation and fisheries management to use watershed divisions as distinct management units.

Automated summary

Comparative methods are crucial for understanding biodiversity distribution, yet current research primarily focuses on single species. In this study, Zbinden et al. utilized landscape genetics to investigate the landscape genomics of 31 fish species in the White River Basin, revealing the significant impact of stream hierarchy on fish population structure. These findings provide empirical evidence for conservation and fisheries management.