Comparative landscape genomics has arrived with a splash

Author:

Riginos Cynthia12ORCID,Jahnke Marlene1ORCID

Affiliation:

1. Department of Marine Sciences – Tjärnö Marine Laboratory University of Gothenburg Strömstad Sweden

2. School of the Environment The University of Queensland Brisbane Queensland Australia

Abstract

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.

Funder

Svenska Forskningsrådet Formas

Publisher

Wiley

Subject

Genetics,Ecology, Evolution, Behavior and Systematics

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