Ecological disturbance influences adaptive divergence despite high gene flow in golden perch (Macquaria ambigua): Implications for management and resilience to climate change

Catherine Attard, Christopher Brauer, Jonathan Sandoval-Castillo, Leanne Faulks, Peter Unmack, Dean Gilligan, Luciano Beheregaray

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Populations that are adaptively divergent but maintain high gene flow may have greater resilience to environmental change as gene flow allows the spread of alleles that have already been tested elsewhere. In addition, populations naturally subjected to ecological disturbance may already hold resilience to future environmental change. Confirming this necessitates ecological genomic studies of high dispersal, generalist species. Here we perform one such study on golden perch (Macquaria ambigua) in the Murray-Darling Basin (MDB), Australia, using a genome-wide SNP data set. The MDB spans across arid to wet and temperate to subtropical environments, with low to high ecological disturbance in the form of low to high hydrological variability. We found high gene flow across the basin and three populations with low neutral differentiation. Genotype–environment association analyses detected adaptive divergence predominantly linked to an arid region with highly variable riverine flow, and candidate loci included functions related to fat storage, stress and molecular or tissue repair. The high connectivity of golden perch in the MDB will likely allow locally adaptive traits in its most arid and hydrologically variable environment to spread and be selected in localities that are predicted to become arid and hydrologically variable in future climates. High connectivity in golden perch is likely due to their generalist life history and efforts of fisheries management. Our study adds to growing evidence of adaptation in the face of gene flow and highlights the importance of considering ecological disturbance and adaptive divergence in biodiversity management.

Original languageEnglish
Pages (from-to)196-215
Number of pages20
JournalMolecular Ecology
Volume27
Issue number1
DOIs
Publication statusPublished - 2018

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