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Applications de données génétiques pour améliorer la gestion et la conservation des poissons de rivière et de leurs habitats
Author(s) -
Scribner Kim T.,
Lowe Winsor H.,
Landguth Erin,
Luikart Gordon,
Infante Dana M.,
Whelan Gary E.,
Muhlfeld Clint C.
Publication year - 2016
Publication title -
fisheries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.725
H-Index - 79
eISSN - 1548-8446
pISSN - 0363-2415
DOI - 10.1080/03632415.2016.1150838
Subject(s) - biodiversity , temporal scales , ecology , habitat , range (aeronautics) , disturbance (geology) , predictability , population , genetic diversity , environmental resource management , geography , environmental science , biology , paleontology , materials science , physics , demography , quantum mechanics , sociology , composite material
Environmental variation and landscape features affect ecological processes in fluvial systems; however, assessing effects at management‐relevant temporal and spatial scales is challenging. Genetic data can be used with landscape models and traditional ecological assessment data to identify biodiversity hotspots, predict ecosystem responses to anthropogenic effects, and detect impairments to underlying processes. We show that by combining taxonomic, demographic, and genetic data of species in complex riverscapes, managers can better understand the spatial and temporal scales over which environmental processes and disturbance influence biodiversity. We describe how population genetic models using empirical or simulated genetic data quantify effects of environmental processes affecting species diversity and distribution. Our summary shows that aquatic assessment initiatives that use standardized data sets to direct management actions can benefit from integration of genetic data to improve the predictability of disturbance‐response relationships of river fishes and their habitats over a broad range of spatial and temporal scales.