Abstract
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.
| Translated title of the contribution | Applications of Genetic Data to Improve Management and Conservation of River Fishes and Their Habitats |
|---|---|
| Original language | English |
| Pages (from-to) | 174-188 |
| Number of pages | 15 |
| Journal | Fisheries |
| Volume | 41 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 2 2016 |
Funding
K.S. and D.I. were supported through the Partnership for Ecosystem Research and Management (PERM) program between the Fisheries Division of the Michigan Department of Natural Resources (DNR) and Michigan State University and USFWS Sport Fish Restoration Program funds. G.L., C.C.M., and E.L. were partially supported by a grant from NASA, grant NNX14AC91G, and USGS Northwest Climate Science Center. G.L. was also supported by National Science Foundation (NSF) grant DEB-1258203. W.H.L. was supported by NSF grant DEB-1050459. G.W. was supported by the Michigan DNR Fisheries Division from USFWS. The USFWS provided support in development of assessment scores.
| Funders | Funder number |
|---|---|
| DEB-1258203, DEB-1050459 | |
| National Aeronautics and Space Administration | NNX14AC91G |
| Michigan State University | |
| Colorado Department of Natural Resources |
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