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Landscape attributes and life history variability shape genetic structure of trout populations in a stream network

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Abstract

Spatial and temporal landscape patterns have long been recognized to influence biological processes, but these processes often operate at scales that are difficult to study by conventional means. Inferences from genetic markers can overcome some of these limitations. We used a landscape genetics approach to test hypotheses concerning landscape processes influencing the demography of Lahontan cutthroat trout in a complex stream network in the Great Basin desert of the western US. Predictions were tested with population- and individual-based analyses of microsatellite DNA variation, reflecting patterns of dispersal, population stability, and local effective population sizes. Complementary genetic inferences suggested samples from migratory corridors housed a mixture of fish from tributaries, as predicted based on assumed migratory life histories in those habitats. Also as predicted, populations presumed to have greater proportions of migratory fish or from physically connected, large, or high quality habitats had higher genetic variability and reduced genetic differentiation from other populations. Populations thought to contain largely non-migratory individuals generally showed the opposite pattern, suggesting behavioral isolation. Estimated effective sizes were small, and we identified significant and severe genetic bottlenecks in several populations that were isolated, recently founded, or that inhabit streams that desiccate frequently. Overall, this work suggested that Lahontan cutthroat trout populations in stream networks are affected by a combination of landscape and metapopulation processes. Results also demonstrated that genetic patterns can reveal unexpected processes, even within a system that is well studied from a conventional ecological perspective.

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  1. Department of Biology/314, University of Nevada, Reno, NV, 89557, USA

    Helen M. Neville & Mary M. Peacock

  2. Rocky Mountain Research Station, 316 E. Myrtle St., Boise, ID, 83702, USA

    Helen M. Neville & Jason B. Dunham

  3. USGS FRESC Corvallis Research Group 3200 SW Jefferson Way Corvallis, OR, 97331

    Jason B. Dunham

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  1. Helen M. Neville
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Neville, H.M., Dunham, J.B. & Peacock, M.M. Landscape attributes and life history variability shape genetic structure of trout populations in a stream network. Landscape Ecol 21, 901–916 (2006). https://doi.org/10.1007/s10980-005-5221-4

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