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Genetic Population Structure of Brook Trout Inhabiting a Large River Watershed
Author(s) -
Rogers Sean M.,
Curry R. Allen
Publication year - 2004
Publication title -
transactions of the american fisheries society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.696
H-Index - 86
eISSN - 1548-8659
pISSN - 0002-8487
DOI - 10.1577/t01-153.1
Subject(s) - salvelinus , trout , watershed , ecology , biological dispersal , population , biology , genetic structure , isolation by distance , habitat , sampling (signal processing) , drainage basin , geography , genetic variation , fishery , cartography , fish <actinopterygii> , demography , machine learning , sociology , computer science , filter (signal processing) , computer vision
The genetic population structure of brook trout Salvelinus fontinalis inhabiting the Miramichi River, New Brunswick, a large (14,000‐km 2 ) river system composed of three main stems, was assessed using six microsatellite DNA loci. Samples from 12 sites incorporating four temporal replicates were analyzed. An individual‐based assignment method without a priori knowledge of geographic origin suggested the presence of five candidate source populations within the 12 sites. Drainage structuring based on the 12 sampling sites did not explain the observed patterns of genetic population structure (analysis of molecular variance: 0.74% of variance explained; not significant). Conversely, the five candidate source populations estimated under the assignment approach significantly explained the genetic population structure observed (3.47% of variance explained; P < 0.001), the level of population fragmentation within sampling sites increasing significantly with proximity to the mouth of the watershed ( P = 0.011). These results suggested elevated levels of brook trout dispersal within a large river watershed where geographic distance among sampling sites did not have a significant impact on the genetic population structure. Brook trout populations inhabiting a large river watershed may therefore be more influenced by ecological variables affecting the observed patterns of divergence, such as alternative life history strategies (e.g., anadromy) and habitat selection.