Larval dispersal underlies demographically important intersystem connectivity in a Great Lakes yellow perch (Perca flavescens) population
Ability to quantify connectivity among spawning subpopulations and their relative contribution of recruits to the broader population is a critical fisheries management need. By combining microsatellite and age information from larval yellow perch (Perca flavescens) collected in the Lake St. Clair -...
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Published in | Canadian journal of fisheries and aquatic sciences Vol. 73; no. 3; p. 11 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
01.01.2016
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Subjects | |
Online Access | Get full text |
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Summary: | Ability to quantify connectivity among spawning subpopulations and their relative contribution of recruits to the broader population is a critical fisheries management need. By combining microsatellite and age information from larval yellow perch (Perca flavescens) collected in the Lake St. Clair - Detroit River system (SC-DRS) and western Lake Erie with a hydrodynamic backtracking approach, we quantified subpopulation structure, connectivity, and contributions of recruits to the juvenile stage in western Lake Erie during 2006-2007. After finding weak (yet stable) genetic structure between the SC-DRS and two western Lake Erie subpopulations, microsatellites also revealed measurable recruitment of SC-DRS larvae to the juvenile stage in western Lake Erie (17%-21% during 2006-2007). Consideration of precollection larval dispersal trajectories, using hydrodynamic backtracking, increased estimated contributions to 65% in 2006 and 57% in 2007. Our findings highlight the value of complementing subpopulation discrimination methods with hydrodynamic predictions of larval dispersal by revealing the SC-DRS as a source of recruits to western Lake Erie and also showing that connectivity through larval dispersal can affect the structure and dynamics of large lake fish populations. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 content type line 23 ObjectType-Feature-2 |
ISSN: | 0706-652X 1205-7533 |