Estimating connectivity in marine populations: an empirical evaluation of assignment tests and parentage analysis under different gene flow scenarios
Identifieur interne : 001564 ( Istex/Curation ); précédent : 001563; suivant : 001565Estimating connectivity in marine populations: an empirical evaluation of assignment tests and parentage analysis under different gene flow scenarios
Auteurs : P. Saenz-Agudelo ; G. P. Jones [Australie] ; S. R. Thorrold [États-Unis] ; S. PlanesSource :
- Molecular Ecology [ 0962-1083 ] ; 2009-04.
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Abstract
The application of spatially explicit models of population dynamics to fisheries management and the design marine reserve network systems has been limited due to a lack of empirical estimates of larval dispersal. Here we compared assignment tests and parentage analysis for examining larval retention and connectivity under two different gene flow scenarios using panda clownfish (Amphiprion polymnus) in Papua New Guinea. A metapopulation of panda clownfish in Bootless Bay with little or no genetic differentiation among five spatially discrete locations separated by 2–6 km provided the high gene flow scenario. The low gene flow scenario compared the Bootless Bay metapopulation with a genetically distinct population (FST = 0.1) located at Schumann Island, New Britain, 1500 km to the northeast. We used assignment tests and parentage analysis based on microsatellite DNA data to identify natal origins of 177 juveniles in Bootless Bay and 73 juveniles at Schumann Island. At low rates of gene flow, assignment tests correctly classified juveniles to their source population. On the other hand, parentage analysis led to an overestimate of self‐recruitment within the two populations due to the significant deviation from panmixia when both populations were pooled. At high gene flow (within Bootless Bay), assignment tests underestimated self‐recruitment and connectivity among subpopulations, and grossly overestimated self‐recruitment within the overall metapopulation. However, the assignment tests did identify immigrants from distant (genetically distinct) populations. Parentage analysis clearly provided the most accurate estimates of connectivity in situations of high gene flow.
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DOI: 10.1111/j.1365-294X.2009.04109.x
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P. Saenz-Agudelo<affiliation><mods:affiliation>Laboratoire Écosystèmes Aquatiques Tropicaux et Méditerranéens UMR 5244 CNRS‐EPHE‐UPVD, Université de Perpignan 66860 Perpignan cedex, France,</mods:affiliation>
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<front><div type="abstract" xml:lang="en">The application of spatially explicit models of population dynamics to fisheries management and the design marine reserve network systems has been limited due to a lack of empirical estimates of larval dispersal. Here we compared assignment tests and parentage analysis for examining larval retention and connectivity under two different gene flow scenarios using panda clownfish (Amphiprion polymnus) in Papua New Guinea. A metapopulation of panda clownfish in Bootless Bay with little or no genetic differentiation among five spatially discrete locations separated by 2–6 km provided the high gene flow scenario. The low gene flow scenario compared the Bootless Bay metapopulation with a genetically distinct population (FST = 0.1) located at Schumann Island, New Britain, 1500 km to the northeast. We used assignment tests and parentage analysis based on microsatellite DNA data to identify natal origins of 177 juveniles in Bootless Bay and 73 juveniles at Schumann Island. At low rates of gene flow, assignment tests correctly classified juveniles to their source population. On the other hand, parentage analysis led to an overestimate of self‐recruitment within the two populations due to the significant deviation from panmixia when both populations were pooled. At high gene flow (within Bootless Bay), assignment tests underestimated self‐recruitment and connectivity among subpopulations, and grossly overestimated self‐recruitment within the overall metapopulation. However, the assignment tests did identify immigrants from distant (genetically distinct) populations. Parentage analysis clearly provided the most accurate estimates of connectivity in situations of high gene flow.</div>
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