Characterizing dispersal patterns in a threatened seabird with limited genetic structure.
2009 (English)In: Molecular ecology, ISSN 1365-294XArticle in journal (Refereed) Published
Abstract Genetic assignment methods provide an appealing approach for characterizing dispersal patterns on ecological time scales, but require sufficient genetic differentiation to accurately identify migrants and a large enough sample size of migrants to, for example, compare dispersal between sexes or age classes. We demonstrate that assignment methods can be rigorously used to characterize dispersal patterns in a marbled murrelet (Brachyramphus marmoratus) population from central California that numbers approximately 600 individuals and is only moderately differentiated (F(ST) approximately 0.03) from larger populations to the north. We used coalescent simulations to select a significance level that resulted in a low and approximately equal expected number of type I and II errors and then used this significance level to identify a population of origin for 589 individuals genotyped at 13 microsatellite loci. The proportion of migrants in central California was greatest during winter when 83% of individuals were classified as migrants compared to lower proportions during the breeding (6%) and post-breeding (8%) seasons. Dispersal was also biased toward young and female individuals, as is typical in birds. Migrants were rarely members of parent-offspring pairs, suggesting that they contributed few young to the central California population. A greater number of migrants than expected under equilibrium conditions, a lack of individuals with mixed ancestry, and a small number of potential source populations (two), likely allowed us to use assignment methods to rigorously characterize dispersal patterns for a population that was larger and less differentiated than typically thought required for the identification of migrants.
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IdentifiersURN: urn:nbn:se:su:diva-32386DOI: 10.1111/j.1365-294X.2009.04416.xISI: 000272452700010PubMedID: 19912540OAI: oai:DiVA.org:su-32386DiVA: diva2:280395