Genetic variation among interconnected populations of Catostomus occidentalis: Implications for distinguishing impacts of contaminants from biogeographical structuring
Exposure to contaminants can affect survivorship, recruitment, reproductive success, mutation rates and migration, and may play a significant role in the partitioning of genetic variation among exposed and nonexposed populations. However, the application of molecular population genetic data to evaluate such influences has been uncommon and often flawed. We tested whether patterns of genetic variation among native fish populations (Sacramento sucker, Catostomus occidentalis) in the Central Valley of California were consistent with long-term pesticide exposure history, or primarily with expectations based on biogeography. Field sampling was designed to rigorously test for both geographical and contamination influences. Fine-scale structure of these interconnected populations was detected with both amplified fragment length polymorphisms (AFLP) and microsatellite markers, and patterns of variation elucidated by the two marker systems were highly concordant. Analyses indicated that biogeographical hypotheses described the data set better than hypotheses relating to common historical pesticide exposure. Downstream populations had higher genetic diversity than upstream populations, regardless of exposure history, and genetic distances showed that populations from the same river system tended to cluster together. Relatedness among populations reflected primarily directions of gene flow, rather than convergence among contaminant-exposed populations. Watershed geography accounted for significant partitioning of genetic variation among populations, whereas contaminant exposure history did not. Genetic patterns indicating contaminant-induced selection, increased mutation rates or recent bottlenecks were weak or absent. We stress the importance of testing contaminant-induced genetic change hypotheses within a biogeographical context. Strategic application of molecular markers for analysis of fine-scale structure, and for evaluating contaminant impacts on gene pools, is discussed.