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      Genetic Structure Among 50 Species of the Northeastern Pacific Rocky Intertidal Community

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      PLoS ONE
      Public Library of Science

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          Abstract

          Comparing many species' population genetic patterns across the same seascape can identify species with different levels of structure, and suggest hypotheses about the processes that cause such variation for species in the same ecosystem. This comparative approach helps focus on geographic barriers and selective or demographic processes that define genetic connectivity on an ecosystem scale, the understanding of which is particularly important for large-scale management efforts. Moreover, a multispecies dataset has great statistical advantages over single-species studies, lending explanatory power in an effort to uncover the mechanisms driving population structure. Here, we analyze a 50-species dataset of Pacific nearshore invertebrates with the aim of discovering the most influential structuring factors along the Pacific coast of North America. We collected cytochrome c oxidase I (COI) mtDNA data from populations of 34 species of marine invertebrates sampled coarsely at four coastal locations in California, Oregon, and Alaska, and added published data from 16 additional species. All nine species with non-pelagic development have strong genetic structure. For the 41 species with pelagic development, 13 show significant genetic differentiation, nine of which show striking F ST levels of 0.1–0.6. Finer scale geographic investigations show unexpected regional patterns of genetic change near Cape Mendocino in northern California for five of the six species tested. The region between Oregon and Alaska is a second focus of intraspecific genetic change, showing differentiation in half the species tested. Across regions, strong genetic subdivision occurs more often than expected in mid-to-high intertidal species, a result that may reflect reduced gene flow due to natural selection along coastal environmental gradients. Finally, the results highlight the importance of making primary research accessible to policymakers, as unexpected barriers to marine dispersal break the coast into separate demographic zones that may require their own management plans.

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          Arlequin (version 3.0): An integrated software package for population genetics data analysis

          Arlequin ver 3.0 is a software package integrating several basic and advanced methods for population genetics data analysis, like the computation of standard genetic diversity indices, the estimation of allele and haplotype frequencies, tests of departure from linkage equilibrium, departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions, and thorough analyses of population subdivision under the AMOVA framework. Arlequin 3 introduces a completely new graphical interface written in C++, a more robust semantic analysis of input files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes, and an estimation of the parameters of an instantaneous spatial expansion from DNA sequence polymorphism. Arlequin can handle several data types like DNA sequences, microsatellite data, or standard multi-locus genotypes. A Windows version of the software is freely available on http://cmpg.unibe.ch/software/arlequin3.
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            Connectivity of marine populations: open or closed?

            Most marine populations are thought to be well connected via long-distance dispersal of larval stages. Eulerian and Lagrangian flow models, coupled with linear mortality estimates, were used to examine this assumption. The findings show that when simple advection models are used, larval exchange rates may be overestimated; such simplistic models fail to account for a decrease of up to nine orders of magnitude in larval concentrations resulting from diffusion and mortality. The alternative process of larval retention near local populations is shown to exist and may be of great importance in the maintenance of marine population structure and management of coastal marine resources.
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              Dispersal, gene flow, and population structure.

              The accuracy of gene flow estimates is unknown in most natural populations because direct estimates of dispersal are often not possible. These estimates can be highly imprecise or even biased because population genetic structure reflects more than a simple balance between genetic drift and gene flow. Most of the models used to estimate gene flow also assume very simple patterns of movement. As a result, multiple interpretations of population structure involving contemporary gene flow, departures from equilibrium, and other factors are almost always possible. One way to isolate the relative contribution of gene flow to population genetic differentiation is to utilize comparative methods. Population genetic statistics such as FST, heterozygosity and Nei's D can be compared between species with differing dispersal abilities if these species are otherwise phylogenetically, geographically and demographically comparable. Accordingly, the available literature was searched for all groups that meet these criteria to determine whether broad conclusions regarding the relationships between dispersal, population genetic structure, and gene flow estimates are possible. Allozyme and mtDNA data were summarized for 27 animal groups in which dispersal differences can be characterized. In total, genetic data were obtained for 333 species of vertebrates and invertebrates from terrestrial, freshwater and marine habitats. Across these groups, dispersal ability was consistently related to population structure, with a mean rank correlation of -0.72 between ranked dispersal ability and FST. Gene flow estimates derived from private alleles were also correlated with dispersal ability, but were less widely available. Direct-count heterozygosity and average values of Nei's D showed moderate degrees of correlation with dispersal ability. Thus, despite regional, taxonomic and methodological differences among the groups of species surveyed, available data demonstrate that dispersal makes a measurable contribution to population genetic differentiation in the majority of animal species in nature, and that gene flow estimates are rarely so overwhelmed by population history, departures from equilibrium, or other microevolutionary forces as to be uninformative.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2010
                7 January 2010
                : 5
                : 1
                : e8594
                Affiliations
                [1]Department of Biology, Hopkins Marine Station, Stanford University, Pacific Grove, California, United States of America
                University of California San Diego, United States of America
                Author notes

                Conceived and designed the experiments: RK SP. Performed the experiments: RK. Analyzed the data: RK SP. Contributed reagents/materials/analysis tools: SP. Wrote the paper: RK SP.

                Article
                09-PONE-RA-12052R1
                10.1371/journal.pone.0008594
                2799524
                20062807
                238fdc1e-f3f5-4c13-8cf9-647e7be32796
                Kelly, Palumbi. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 3 August 2009
                : 7 December 2009
                Page count
                Pages: 13
                Categories
                Research Article
                Ecology/Marine and Freshwater Ecology
                Ecology/Population Ecology
                Genetics and Genomics/Population Genetics
                Marine and Aquatic Sciences/Biological Oceanography
                Marine and Aquatic Sciences/Ecology
                Marine and Aquatic Sciences/Evolutionary Biology
                Marine and Aquatic Sciences/Genetics, Genomics, and Barcoding

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                Uncategorized

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