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      Introgression and dispersal among spotted owl ( Strix occidentalis) subspecies

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          Abstract

          Population genetics plays an increasingly important role in the conservation and management of declining species, particularly for defining taxonomic units. Subspecies are recognized by several conservation organizations and countries and receive legal protection under the US Endangered Species Act (ESA). Two subspecies of spotted owls, northern ( Strix occidentalis caurina) and Mexican ( S. o. lucida) spotted owls, are ESA-listed as threatened, but the California ( S. o. occidentalis) spotted owl is not listed. Thus, determining the boundaries of these subspecies is critical for effective enforcement of the ESA. We tested the validity of previously recognized spotted owl subspecies by analysing 394 spotted owls at 10 microsatellite loci. We also tested whether northern and California spotted owls hybridize as suggested by previous mitochondrial DNA studies. Our results supported current recognition of three subspecies. We also found bi-directional hybridization and dispersal between northern and California spotted owls centered in southern Oregon and northern California. Surprisingly, we also detected introgression of Mexican spotted owls into the range of northern spotted owls, primarily in the northern part of the subspecies’ range in Washington, indicating long-distance dispersal of Mexican spotted owls. We conclude with a discussion of the conservation implications of our study.

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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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            Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power.

            Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (DLR) appeared to be an effective way to predict whether F0 immigrants could be identified for a particular pair of populations using a given set of markers.
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              What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity.

              We review commonly used population definitions under both the ecological paradigm (which emphasizes demographic cohesion) and the evolutionary paradigm (which emphasizes reproductive cohesion) and find that none are truly operational. We suggest several quantitative criteria that might be used to determine when groups of individuals are different enough to be considered 'populations'. Units for these criteria are migration rate (m) for the ecological paradigm and migrants per generation (Nm) for the evolutionary paradigm. These criteria are then evaluated by applying analytical methods to simulated genetic data for a finite island model. Under the standard parameter set that includes L = 20 High mutation (microsatellite-like) loci and samples of S = 50 individuals from each of n = 4 subpopulations, power to detect departures from panmixia was very high ( approximately 100%; P < 0.001) even with high gene flow (Nm = 25). A new method, comparing the number of correct population assignments with the random expectation, performed as well as a multilocus contingency test and warrants further consideration. Use of Low mutation (allozyme-like) markers reduced power more than did halving S or L. Under the standard parameter set, power to detect restricted gene flow below a certain level X (H(0): Nm < X) can also be high, provided that true Nm < or = 0.5X. Developing the appropriate test criterion, however, requires assumptions about several key parameters that are difficult to estimate in most natural populations. Methods that cluster individuals without using a priori sampling information detected the true number of populations only under conditions of moderate or low gene flow (Nm < or = 5), and power dropped sharply with smaller samples of loci and individuals. A simple algorithm based on a multilocus contingency test of allele frequencies in pairs of samples has high power to detect the true number of populations even with Nm = 25 but requires more rigorous statistical evaluation. The ecological paradigm remains challenging for evaluations using genetic markers, because the transition from demographic dependence to independence occurs in a region of high migration where genetic methods have relatively little power. Some recent theoretical developments and continued advances in computational power provide hope that this situation may change in the future.
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                Author and article information

                Journal
                Evol Appl
                Evol Appl
                eva
                Evolutionary Applications
                Blackwell Publishing Ltd (Oxford, UK )
                1752-4571
                1752-4571
                February 2008
                09 January 2008
                : 1
                : 1
                : 161-171
                Affiliations
                [1 ]simpleUS Geological Survey, Forest and Rangeland Ecosystem Science Center Corvallis, OR, USA
                [2 ]simpleUSDA Forest Service, Pacific Northwest Research Station Corvallis, OR, USA
                Author notes
                W. Chris Funk, Biology Department, College of William and Mary, PO Box 8795, Williamsburg, VA 23187, USA. Tel.: +757 221 2216; fax: +757 221 6483; e-mail: wcfunk@ 123456wm.edu
                Article
                10.1111/j.1752-4571.2007.00002.x
                3352401
                319a3613-63e5-467e-a1e8-dff19e1d4234
                © 2008 The Authors
                History
                : 13 November 2007
                Categories
                Original Articles

                Evolutionary Biology
                subspecies,long-distance dispersal,spotted owl,conservation,strix occidentalis,microsatellites,introgression,us endangered species act

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