30
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Early detection of population declines: high power of genetic monitoring using effective population size estimators

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Early detection of population declines is essential to prevent extinctions and to ensure sustainable harvest. We evaluated the performance of two N e estimators to detect population declines: the two-sample temporal method and a one-sample method based on linkage disequilibrium (LD). We used simulated data representing a wide range of population sizes, sample sizes and number of loci. Both methods usually detect a population decline only one generation after it occurs if N e drops to less than approximately 100, and 40 microsatellite loci and 50 individuals are sampled. However, the LD method often out performed the temporal method by allowing earlier detection of less severe population declines ( N e approximately 200). Power for early detection increased more rapidly with the number of individuals sampled than with the number of loci genotyped, primarily for the LD method. The number of samples available is therefore an important criterion when choosing between the LD and temporal methods. We provide guidelines regarding design of studies targeted at monitoring for population declines. We also report that 40 single nucleotide polymorphism (SNP) markers give slightly lower precision than 10 microsatellite markers. Our results suggest that conservation management and monitoring strategies can reliably use genetic based methods for early detection of population declines.

          Related collections

          Most cited references40

          • Record: found
          • Abstract: found
          • Article: not found

          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.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci*

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Estimation of effective population size from data on linkage disequilibrium

                Bookmark

                Author and article information

                Journal
                Evol Appl
                Evol Appl
                eva
                Evolutionary Applications
                Blackwell Publishing Ltd (Oxford, UK )
                1752-4571
                1752-4571
                January 2011
                03 August 2010
                : 4
                : 1
                : 144-154
                Affiliations
                [1 ]simpleLiverpool School of Tropical Medicine Liverpool, UK
                [2 ]simpleDepartamento de Bioquímica, Genética e Inmunología, Facultad de Biología, Universidad de Vigo Vigo, Spain
                [3 ]simpleFlathead Lake Biological Station and Division of Biological Sciences, University of Montana Polson, MT, USA
                [4 ]simpleCIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão Vairão, Portugal
                Author notes
                Tiago Antao, Liverpool School of Tropical Medicine, Liverpool, UK. Tel: +44(0)151 705 3100; fax: +44(0)151 705 3370; e-mail: tra@ 123456popgen.eu
                Article
                10.1111/j.1752-4571.2010.00150.x
                3352520
                25567959
                99ef7ea0-e775-479b-8269-e74a27b567ca
                © 2010 Blackwell Publishing Ltd
                History
                : 15 June 2010
                : 25 June 2010
                Categories
                Original Articles

                Evolutionary Biology
                bottleneck,computational simulations,population monitoring,statistical power,habitat fragmentation,endangered species,effective population size

                Comments

                Comment on this article