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      Can effective population size estimates be used to monitor population trends of woodland bats? A case study of Myotis bechsteinii

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          Abstract

          Molecular approaches to calculate effective population size estimates (Ne) are increasingly used as an alternative to long‐term demographic monitoring of wildlife populations. However, the complex ecology of most long‐lived species and the consequent uncertainties in model assumptions means that effective population size estimates are often imprecise. Although methods exist to incorporate age structure into Ne estimations for long‐lived species with overlapping generations, they are rarely used owing to the lack of relevant information for most wild populations. Here, we performed a case study on an elusive woodland bat, Myotis bechsteinii, to compare the use of the parentage assignment Ne estimator (EPA) with the more commonly used linkage disequilibrium (LD) Ne estimator in detecting long‐term population trends, and assessed the impacts of deploying different overall sample sizes. We used genotypic data from a previously published study, and simulated 48 contrasting demographic scenarios over 150 years using the life history characteristics of this species The LD method strongly outperformed the EPA method. As expected, smaller sample sizes resulted in a reduced ability to detect population trends. Nevertheless, even the smallest sample size tested ( n = 30) could detect important changes (60%–80% decline) with the LD method. These results demonstrate that genetic approaches can be an effective way to monitor long‐lived species, such as bats, provided that they are undertaken over multiple decades.

          Abstract

          Molecular approaches to calculate effective population size estimates (Ne) are increasingly used as an alternative to long‐term demographic monitoring of wildlife populations. Here, we performed a case study on an elusive woodland bat, Myotis bechsteinii, to compare the use of the parentage assignment Ne estimator (EPA) (Figure b) with the more commonly used linkage disequilibrium (LD) Ne estimato (Figure a), and assessed the impacts of deploying different overall sample sizes. Our results indicated that the LD method provided more precise estimates (known population size shown in black) and was better suited for the long‐term monitoring of this species.

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          Most cited references43

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          NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne ) from genetic data.

          NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10 000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.
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            Evolution in Mendelian Populations.

            S. Wright (1931)
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              Estimation of effective population size from data on linkage disequilibrium

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                Author and article information

                Contributors
                f.mathews@sussex.ac.uk
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                03 February 2021
                March 2021
                : 11
                : 5 ( doiID: 10.1002/ece3.v11.5 )
                : 2015-2023
                Affiliations
                [ 1 ] Department of Life Sciences University of Sussex Falmer UK
                [ 2 ] Vincent Wildlife Trust Ledbury UK
                Author notes
                [*] [* ] Correspondence

                Fiona Mathews, Department of Life Sciences, University of Sussex, Falmer BN1 9QG, UK.

                Email: f.mathews@ 123456sussex.ac.uk

                Author information
                https://orcid.org/0000-0002-1026-6596
                https://orcid.org/0000-0002-2580-2769
                Article
                ECE37143
                10.1002/ece3.7143
                7920762
                711b696d-6f6a-4b57-a9a5-66d8a979365b
                © 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 July 2020
                : 26 November 2020
                : 04 December 2020
                Page count
                Figures: 5, Tables: 1, Pages: 9, Words: 6407
                Funding
                Funded by: Natural Environment Research Council , open-funder-registry 10.13039/501100000270;
                Award ID: NE/S006486/1
                Funded by: Vincent Wildlife Trust
                Funded by: Woodland Trust , open-funder-registry 10.13039/100012152;
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                March 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.9 mode:remove_FC converted:01.03.2021

                Evolutionary Biology
                chiroptera,effective population size,genetic monitoring,population monitoring,population trends,wildlife management

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