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      A renewed glance at the Palearctic golden eagle: Genetic variation in space and time

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          Abstract

          Anthropogenic pressures on nature have been causing population declines for centuries. Intensified persecution of apex predators, like the golden eagle, resulted in population bottlenecks during the 19th and 20th centuries. To study population genetics and demographic history of the golden eagle throughout its distribution, we collected museum samples from previously underrepresented regions, such as Russia and Central Asia. We used 12 microsatellite loci and a fragment of the mitochondrial DNA control region to re‐evaluate phylogeography of Eurasian golden eagles and study the impacts of the population bottleneck. Our results revealed a north–south genetic gradient, expressed by the difference between Mediterranean and Holarctic lineages, as well as genetically distinct Northern Europe and Central Asia and Caucasus regions. Furthermore, Northern Europe exhibited the lowest, whereas Central Asia and Caucasus had the highest genetic diversity. Although golden eagles maintained relatively high genetic diversity, we detected genetic signatures of the recent bottleneck, including reduced genetic diversity and a decline in the effective female population size around the year 1975. Our study improves the knowledge of the genetic composition of Eurasian golden eagles and highlights the importance of understanding their historical population dynamics in the face of ongoing and future conservation efforts.

          Abstract

          In this study, we investigated the phylogeography, demographic history, and impacts of past population bottlenecks in Eurasian golden eagles. Using microsatellite loci and mitochondrial DNA, we discovered a north–south genetic gradient where Central Asia and Caucasus was a high genetic diversity region, and Northern Europe showed the opposite trend. We also detected genetic signatures of a recent population bottleneck, including reduced genetic diversity and a decline in effective female population size around 1975, which highlight the significance of understanding historical population dynamics for conservation efforts.

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7

            Abstract Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.
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              Detecting the number of clusters of individuals using the software structure: a simulation study

              The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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                Author and article information

                Contributors
                ekaterina.karabanina@oulu.fi
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                10 March 2024
                March 2024
                : 14
                : 3 ( doiID: 10.1002/ece3.v14.3 )
                : e11109
                Affiliations
                [ 1 ] Ecology and Genetics Research Unit University of Oulu Oulu Finland
                Author notes
                [*] [* ] Correspondence

                Ekaterina Karabanina, Ecology and Genetics Research Unit, University of Oulu, Oulu 90014, Finland.

                Email: ekaterina.karabanina@ 123456oulu.fi

                Author information
                https://orcid.org/0000-0001-7001-8167
                Article
                ECE311109 ECE-2023-10-01907.R1
                10.1002/ece3.11109
                10925523
                38469039
                b94206e3-8d19-4203-84c7-f6898e229a7c
                © 2024 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
                : 16 February 2024
                : 02 November 2023
                : 21 February 2024
                Page count
                Figures: 6, Tables: 2, Pages: 19, Words: 14284
                Funding
                Funded by: Kvantum Institute of the University of Oulu
                Funded by: Societas pro Fauna et Flora Fennica , doi 10.13039/501100018756;
                Funded by: Oulun yliopiston tukisäätiö , doi 10.13039/501100012682;
                Award ID: 0195066‐5
                Categories
                Biogeography
                Conservation Genetics
                Genetics
                Population Genetics
                Research Article
                Research Articles
                Custom metadata
                2.0
                March 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.9 mode:remove_FC converted:10.03.2024

                Evolutionary Biology
                aquila chrysaetos,demographic history,microsatellites,mitochondrial dna,phylogeography,population bottleneck

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