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      Genetic mixing for population management: From genetic rescue to provenancing


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          Animal and plant species around the world are being challenged by the deleterious effects of inbreeding, loss of genetic diversity, and maladaptation due to widespread habitat destruction and rapid climate change. In many cases, interventions will likely be needed to safeguard populations and species and to maintain functioning ecosystems. Strategies aimed at initiating, reinstating, or enhancing patterns of gene flow via the deliberate movement of genotypes around the environment are generating growing interest with broad applications in conservation and environmental management. These diverse strategies go by various names ranging from genetic or evolutionary rescue to provenancing and genetic resurrection. Our aim here is to provide some clarification around terminology and to how these strategies are connected and linked to underlying genetic processes. We draw on case studies from the literature and outline mechanisms that underlie how the various strategies aim to increase species fitness and impact the wider community. We argue that understanding mechanisms leading to species decline and community impact is a key to successful implementation of these strategies. We emphasize the need to consider the nature of source and recipient populations, as well as associated risks and trade‐offs for the various strategies. This overview highlights where strategies are likely to have potential at population, species, and ecosystem scales, but also where they should probably not be attempted depending on the overall aims of the intervention. We advocate an approach where short‐ and long‐term strategies are integrated into a decision framework that also considers nongenetic aspects of management.

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          Most cited references152

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          Spatial and temporal patterns of mass bleaching of corals in the Anthropocene

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            Climate change and evolutionary adaptation.

            Evolutionary adaptation can be rapid and potentially help species counter stressful conditions or realize ecological opportunities arising from climate change. The challenges are to understand when evolution will occur and to identify potential evolutionary winners as well as losers, such as species lacking adaptive capacity living near physiological limits. Evolutionary processes also need to be incorporated into management programmes designed to minimize biodiversity loss under rapid climate change. These challenges can be met through realistic models of evolutionary change linked to experimental data across a range of taxa.
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              Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

              Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding.

                Author and article information

                Evol Appl
                Evol Appl
                Evolutionary Applications
                John Wiley and Sons Inc. (Hoboken )
                06 November 2020
                March 2021
                : 14
                : 3 ( doiID: 10.1111/eva.v14.3 )
                : 634-652
                [ 1 ] School of BioSciences Bio21 Institute The University of Melbourne Parkville Vic. Australia
                [ 2 ] School of Life and Environmental Sciences Centre for Integrative Ecology Deakin University Warrnambool Vic. Australia
                [ 3 ] Deakin Genomics Centre Deakin University Geelong Vic. Australia
                [ 4 ] cesar Pty Ltd Parkville Vic. Australia
                Author notes
                [*] [* ] Correspondence

                Ary A. Hoffmann, School of BioSciences, Bio21 Institute, The University of Melbourne, Parkville, Vic., Australia.

                Email: ary@ 123456unimelb.edu.au

                Author information
                © 2020 The Authors. Evolutionary Applications 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.

                : 10 October 2020
                : 20 August 2020
                : 14 October 2020
                Page count
                Figures: 5, Tables: 2, Pages: 19, Words: 15537
                Reviews and Syntheses
                Reviews and Syntheses
                Custom metadata
                March 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.0 mode:remove_FC converted:20.03.2021

                Evolutionary Biology
                adaptation,conservation,genetic variation,population size,revegetation
                Evolutionary Biology
                adaptation, conservation, genetic variation, population size, revegetation


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