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      Multiscale landscape genetics of American marten at their southern range periphery

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          Abstract

          American marten ( Martes americana) are a conservation priority in many forested regions of North America. Populations are fragmented at the southern edge of their distribution due to suboptimal habitat conditions. Facilitating gene flow may improve population resilience through genetic and demographic rescue. We used a multiscale approach to estimate the relationship between genetic connectivity and landscape characteristics among individuals at three scales in the northeastern United States: regional, subregional, and local. We integrated multiple modeling techniques and identified top models based on consensus. Top models were used to parameterize resistance surfaces at each scale, and circuit theory was used to identify potential movement corridors. Regional gene flow was affected by forest cover, elevation, developed land cover, and slope. At subregional and local scales, the effects were site specific and included subsets of temperature, elevation, developed land cover, and slope. Developed land cover significantly affected gene flow at each scale. At finer scales, lack of variance in forest cover may have limited the ability to detect a relationship with gene flow. The effect of slope on gene flow was positive or negative, depending on the site examined. Occupancy probability was a relatively poor predictor, and we caution its use as a proxy for landscape resistance. Our results underscore the importance of replication and multiscale approaches in landscape genetics. Climate warming and landscape conversion may reduce the genetic connectivity of marten populations in the northeastern United States, and represent the primary challenges to marten conservation at the southern periphery of their range.

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          A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion

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            USING CIRCUIT THEORY TO MODEL CONNECTIVITY IN ECOLOGY, EVOLUTION, AND CONSERVATION

            Connectivity among populations and habitats is important for a wide range of ecological processes. Understanding, preserving, and restoring connectivity in complex landscapes requires connectivity models and metrics that are reliable, efficient, and process based. We introduce a new class of ecological connectivity models based in electrical circuit theory. Although they have been applied in other disciplines, circuit-theoretic connectivity models are new to ecology. They offer distinct advantages over common analytic connectivity models, including a theoretical basis in random walk theory and an ability to evaluate contributions of multiple dispersal pathways. Resistance, current, and voltage calculated across graphs or raster grids can be related to ecological processes (such as individual movement and gene flow) that occur across large population networks or landscapes. Efficient algorithms can quickly solve networks with millions of nodes, or landscapes with millions of raster cells. Here we review basic circuit theory, discuss relationships between circuit and random walk theories, and describe applications in ecology, evolution, and conservation. We provide examples of how circuit models can be used to predict movement patterns and fates of random walkers in complex landscapes and to identify important habitat patches and movement corridors for conservation planning.
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              Genetic rescue to the rescue.

              Genetic rescue can increase the fitness of small, imperiled populations via immigration. A suite of studies from the past decade highlights the value of genetic rescue in increasing population fitness. Nonetheless, genetic rescue has not been widely applied to conserve many of the threatened populations that it could benefit. In this review, we highlight recent studies of genetic rescue and place it in the larger context of theoretical and empirical developments in evolutionary and conservation biology. We also propose directions to help shape future research on genetic rescue. Genetic rescue is a tool that can stem biodiversity loss more than has been appreciated, provides population resilience, and will become increasingly useful if integrated with molecular advances in population genomics.
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                Author and article information

                Contributors
                cmaylward@ucdavis.edu
                Journal
                Heredity (Edinb)
                Heredity (Edinb)
                Heredity
                Springer International Publishing (Cham )
                0018-067X
                1365-2540
                28 January 2020
                28 January 2020
                April 2020
                : 124
                : 4
                : 550-561
                Affiliations
                [1 ]ISNI 0000 0004 1936 7689, GRID grid.59062.38, Wildlife and Fisheries Biology Program, Rubenstein School of Environment and Natural Resources, , University of Vermont, ; 81 Carrigan Drive, Burlington, VT 05405 USA
                [2 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Department of Wildlife, Fish and Conservation Biology, One Shields Avenue, , University of California, ; Davis, CA 95616 USA
                [3 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Mammalian Ecology and Conservation Unit, Veterinary Genetics Laboratory, , University of California, ; Davis, CA 95616 USA
                [4 ]ISNI 0000 0004 1936 7689, GRID grid.59062.38, Department of Biology, , University of Vermont, ; 109 Carrigan Drive, Burlington, VT 05405 USA
                Author information
                http://orcid.org/0000-0003-4105-0939
                Article
                295
                10.1038/s41437-020-0295-y
                7080830
                31992842
                d2772e6b-8c65-44f0-9105-c891581997af
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 30 April 2019
                : 10 November 2019
                : 11 November 2019
                Funding
                Funded by: Vermont Department of Fish and Wildlife
                Categories
                Article
                Custom metadata
                © The Genetics Society 2020

                Human biology
                ecological genetics,population genetics
                Human biology
                ecological genetics, population genetics

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