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      Landscape Genetics for the Empirical Assessment of Resistance Surfaces: The European Pine Marten ( Martes martes) as a Target-Species of a Regional Ecological Network

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          Abstract

          Coherent ecological networks (EN) composed of core areas linked by ecological corridors are being developed worldwide with the goal of promoting landscape connectivity and biodiversity conservation. However, empirical assessment of the performance of EN designs is critical to evaluate the utility of these networks to mitigate effects of habitat loss and fragmentation. Landscape genetics provides a particularly valuable framework to address the question of functional connectivity by providing a direct means to investigate the effects of landscape structure on gene flow. The goals of this study are (1) to evaluate the landscape features that drive gene flow of an EN target species (European pine marten), and (2) evaluate the optimality of a regional EN design in providing connectivity for this species within the Basque Country (North Spain). Using partial Mantel tests in a reciprocal causal modeling framework we competed 59 alternative models, including isolation by distance and the regional EN. Our analysis indicated that the regional EN was among the most supported resistance models for the pine marten, but was not the best supported model. Gene flow of pine marten in northern Spain is facilitated by natural vegetation, and is resisted by anthropogenic landcover types and roads. Our results suggest that the regional EN design being implemented in the Basque Country will effectively facilitate gene flow of forest dwelling species at regional scale.

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          New insights from fine-scale spatial genetic structure analyses in plant populations.

          Many empirical studies have assessed fine-scale spatial genetic structure (SGS), i.e. the nonrandom spatial distribution of genotypes, within plant populations using genetic markers and spatial autocorrelation techniques. These studies mostly provided qualitative descriptions of SGS, rendering quantitative comparisons among studies difficult. The theory of isolation by distance can predict the pattern of SGS under limited gene dispersal, suggesting new approaches, based on the relationship between pairwise relatedness coefficients and the spatial distance between individuals, to quantify SGS and infer gene dispersal parameters. Here we review the theory underlying such methods and discuss issues about their application to plant populations, such as the choice of the relatedness statistics, the sampling scheme to adopt, the procedure to test SGS, and the interpretation of spatial autocorrelograms. We propose to quantify SGS by an 'Sp' statistic primarily dependent upon the rate of decrease of pairwise kinship coefficients between individuals with the logarithm of the distance in two dimensions. Under certain conditions, this statistic estimates the reciprocal of the neighbourhood size. Reanalysing data from, mostly, published studies, the Sp statistic was assessed for 47 plant species. It was found to be significantly related to the mating system (higher in selfing species) and to the life form (higher in herbs than trees), as well as to the population density (higher under low density). We discuss the necessity for comparing SGS with direct estimates of gene dispersal distances, and show how the approach presented can be extended to assess (i) the level of biparental inbreeding, and (ii) the kurtosis of the gene dispersal distribution.
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            Noninvasive genetic sampling: look before you leap.

            Noninvasive sampling allows genetic studies of free-ranging animals without the need to capture or even observe them, and thus allows questions to be addressed that cannot be answered using conventional methods. Initially, this sampling strategy promised to exploit fully the existing DNA-based technology for studies in ethology, conservation biology and population genetics. However, recent work now indicates the need for a more cautious approach, which includes quantifying the genotyping error rate. Despite this, many of the difficulties of noninvasive sampling will probably be overcome with improved methodology.
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              Use of resistance surfaces for landscape genetic studies: considerations for parameterization and analysis.

              Measures of genetic structure among individuals or populations collected at different spatial locations across a landscape are commonly used as surrogate measures of functional (i.e. demographic or genetic) connectivity. In order to understand how landscape characteristics influence functional connectivity, resistance surfaces are typically created in a raster GIS environment. These resistance surfaces represent hypothesized relationships between landscape features and gene flow, and are based on underlying biological functions such as relative abundance or movement probabilities in different land cover types. The biggest challenge for calculating resistance surfaces is assignment of resistance values to different landscape features. Here, we first identify study objectives that are consistent with the use of resistance surfaces and critically review the various approaches that have been used to parameterize resistance surfaces and select optimal models in landscape genetics. We then discuss the biological assumptions and considerations that influence analyses using resistance surfaces, such as the relationship between gene flow and dispersal, how habitat suitability may influence animal movement, and how resistance surfaces can be translated into estimates of functional landscape connectivity. Finally, we outline novel approaches for creating optimal resistance surfaces using either simulation or computational methods, as well as alternatives to resistance surfaces (e.g. network and buffered paths). These approaches have the potential to improve landscape genetic analyses, but they also create new challenges. We conclude that no single way of using resistance surfaces is appropriate for every situation. We suggest that researchers carefully consider objectives, important biological assumptions and available parameterization and validation techniques when planning landscape genetic studies.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                16 October 2014
                : 9
                : 10
                : e110552
                Affiliations
                [1 ]Department of Zoology and Animal Cell Biology, University of the Basque Country, UPV/EHU, Vitoria-Gasteiz, Spain
                [2 ]Systematics, Biogeography and Population Dynamics Research Group, Lascaray Research Center, University of the Basque Country, UPV/EHU, Vitoria-Gasteiz, Spain
                [3 ]Conservation Genetics Laboratory, National Institute for Environmental Protection and Research, ISPRA, Ozzano dell'Emilia, Bologna, Italy
                [4 ]Department of Geography, University of the Basque Country, UPV/EHU, Vitoria-Gasteiz, Spain
                [5 ]U.S. Forest Service, Rocky Mountain Research Station, Flagstaff, AZ, United States of America
                [6 ]Department 18/Section of Environmental Engineering, Aalborg University, Aalborg, Denmark
                Smithsonian Conservation Biology Institute, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: ARG MG SC ER BJGM. Performed the experiments: ARG MG MJM. Analyzed the data: ARG MG SC. Contributed reagents/materials/analysis tools: ER BJGM. Wrote the paper: ARG MG SC. Revised the manuscript: ARG MG SC MJM ER BJGM.

                Article
                PONE-D-13-52837
                10.1371/journal.pone.0110552
                4199733
                25329047
                bd3447e5-7756-43d9-820f-2e4e89f2fb01
                Copyright @ 2014

                This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 17 December 2013
                : 23 September 2014
                Page count
                Pages: 19
                Funding
                This study has been funded by the Basque Government through the Research group on “Systematics, Biogeography and Population Dynamics” (Ref. IT317-10; GIC10/76; IT575/13) and by the University of the Basque Country (UPV-EHU) and the Department of Environment, Territorial Planning, Agriculture and Fisheries (Basque Government) through IKT S.A under the University-Enterprise research program (Ref. UE07/02). Ruiz-González holds a Post doc fellowship awarded by the Dept. of Education Universities and Research of the Basque Government (Ref. DKR-2012-64). Several samples analysed in this study have been obtained in the framework of different carnivore surveys funded by regional or national administrations (Spanish Ministry of Environment, Regional Governments of Navarre and Aragon, Alava Provincial Council). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Ecology
                Biodiversity
                Spatial and Landscape Ecology
                Evolutionary Biology
                Population Genetics
                Gene Flow
                Zoology
                Mammalogy
                Ecology and Environmental Sciences
                Conservation Science

                Uncategorized
                Uncategorized

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