Modelling functional landscape connectivity from genetic population structure: a new spatially explicit approach
Identifieur interne : 000E30 ( Istex/Corpus ); précédent : 000E29; suivant : 000E31Modelling functional landscape connectivity from genetic population structure: a new spatially explicit approach
Auteurs : Veronika Braunisch ; Gernot Segelbacher ; Alexandre H. HirzelSource :
- Molecular Ecology [ 0962-1083 ] ; 2010-09.
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Abstract
Functional connectivity between spatially disjoint habitat patches is a key factor for the persistence of species in fragmented landscapes. Modelling landscape connectivity to identify potential dispersal corridors requires information about those landscape features affecting dispersal. Here we present a new approach using spatial and genetic data of a highly fragmented population of capercaillie (Tetrao urogallus) in the Black Forest, Germany, to investigate effects of landscape structure on gene flow and to parameterize a spatially explicit corridor model for conservation purposes. Mantel tests and multiple regressions on distance matrices were employed to detect and quantify the effect of different landscape features on relatedness among individuals, while controlling for the effect of geographic distance. We extrapolated the results to an area‐wide landscape permeability map and developed a new corridor model that incorporates stochasticity in simulating animal movement. The model was evaluated using both a partition of the data previously set apart and independent observation data of dispersing birds. Most land cover variables (such as coniferous forest, forest edges, agricultural land, roads, settlements) and one topographic variable (topographic exposure) were significantly correlated with gene flow. Although inter‐individual relatedness inherently varies greatly and the variance explained by geographic distance and landscape structure was low, the permeability map and the corridor model significantly explained relatedness in the validation data and the spatial distribution of dispersing birds. Thus, landscape structure measurably affected within‐population gene flow in the study area. By converting these effects into spatially explicit information our model enables localizing priority areas for the preservation or restoration of metapopulation connectivity.
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DOI: 10.1111/j.1365-294X.2010.04703.x
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ISTEX:3285E1264D9F1D96E93CDC6513C7A8366D4A33CELe document en format XML
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Modelling landscape connectivity to identify potential dispersal corridors requires information about those landscape features affecting dispersal. Here we present a new approach using spatial and genetic data of a highly fragmented population of capercaillie (Tetrao urogallus) in the Black Forest, Germany, to investigate effects of landscape structure on gene flow and to parameterize a spatially explicit corridor model for conservation purposes. Mantel tests and multiple regressions on distance matrices were employed to detect and quantify the effect of different landscape features on relatedness among individuals, while controlling for the effect of geographic distance. We extrapolated the results to an area‐wide landscape permeability map and developed a new corridor model that incorporates stochasticity in simulating animal movement. The model was evaluated using both a partition of the data previously set apart and independent observation data of dispersing birds. Most land cover variables (such as coniferous forest, forest edges, agricultural land, roads, settlements) and one topographic variable (topographic exposure) were significantly correlated with gene flow. Although inter‐individual relatedness inherently varies greatly and the variance explained by geographic distance and landscape structure was low, the permeability map and the corridor model significantly explained relatedness in the validation data and the spatial distribution of dispersing birds. Thus, landscape structure measurably affected within‐population gene flow in the study area. 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Most land cover variables (such as coniferous forest, forest edges, agricultural land, roads, settlements) and one topographic variable (topographic exposure) were significantly correlated with gene flow. Although inter‐individual relatedness inherently varies greatly and the variance explained by geographic distance and landscape structure was low, the permeability map and the corridor model significantly explained relatedness in the validation data and the spatial distribution of dispersing birds. Thus, landscape structure measurably affected within‐population gene flow in the study area. 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BRAUNISCH, G. SEGELBACHER AND A. H. HIRZEL</title><title type="short">MODELLING LANDSCAPE CONNECTIVITY FROM GENETIC DATA</title></titleGroup><creators><creator creatorRole="author" xml:id="cr1" affiliationRef="#a1 #a2"><personName><givenNames>VERONIKA</givenNames><familyName>BRAUNISCH</familyName></personName></creator><creator creatorRole="author" xml:id="cr2" affiliationRef="#a3"><personName><givenNames>GERNOT</givenNames><familyName>SEGELBACHER</familyName></personName></creator><creator creatorRole="author" xml:id="cr3" affiliationRef="#a4"><personName><givenNames>ALEXANDRE H.</givenNames><familyName>HIRZEL</familyName></personName></creator></creators><affiliationGroup><affiliation xml:id="a1" countryCode="DE"><unparsedAffiliation>Forest Research Institute of Baden‐Wuerttemberg FVA, Wonnhaldestr. 4, D‐79100 Freiburg, Germany</unparsedAffiliation></affiliation><affiliation xml:id="a2" countryCode="CH"><unparsedAffiliation>Conservation Biology, Institute of Ecology and Evolution, University of Bern, CH‐3012 Bern, Switzerland</unparsedAffiliation></affiliation><affiliation xml:id="a3" countryCode="DE"><unparsedAffiliation>Department of Wildlife Ecology and Management, Albert‐Ludwigs University Freiburg, Tennenbacher Strasse 4, D‐79106 Freiburg, Germany</unparsedAffiliation></affiliation><affiliation xml:id="a4" countryCode="CH"><unparsedAffiliation>Centre Informatique, University of Lausanne, CH‐1015 Lausanne, Switzerland</unparsedAffiliation></affiliation></affiliationGroup><keywordGroup xml:lang="en"><keyword xml:id="k1">capercaillie</keyword><keyword xml:id="k2">dispersal corridors</keyword><keyword xml:id="k3">habitat connectivity</keyword><keyword xml:id="k4">landscape permeability</keyword><keyword xml:id="k5"><i>Tetrao urogallus</i></keyword></keywordGroup><abstractGroup><abstract type="main" xml:lang="en"><title type="main">Abstract</title><p>Functional connectivity between spatially disjoint habitat patches is a key factor for the persistence of species in fragmented landscapes. Modelling landscape connectivity to identify potential dispersal corridors requires information about those landscape features affecting dispersal. Here we present a new approach using spatial and genetic data of a highly fragmented population of capercaillie (<i>Tetrao urogallus</i>) in the Black Forest, Germany, to investigate effects of landscape structure on gene flow and to parameterize a spatially explicit corridor model for conservation purposes. Mantel tests and multiple regressions on distance matrices were employed to detect and quantify the effect of different landscape features on relatedness among individuals, while controlling for the effect of geographic distance. We extrapolated the results to an area‐wide landscape permeability map and developed a new corridor model that incorporates stochasticity in simulating animal movement. The model was evaluated using both a partition of the data previously set apart and independent observation data of dispersing birds. Most land cover variables (such as coniferous forest, forest edges, agricultural land, roads, settlements) and one topographic variable (topographic exposure) were significantly correlated with gene flow. Although inter‐individual relatedness inherently varies greatly and the variance explained by geographic distance and landscape structure was low, the permeability map and the corridor model significantly explained relatedness in the validation data and the spatial distribution of dispersing birds. Thus, landscape structure measurably affected within‐population gene flow in the study area. By converting these effects into spatially explicit information our model enables localizing priority areas for the preservation or restoration of metapopulation connectivity.</p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Modelling functional landscape connectivity from genetic population structure: a new spatially explicit approach</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>MODELLING LANDSCAPE CONNECTIVITY FROM GENETIC DATA</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Modelling functional landscape connectivity from genetic population structure: a new spatially explicit approach</title></titleInfo><name type="personal"><namePart type="given">VERONIKA</namePart><namePart type="family">BRAUNISCH</namePart><affiliation>Forest Research Institute of Baden‐Wuerttemberg FVA, Wonnhaldestr. 4, D‐79100 Freiburg, Germany</affiliation><affiliation>Conservation Biology, Institute of Ecology and Evolution, University of Bern, CH‐3012 Bern, Switzerland</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">GERNOT</namePart><namePart type="family">SEGELBACHER</namePart><affiliation>Department of Wildlife Ecology and Management, Albert‐Ludwigs University Freiburg, Tennenbacher Strasse 4, D‐79106 Freiburg, Germany</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">ALEXANDRE H.</namePart><namePart type="family">HIRZEL</namePart><affiliation>Centre Informatique, University of Lausanne, CH‐1015 Lausanne, Switzerland</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="article"></genre><originInfo><publisher>Blackwell Publishing Ltd</publisher><place><placeTerm type="text">Oxford, UK</placeTerm></place><dateIssued encoding="w3cdtf">2010-09</dateIssued><edition>Received 26 January 2010; revision received 8 April 2010; accepted 22 April 2010</edition><copyrightDate encoding="w3cdtf">2010</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType><extent unit="figures">6</extent><extent unit="tables">4</extent></physicalDescription><abstract lang="en">Functional connectivity between spatially disjoint habitat patches is a key factor for the persistence of species in fragmented landscapes. Modelling landscape connectivity to identify potential dispersal corridors requires information about those landscape features affecting dispersal. Here we present a new approach using spatial and genetic data of a highly fragmented population of capercaillie (Tetrao urogallus) in the Black Forest, Germany, to investigate effects of landscape structure on gene flow and to parameterize a spatially explicit corridor model for conservation purposes. Mantel tests and multiple regressions on distance matrices were employed to detect and quantify the effect of different landscape features on relatedness among individuals, while controlling for the effect of geographic distance. We extrapolated the results to an area‐wide landscape permeability map and developed a new corridor model that incorporates stochasticity in simulating animal movement. The model was evaluated using both a partition of the data previously set apart and independent observation data of dispersing birds. Most land cover variables (such as coniferous forest, forest edges, agricultural land, roads, settlements) and one topographic variable (topographic exposure) were significantly correlated with gene flow. Although inter‐individual relatedness inherently varies greatly and the variance explained by geographic distance and landscape structure was low, the permeability map and the corridor model significantly explained relatedness in the validation data and the spatial distribution of dispersing birds. Thus, landscape structure measurably affected within‐population gene flow in the study area. By converting these effects into spatially explicit information our model enables localizing priority areas for the preservation or restoration of metapopulation connectivity.</abstract><subject lang="en"><genre>keywords</genre><topic>capercaillie</topic><topic>dispersal corridors</topic><topic>habitat connectivity</topic><topic>landscape permeability</topic><topic>Tetrao urogallus</topic></subject><relatedItem type="host"><titleInfo><title>Molecular Ecology</title></titleInfo><genre type="journal">journal</genre><identifier type="ISSN">0962-1083</identifier><identifier type="eISSN">1365-294X</identifier><identifier type="DOI">10.1111/(ISSN)1365-294X</identifier><identifier type="PublisherID">MEC</identifier><part><date>2010</date><detail type="title"><title>SPECIAL ISSUE ON LANDSCAPE GENETICS</title></detail><detail type="volume"><caption>vol.</caption><number>19</number></detail><detail type="issue"><caption>no.</caption><number>17</number></detail><extent unit="pages"><start>3664</start><end>3678</end><total>4</total></extent></part></relatedItem><identifier type="istex">3285E1264D9F1D96E93CDC6513C7A8366D4A33CE</identifier><identifier type="DOI">10.1111/j.1365-294X.2010.04703.x</identifier><identifier type="ArticleID">MEC4703</identifier><accessCondition type="use and reproduction" contentType="copyright">© 2010 Blackwell Publishing Ltd</accessCondition><recordInfo><recordContentSource>WILEY</recordContentSource><recordOrigin>Blackwell Publishing Ltd</recordOrigin></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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