Influence of sampling scheme on the inference of sex-biased gene flow in the American badger (Taxidea taxus)

Population genetics has fueled a substantial growth in studies of dispersal, a life-history trait that has important applications in ecology and evolution. Mammals typically exhibit male-biased gene flow, so this pattern often serves as a null hypothesis in empirical studies. Estimation of dispersal...

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Published inCanadian journal of zoology Vol. 90; no. 10; pp. 1231 - 1242
Main Authors Kierepka, E.M., Latch, E.K., Swanson, B.J.
Format Journal Article
LanguageEnglish
Published Ottawa NRC Research Press 01.10.2012
National Research Council of Canada
Canadian Science Publishing NRC Research Press
Subjects
American badger
Animals
autocorrélation spatiale
badgers
Biological and medical sciences
blaireau d’Amérique
Dispersal
dispersion biaisée selon le sexe
evolution
females
Fundamental and applied biological sciences. Psychology
Gene flow
Genetic research
Genetic structure
Genetics
Genetics of eukaryotes. Biological and molecular evolution
genotyping
heterozygosity
Inbreeding
Life history
males
Mammals
Methods
microsatellite repeats
philopatry
Population density
Population genetics
Population genetics, reproduction patterns
sampling
sex-biased dispersal
Simulation
spatial autocorrelation
Statistical sampling
statistics
Taxidea taxus
territoriality
Vertebrata
Zoology
échantillonnage
United States
Carnivora
Vertebrata
Gene flow
Mammalia
Methodological bias
Sexual dimorphism
Method
Sampling
Dispersion
Online AccessGet full text
ISSN1480-3283
0008-4301
1480-3283
0008-4301
DOI10.1139/z2012-094

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Abstract Population genetics has fueled a substantial growth in studies of dispersal, a life-history trait that has important applications in ecology and evolution. Mammals typically exhibit male-biased gene flow, so this pattern often serves as a null hypothesis in empirical studies. Estimation of dispersal using population genetics is not without biases, so we utilized a combination of population genetic methods and simulations to evaluate gene flow within the American badger (Taxidea taxus (Schreber, 1777)), a highly elusive and poorly understood mustelid. A total of 132 badgers captured between 2001 and 2002 were genotyped at nine microsatellite loci to investigate fine-scale genetic structure consistent with philopatry in females and dispersal in males. Resultant genetic patterns were largely consistent with a panmictic population with little evidence for sex-biased dispersal, and simulations confirmed that our sampling scheme did not substantially impact our statistics. An overall deficiency of heterozygotes was observed across the Lower Peninsula, which indicates either a Wahlund effect, mixing of separate populations, or inbreeding. Our study emphasizes the importance in deciphering between actual behavioral mechanisms and sampling effects when interpreting genetic data to understand other factors that influence dispersal like population density and territoriality.
AbstractList Population genetics has fueled a substantial growth in studies of dispersal, a life-history trait that has important applications in ecology and evolution. Mammals typically exhibit male-biased gene flow, so this pattern often serves as a null hypothesis in empirical studies. Estimation of dispersal using population genetics is not without biases, so we utilized a combination of population genetic methods and simulations to evaluate gene flow within the American badger (Taxidea taxus (Schreber, 1777)), a highly elusive and poorly understood mustelid. A total of 132 badgers captured between 2001 and 2002 were genotyped at nine microsatellite loci to investigate fine-scale genetic structure consistent with philopatry in females and dispersal in males. Resultant genetic patterns were largely consistent with a panmictic population with little evidence for sex-biased dispersal, and simulations confirmed that our sampling scheme did not substantially impact our statistics. An overall deficiency of heterozygotes was observed across the Lower Peninsula, which indicates either a Wahlund effect, mixing of separate populations, or inbreeding. Our study emphasizes the importance in deciphering between actual behavioral mechanisms and sampling effects when interpreting genetic data to understand other factors that influence dispersal like population density and territoriality. Key words: Taxidea taxus, American badger, sex-biased dispersal, sampling, spatial autocorrelation. La genetique des populations a entrame une augmentation marquee des etudes sur la dispersion, un caractere du cycle biologique qui offre d'importantes applications en ecologie et en science de l'evolution. Les mammiferes presentent typiquement un flux genetique biaise vers les males, cette situation servant donc souvent d'hypothese nulle dans les etudes empiriques. L'estimation de la dispersion a l'aide de la genetique des populations n'est pas sans biais. C'est pourquoi nous avons utilise une combinaison de methodes de genetique des populations et de simulations pour evaluer le flux genetique chez le blaireau d'Amerique (Taxidea taxus (Schreber, 1777)), un mustelide tres discret et meconnu. Un total de 132 blaireaux captures de 2001 a 2002 ont ete genotypes sur neuf sites microsatellites afin d'etudier la structure genetique fine associee a la philopatrie chez les femelles et a la dispersion chez les males. Les patrons genetiques en decoulant concordaient globalement avec une population panmictique, mais tres peu avec une dispersion biaisee selon le sexe. Des simulations ont en outre confirme que notre schema d'echantillonnage n'avait pas une incidence importante sur les statistiques obtenues. Un deficit global d' heterozygotes a ete observe a l' echelle de la peninsule inferieure du Michigan, ce qui indique soit un effet Wahlund, soit le melange de populations distinctes, soit de la consanguinite. Notre etude souligne l'importance de distinguer les mecanismes comportementaux reels des effets d'echantillonnage au moment d'interpreter des donnees genetiques afin de comprendre les autres facteurs qui influencent la dispersion, tels que la densite de population et la territorialite. Mots-cles: Taxidea taxus, blaireau d'Amerique, dispersion biaisee selon le sexe, echantillonnage, autocorrelation spatiale. [Traduit par la Redaction]
Population genetics has fueled a substantial growth in studies of dispersal, a life-history trait that has important applications in ecology and evolution. Mammals typically exhibit male-biased gene flow, so this pattern often serves as a null hypothesis in empirical studies. Estimation of dispersal using population genetics is not without biases, so we utilized a combination of population genetic methods and simulations to evaluate gene flow within the American badger (Taxidea taxus (Schreber, 1777)), a highly elusive and poorly understood mustelid. A total of 132 badgers captured between 2001 and 2002 were genotyped at nine microsatellite loci to investigate fine-scale genetic structure consistent with philopatry in females and dispersal in males. Resultant genetic patterns were largely consistent with a panmictic population with little evidence for sex-biased dispersal, and simulations confirmed that our sampling scheme did not substantially impact our statistics. An overall deficiency of heterozygotes was observed across the Lower Peninsula, which indicates either a Wahlund effect, mixing of separate populations, or inbreeding. Our study emphasizes the importance in deciphering between actual behavioral mechanisms and sampling effects when interpreting genetic data to understand other factors that influence dispersal like population density and territoriality.Original Abstract: La genetique des populations a entraine une augmentation marquee des etudes sur la dispersion, un caractere du cycle biologique qui offre d'importantes applications en ecologie et en science de l'evolution. Les mammiferes presentent typiquement un flux genetique biaise vers les males, cette situation servant donc souvent d'hypothese nulle dans les etudes empiriques. L'estimation de la dispersion a l'aide de la genetique des populations n'est pas sans biais. C'est pourquoi nous avons utilise une combinaison de methodes de genetique des populations et de simulations pour evaluer le flux genetique chez le blaireau d'Amerique (Taxidea taxus (Schreber, 1777)), un mustelide tres discret et meconnu. Un total de 132 blaireaux captures de 2001 a 2002 ont ete genotypes sur neuf sites microsatellites afin d'etudier la structure genetique fine associee a la philopatrie chez les femelles et a la dispersion chez les males. Les patrons genetiques en decoulant concordaient globalement avec une population panmictique, mais tres peu avec une dispersion biaisee selon le sexe. Des simulations ont en outre confirme que notre schema d'echantillonnage n'avait pas une incidence importante sur les statistiques obtenues. Un deficit global d'heterozygotes a ete observe a l'echelle de la peninsule inferieure du Michigan, ce qui indique soit un effet Wahlund, soit le melange de populations distinctes, soit de la consanguinite. Notre etude souligne l'importance de distinguer les mecanismes comportementaux reels des effets d'echantillonnage au moment d'interpreter des donnees genetiques afin de comprendre les autres facteurs qui influencent la dispersion, tels que la densite de population et la territorialite.
Population genetics has fueled a substantial growth in studies of dispersal, a life-history trait that has important applications in ecology and evolution. Mammals typically exhibit male-biased gene flow, so this pattern often serves as a null hypothesis in empirical studies. Estimation of dispersal using population genetics is not without biases, so we utilized a combination of population genetic methods and simulations to evaluate gene flow within the American badger ( Taxidea taxus (Schreber, 1777)), a highly elusive and poorly understood mustelid. A total of 132 badgers captured between 2001 and 2002 were genotyped at nine microsatellite loci to investigate fine-scale genetic structure consistent with philopatry in females and dispersal in males. Resultant genetic patterns were largely consistent with a panmictic population with little evidence for sex-biased dispersal, and simulations confirmed that our sampling scheme did not substantially impact our statistics. An overall deficiency of heterozygotes was observed across the Lower Peninsula, which indicates either a Wahlund effect, mixing of separate populations, or inbreeding. Our study emphasizes the importance in deciphering between actual behavioral mechanisms and sampling effects when interpreting genetic data to understand other factors that influence dispersal like population density and territoriality.
Population genetics has fueled a substantial growth in studies of dispersal, a life-history trait that has important applications in ecology and evolution. Mammals typically exhibit male-biased gene flow, so this pattern often serves as a null hypothesis in empirical studies. Estimation of dispersal using population genetics is not without biases, so we utilized a combination of population genetic methods and simulations to evaluate gene flow within the American badger (Taxidea taxus (Schreber, 1777)), a highly elusive and poorly understood mustelid. A total of 132 badgers captured between 2001 and 2002 were genotyped at nine microsatellite loci to investigate fine-scale genetic structure consistent with philopatry in females and dispersal in males. Resultant genetic patterns were largely consistent with a panmictic population with little evidence for sex-biased dispersal, and simulations confirmed that our sampling scheme did not substantially impact our statistics. An overall deficiency of heterozygotes was observed across the Lower Peninsula, which indicates either a Wahlund effect, mixing of separate populations, or inbreeding. Our study emphasizes the importance in deciphering between actual behavioral mechanisms and sampling effects when interpreting genetic data to understand other factors that influence dispersal like population density and territoriality.
Population genetics has fueled a substantial growth in studies of dispersal, a life-history trait that has important applications in ecology and evolution. Mammals typically exhibit male-biased gene flow, so this pattern often serves as a null hypothesis in empirical studies. Estimation of dispersal using population genetics is not without biases, so we utilized a combination of population genetic methods and simulations to evaluate gene flow within the American badger (Taxidea taxus (Schreber, 1777)), a highly elusive and poorly understood mustelid. A total of 132 badgers captured between 2001 and 2002 were genotyped at nine microsatellite loci to investigate fine-scale genetic structure consistent with philopatry in females and dispersal in males. Resultant genetic patterns were largely consistent with a panmictic population with little evidence for sex-biased dispersal, and simulations confirmed that our sampling scheme did not substantially impact our statistics. An overall deficiency of heterozygotes was observed across the Lower Peninsula, which indicates either a Wahlund effect, mixing of separate populations, or inbreeding. Our study emphasizes the importance in deciphering between actual behavioral mechanisms and sampling effects when interpreting genetic data to understand other factors that influence dispersal like population density and territoriality. [PUBLICATION ABSTRACT]
Abstract_FL La génétique des populations a entraîné une augmentation marquée des études sur la dispersion, un caractère du cycle biologique qui offre d’importantes applications en écologie et en science de l’évolution. Les mammifères présentent typiquement un flux génétique biaisé vers les mâles, cette situation servant donc souvent d’hypothèse nulle dans les études empiriques. L’estimation de la dispersion à l’aide de la génétique des populations n’est pas sans biais. C’est pourquoi nous avons utilisé une combinaison de méthodes de génétique des populations et de simulations pour évaluer le flux génétique chez le blaireau d’Amérique ( Taxidea taxus (Schreber, 1777)), un mustélidé très discret et méconnu. Un total de 132 blaireaux capturés de 2001 à 2002 ont été génotypés sur neuf sites microsatellites afin d’étudier la structure génétique fine associée à la philopatrie chez les femelles et à la dispersion chez les mâles. Les patrons génétiques en découlant concordaient globalement avec une population panmictique, mais très peu avec une dispersion biaisée selon le sexe. Des simulations ont en outre confirmé que notre schéma d’échantillonnage n’avait pas une incidence importante sur les statistiques obtenues. Un déficit global d’hétérozygotes a été observé à l’échelle de la péninsule inférieure du Michigan, ce qui indique soit un effet Wahlund, soit le mélange de populations distinctes, soit de la consanguinité. Notre étude souligne l’importance de distinguer les mécanismes comportementaux réels des effets d’échantillonnage au moment d’interpréter des données génétiques afin de comprendre les autres facteurs qui influencent la dispersion, tels que la densité de population et la territorialité.
Audience Academic
Author Kierepka, E.M.
Swanson, B.J.
Latch, E.K.
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  fullname: Swanson, B.J.
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Cites_doi 10.1139/Z09-072
10.1093/oso/9780198540663.001.0001
10.1098/rspb.1997.0019
10.1007/s10592-005-9056-y
10.1046/j.1365-294X.2001.01184.x
10.1007/s10592-005-9098-1
10.1111/j.1471-8286.2005.01031.x
10.1016/S0003-3472(80)80103-5
10.1139/Z10-024
10.1111/j.1365-294X.1995.tb00214.x
10.2307/2409206
10.1046/j.1365-294x.1999.00740.x
10.1214/aos/1013699998
10.1007/s00442-006-0384-5
10.1111/j.1461-0248.2008.01267.x
10.1146/annurev.ecolsys.110308.120324
10.1644/05-MAMM-A-427R1.1
10.1093/jhered/92.3.301
10.1111/j.1365-294X.2009.04386.x
10.1046/j.1365-2052.1998.00221.x
10.1016/0169-5347(96)10028-8
10.1093/oso/9780198506607.001.0001
10.1111/j.1471-8286.2005.01155.x
10.1111/j.1365-294X.2010.04678.x
10.1086/303296
10.1111/j.1365-294X.2005.02553.x
10.1086/284267
10.1111/j.1365-294X.2008.03950.x
10.2307/5959
10.1111/j.1365-294X.2005.02598.x
10.1111/j.1471-8286.2004.00796.x
10.1111/j.1365-294X.2004.02101.x
10.1007/BF00317511
10.2307/2420060
10.2193/2006-406
10.1644/BRB-129
10.1093/oxfordjournals.jhered.a111573
10.1046/j.1471-8286.2002.00305.x
10.1038/hdy.2009.136
10.1046/j.1365-294X.2002.01496.x
10.1111/j.1365-294X.2006.03152.x
10.1111/j.1365-294X.2010.04656.x
10.1046/j.1365-294X.2004.02076.x
10.1007/s10592-008-9622-1
10.18637/jss.v007.i10
10.1111/j.1365-294X.2008.03930.x
10.1007/BF00031693
10.1111/j.1601-5223.1928.tb02483.x
10.1093/genetics/28.2.114
10.2307/1382852
10.1111/j.1469-1795.2006.00037.x
10.1038/sj.hdy.6800545
10.1111/j.1365-294X.2011.05042.x
10.1046/j.1365-294X.1999.00701_2.x
10.1111/j.1365-2664.2008.01606.x
10.1038/sj.hdy.6885180
10.1046/j.1365-294x.1998.00515.x
10.1093/beheco/arg097
10.1093/genetics/155.2.945
10.1111/j.0014-3820.2003.tb00327.x
10.1007/s10592-006-9126-9
10.2307/2445869
10.1007/s10592-004-1976-4
10.1038/sj.hdy.6800060
10.1007/s10980-005-0148-3
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Keywords Carnivora
Vertebrata
Gene flow
Mammalia
Methodological bias
Sexual dimorphism
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Sampling
Dispersion
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References refg40/ref40
refg65/ref65
refg22/ref22
refg36/ref36
refg51/ref51
Bonnet E. (refg5/ref5) 2002; 7
refg11/ref11
refg25/ref25
refg6/ref6
refg15/ref15
refg29/ref29
refg43/ref43
refg26/ref26
refg14/ref14
refg54/ref54
refg57/ref57
refg37/ref37
refg19/ref19
refg21/ref21
refg7/ref7
refg46/ref46
refg48/ref48
refg10/ref10
refg1/ref1
refg32/ref32
Davis C.S. (refg18/ref18) 1998; 7
refg35/ref35
refg61/ref61
refg53/ref53
refg42/ref42
refg24/ref24
Benjamini Y. (refg3/ref3) 2001; 29
refg16/ref16
refg50/ref50
refg64/ref64
refg67/ref67
refg13/ref13
refg27/ref27
refg56/ref56
refg38/ref38
Raymond M. (refg59/ref59) 1995; 86
Wahlund S. (refg300/ref300) 1928; 11
refg45/ref45
refg49/ref49
refg31/ref31
refg9/ref9
refg34/ref34
Messick J.P. (refg47/ref47) 1981; 76
refg52/ref52
refg8/ref8
Pritchard J.K. (refg55/ref55) 2000; 155
refg60/ref60
refg63/ref63
refg2/ref2
refg23/ref23
refg17/ref17
refg30/ref30
refg66/ref66
Wright S. (refg68/ref68) 1943; 28
refg12/ref12
refg28/ref28
refg41/ref41
refg39/ref39
Duffy A.J. (refg20/ref20) 1998; 29
refg62/ref62
refg44/ref44
refg58/ref58
refg33/ref33
References_xml – ident: refg19/ref19
  doi: 10.1139/Z09-072
– ident: refg35/ref35
  doi: 10.1093/oso/9780198540663.001.0001
– ident: refg21/ref21
– ident: refg24/ref24
  doi: 10.1098/rspb.1997.0019
– ident: refg49/ref49
  doi: 10.1007/s10592-005-9056-y
– ident: refg65/ref65
  doi: 10.1046/j.1365-294X.2001.01184.x
– ident: refg43/ref43
  doi: 10.1007/s10592-005-9098-1
– ident: refg34/ref34
  doi: 10.1111/j.1471-8286.2005.01031.x
– ident: refg33/ref33
  doi: 10.1016/S0003-3472(80)80103-5
– ident: refg14/ref14
  doi: 10.1139/Z10-024
– ident: refg52/ref52
  doi: 10.1111/j.1365-294X.1995.tb00214.x
– ident: refg58/ref58
  doi: 10.2307/2409206
– ident: refg39/ref39
  doi: 10.1046/j.1365-294x.1999.00740.x
– volume: 29
  start-page: 1165
  year: 2001
  ident: refg3/ref3
  publication-title: Ann. Stat.
  doi: 10.1214/aos/1013699998
– ident: refg63/ref63
  doi: 10.1007/s00442-006-0384-5
– ident: refg12/ref12
  doi: 10.1111/j.1461-0248.2008.01267.x
– ident: refg7/ref7
  doi: 10.1146/annurev.ecolsys.110308.120324
– ident: refg17/ref17
  doi: 10.1644/05-MAMM-A-427R1.1
– ident: refg1/ref1
  doi: 10.1093/jhered/92.3.301
– ident: refg53/ref53
  doi: 10.1111/j.1365-294X.2009.04386.x
– volume: 29
  start-page: 63
  issue: 1
  year: 1998
  ident: refg20/ref20
  publication-title: Anim. Genet.
  doi: 10.1046/j.1365-2052.1998.00221.x
– ident: refg57/ref57
  doi: 10.1016/0169-5347(96)10028-8
– ident: refg11/ref11
  doi: 10.1093/oso/9780198506607.001.0001
– ident: refg50/ref50
  doi: 10.1111/j.1471-8286.2005.01155.x
– ident: refg22/ref22
  doi: 10.1111/j.1365-294X.2010.04678.x
– ident: refg54/ref54
  doi: 10.1086/303296
– ident: refg23/ref23
  doi: 10.1111/j.1365-294X.2005.02553.x
– ident: refg8/ref8
  doi: 10.1086/284267
– ident: refg30/ref30
  doi: 10.1111/j.1365-294X.2008.03950.x
– ident: refg67/ref67
  doi: 10.2307/5959
– ident: refg6/ref6
  doi: 10.1111/j.1365-294X.2005.02598.x
– ident: refg40/ref40
  doi: 10.1111/j.1471-8286.2004.00796.x
– ident: refg2/ref2
  doi: 10.1111/j.1365-294X.2004.02101.x
– ident: refg48/ref48
  doi: 10.1007/BF00317511
– ident: refg46/ref46
  doi: 10.2307/2420060
– ident: refg38/ref38
  doi: 10.2193/2006-406
– ident: refg41/ref41
  doi: 10.1644/BRB-129
– volume: 86
  start-page: 248
  issue: 3
  year: 1995
  ident: refg59/ref59
  publication-title: J. Hered.
  doi: 10.1093/oxfordjournals.jhered.a111573
– ident: refg36/ref36
  doi: 10.1046/j.1471-8286.2002.00305.x
– ident: refg29/ref29
  doi: 10.1038/hdy.2009.136
– ident: refg32/ref32
  doi: 10.1046/j.1365-294X.2002.01496.x
– ident: refg44/ref44
  doi: 10.1111/j.1365-294X.2006.03152.x
– ident: refg15/ref15
  doi: 10.1111/j.1365-294X.2010.04656.x
– ident: refg64/ref64
  doi: 10.1046/j.1365-294X.2004.02076.x
– ident: refg60/ref60
  doi: 10.1007/s10592-008-9622-1
– volume: 7
  start-page: 1
  issue: 10
  year: 2002
  ident: refg5/ref5
  publication-title: J. Stat. Softw.
  doi: 10.18637/jss.v007.i10
– ident: refg13/ref13
  doi: 10.1111/j.1365-294X.2008.03930.x
– ident: refg27/ref27
  doi: 10.1007/BF00031693
– volume: 11
  start-page: 65
  year: 1928
  ident: refg300/ref300
  publication-title: Hereditas
  doi: 10.1111/j.1601-5223.1928.tb02483.x
– volume: 28
  start-page: 114
  issue: 2
  year: 1943
  ident: refg68/ref68
  publication-title: Genetics
  doi: 10.1093/genetics/28.2.114
– ident: refg31/ref31
  doi: 10.2307/1382852
– ident: refg42/ref42
  doi: 10.1111/j.1469-1795.2006.00037.x
– ident: refg66/ref66
– volume: 76
  start-page: 3
  year: 1981
  ident: refg47/ref47
  publication-title: Wildl. Monogr.
– ident: refg16/ref16
  doi: 10.1038/sj.hdy.6800545
– ident: refg62/ref62
  doi: 10.1111/j.1365-294X.2011.05042.x
– ident: refg26/ref26
  doi: 10.1046/j.1365-294X.1999.00701_2.x
– ident: refg28/ref28
  doi: 10.1111/j.1365-2664.2008.01606.x
– ident: refg61/ref61
  doi: 10.1038/sj.hdy.6885180
– volume: 7
  start-page: 1776
  issue: 12
  year: 1998
  ident: refg18/ref18
  publication-title: Mol. Ecol.
  doi: 10.1046/j.1365-294x.1998.00515.x
– ident: refg25/ref25
  doi: 10.1093/beheco/arg097
– volume: 155
  start-page: 945
  issue: 2
  year: 2000
  ident: refg55/ref55
  publication-title: Genetics
  doi: 10.1093/genetics/155.2.945
– ident: refg51/ref51
  doi: 10.1111/j.0014-3820.2003.tb00327.x
– ident: refg9/ref9
  doi: 10.1007/s10592-006-9126-9
– ident: refg45/ref45
  doi: 10.2307/2445869
– ident: refg10/ref10
  doi: 10.1007/s10592-004-1976-4
– ident: refg56/ref56
  doi: 10.1038/sj.hdy.6800060
– ident: refg37/ref37
  doi: 10.1007/s10980-005-0148-3
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Snippet Population genetics has fueled a substantial growth in studies of dispersal, a life-history trait that has important applications in ecology and evolution....
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SubjectTerms American badger
Animals
autocorrélation spatiale
badgers
Biological and medical sciences
blaireau d’Amérique
Dispersal
dispersion biaisée selon le sexe
evolution
females
Fundamental and applied biological sciences. Psychology
Gene flow
Genetic research
Genetic structure
Genetics
Genetics of eukaryotes. Biological and molecular evolution
genotyping
heterozygosity
Inbreeding
Life history
males
Mammals
Methods
microsatellite repeats
philopatry
Population density
Population genetics
Population genetics, reproduction patterns
sampling
sex-biased dispersal
Simulation
spatial autocorrelation
Statistical sampling
statistics
Taxidea taxus
territoriality
Vertebrata
Zoology
échantillonnage
Title Influence of sampling scheme on the inference of sex-biased gene flow in the American badger (Taxidea taxus)
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