Landscape Ecology

, Volume 32, Issue 12, pp 2261–2279 | Cite as

Identifying environmental drivers of spatial genetic structure of the European pine marten (Martes martes)

  • Marina MergeyEmail author
  • Clara Bardonnet
  • Thomas Quintaine
  • Maxime Galan
  • Carole Bodin
  • Pauline Hubert
  • Rémi Helder
Research Article



In a global context of erosion of biodiversity, the current environmental policy in Europe is oriented towards the creation and the preservation of ecological networks for wildlife. However, most of the management guidelines arose from a structural landscape diagnostic without truly taking into consideration species’ needs.


We tested whether and how landscape elements influence the functional connectivity of landscapes for a forest specialist species, the European pine marten (Martes martes), in Northeastern France.


We collected pine marten scats and tissues from 13 evenly distributed study sites across the whole study area in order to test several types of barriers such as highways, waterways, and open agricultural fields. We crossed the results of several methods: spatial autocorrelation analysis, causal modelling framework, and clustering methods.


The study indicates significant genetic differentiation among the sampling sites. A signal of isolation by distance was detected but disappeared after partialling out landscape or barrier resistance. The only model that was fully supported by causal modelling was the one identifying waterways as the main driver of genetic differentiation. Moreover, clustering analyses indicated the presence of genetic clusters, suggesting that pine marten spatial genetic pattern could be explained by the presence of waterways but also by their reluctance to cross open fields.


The current ecological network could thus be improved by increasing permeability of waterways, in particular navigation canals, and by maintaining and restoring forested corridors in agricultural plains.


Gene flow Landscape Functional connectivity Waterway Barrier Microsatellites Martes martes 



This study has been funded by the Regional Concil of Champagne-Ardenne, by the University of Reims Champagne-Ardenne (URCA) through In Situ research program, by the French system of transmission system operators for electricity (Réseau de Transport Electrique, RTE), and by the Regional natural park of Avesnois. Data used in this work were partly produced through the technical facilities of the Centre Méditerranéen Environnement Biodiversité and of the Laboratoire des Pyrénées et des Landes. We thank all people who collaborated for samples collection and especially all hunters and trappers. We are also grateful to Eva Bellemain (SpyGen) for discussions on how to improve DNA amplification. Finally, we would like to thank Bertrand Gauffre and the two reviewers for comments that greatly improved the manuscript.


The Regional Concil of Champagne-Ardenne and the University of Reims Champagne-Ardenne through In Situ research program.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Baguette M, Blanchet S, Legrand D, Stevens VM, Turlure C (2013) Individual dispersal, landscape connectivity and ecological networks. Biol Rev 88:310–326CrossRefPubMedGoogle Scholar
  2. Balestrieri A, Remonti L, Ruiz-Gonzalez A, Gomez-Moliner BJ, Vergara M, Priogioni C (2010) Range expansion of the pine marten (Martes martes) in an agricultural landscape matrix (NW Italy). Mamm Biol 75:412–419Google Scholar
  3. Balkenhol N, Gugerli F, Cushman SA, Waits LP, Coulon A, Arntzen JW, Holderegger R, Wagner HH, Participants of the Landscape Genetics Research Agenda Workshop 2007 (2009) Identifying future research needs in landscape genetics: where to from here? Land Ecol 24:455–463Google Scholar
  4. Basto MP, Rodrigues M, Santos-Reis M, Bruford MW, Fernandes CA (2010) Isolation and characterization of 13 tetranucleotide microsatellite loci in the Stone marten (Martes foina). Conserv Genet Resour 2:317–319CrossRefGoogle Scholar
  5. Beier P (2005) Dispersal of juvenile cougars in fragmented habitat. J Wildlife Manag 59:228–237CrossRefGoogle Scholar
  6. Belkhir K, Borsa P, Chikhi L, Raufaste N, Bonhomme F (1996–2004) GENETIX 4.05, logiciel Windows TM pour la génétique des populations. Laboratoire Génome, Populations, Interactions, Université de Montpellier II, MontpellierGoogle Scholar
  7. Bennett AF (1999) Linkages in the landscape: the role of corridors and connectivity in wildlife conservation. International Union for Conservation of Nature and Natural Resources, GlandGoogle Scholar
  8. Brainerd SM (1990) The pine marten and forest fragmentation: a review and synthesis. In: Myrberget S (ed), Transaction of the 19th IUGB Congress, Trondheim, pp 421–434Google Scholar
  9. Broquet T, Ray N, Petit E, Fryxell JM, Burel F (2006) Genetic isolation by distance and landscape connectivity in the American marten (Martes americana). Landscape Ecol 21(6):877–889CrossRefGoogle Scholar
  10. Chen XY (2000) Effects of habitat fragmentation on genetic structure of plant populations and implications for the biodiversity conservation. Acta Ecol Sin 20:884–892Google Scholar
  11. Coulon A, Fitzpatrick JW, Bowman R, Stith BM, Makarewich CA, Stenzler LM, Lovette IJ (2008) Congruent population structure inferred from dispersal behaviour and intensive genetic surveys of the threatened Florida scrub-jay (Aphelocoma coerulescens). Mol Ecol 17:1685–1701CrossRefPubMedGoogle Scholar
  12. Coulon A, Guillot G, Cosson J-F, Angibault JM, Aulagnier S, Cargnelutti B, Galan M, Hewison AJ (2006) Genetic structure is influenced by landscape features: empirical evidence from a roe deer population. Mol Ecol 15:1669–1679Google Scholar
  13. Cushman SA, Landguth EL (2010) Spurious correlations and inference in landscape genetics. Mol Ecol 19:3592–3602CrossRefPubMedGoogle Scholar
  14. Cushman SA, McKelvey KS, Hayden J, Schwartz MK (2006) Gene flow in complex landscapes: testing multiple hypotheses with causal modeling. Am Nat 168:486–499CrossRefPubMedGoogle Scholar
  15. Cushman SA, Shirk AJ, Landguth EL (2013a) Landscape genetics and limiting factors. Conserv Genet 14:263–274CrossRefGoogle Scholar
  16. Cushman SA, Wasserman TN, Landguth EL, Shirk AJ (2013b) Re-evaluating causal modeling with Mantel tests in landscape genetics. Diversity 5:51–72CrossRefGoogle Scholar
  17. Davis CS, Strobeck C (1998) Isolation, variability, and cross-species amplification of polymorphic microsatellite loci in the family Mustelidae. Mol Ecol 7:1776–1778CrossRefPubMedGoogle Scholar
  18. Díaz-Muñoz SL (2012) Role of recent and old riverine barriers in fine-scale population genetic structure of Geoffroy’s tamarin (Saguinus geoffroyi) in the Panama Canal watershed. Ecol Evol 2:298–309CrossRefPubMedPubMedCentralGoogle Scholar
  19. Earl DA, von Holdt BM (2011) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361CrossRefGoogle Scholar
  20. Epps CW, Palsboll PJ, Wehausen JD, Roderick GK, Ramey RR, McCullough DR (2005) Highways block gene flow and cause a rapid decline in genetic diversity of desert bighorn sheep. Ecol Lett 8:1029–1038CrossRefGoogle Scholar
  21. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620CrossRefPubMedGoogle Scholar
  22. Fahrig L (2003) Effects of habitat fragmentation on biodiversity. Annu Rev Ecol Syst 34:487–515CrossRefGoogle Scholar
  23. Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587PubMedPubMedCentralGoogle Scholar
  24. Frantz AC, Bertouille S, Eloy MC, Licoppe A, Chaumont F, Flamand MC (2012) Comparative landscape genetic analyses show a Belgian motorway to be a gene flow barrier for red deer (Cervus elaphus), but not wild boars (Sus scrofa). Mol Ecol 14:3445–3457CrossRefGoogle Scholar
  25. Galpern P, Manseau M, Hettinga P, Wilson P, Smith K (2012) ALLELEMATCH: an R package for identifying unique multilocus genotypes where genotyping error and missing data may be present. Mol Ecol Res. doi: 10.1111/j.1755-0998.2012.03137.x Google Scholar
  26. Gillies CS, St. Clair CC (2008) Riparian corridors enhance movement of a forest specialist bird in fragmented tropical forest. Proc Natl Acad Sci 105(50):19774–19779CrossRefPubMedPubMedCentralGoogle Scholar
  27. Goudet J (1995) FSTAT (version 1.2): a computer program to calculate F-statistics. J Heredity 86(6):485–486Google Scholar
  28. Haag T, Santos AS, Sana DA, Morato RG, Cullen L Jr, Crawshaw PG Jr, De Angelo C, Di Bitetti MS, Salzano FM, Eizirik E (2010) The effect of habitat fragmentation on the genetic structure of a top predator: loss of diversity and high differentiation among remnant populations of Atlantic Forest jaguars (Panthera onca). Mol Ecol 19:4906–4921Google Scholar
  29. Holderegger R, Wagner HH (2008) Landscape genetics. Bioscience 58:199–207CrossRefGoogle Scholar
  30. Hubisz MJ, Falush D, Stephens M, Pritchard JK (2009) Inferring weak population structure with the assistance of sample group information. Mol Ecol Resour 9:1322–1332CrossRefPubMedPubMedCentralGoogle Scholar
  31. Jakobsson M, Rosenberg NA (2007) CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinform 23:1801–1806CrossRefGoogle Scholar
  32. Jombart T (2008) Adegenet: a R package for the multivariate analysis of genetic markers. Bioinform 24:1403–1405CrossRefGoogle Scholar
  33. Kimura M, Weiss GH (1964) The stepping stone model of population structure and the decrease of genetic correlation with distance. Genetics 49:561–576PubMedPubMedCentralGoogle Scholar
  34. Kindlmann P, Burel F (2008) Connectivity measures: a review. Landscape Ecol 23:879–890Google Scholar
  35. Larroque J, Ruette S, Vandel J-M, Devillard S (2016) Divergent landscape effects on genetic differentiation in two populations of the European pine marten (Martes martes). Landscape Ecol 31(3):517–531CrossRefGoogle Scholar
  36. Legendre P (1993) Spatial auto-correlation: trouble or newparadigm. Ecology 74:1659–1673CrossRefGoogle Scholar
  37. Legendre P, Trousselier M (1988) Aquatic heterotrophic bacteria: modeling in the presence of spatial autocorrelation. Limnol Oceanogr 33:1055–1067CrossRefGoogle Scholar
  38. Lindenmayer D, Hobbs RJ, Montague-Drake R, Alexandra J,  Bennett A, Burgman M, Cale P, Calhoun A, Cramer V, Cullen P, Driscoll D, Fahrig L, Fischer J, Franklin J, Haila Y, Hunter M, Gibbons P, Lake S, Luck G, MacGregor G, McIntyre S, Mac Nally R, Manning A, Miller J, Mooney H, Noss R, Possingham H, Saunders D, Schmiegelow F, Scott M, Simberloff D, Sisk T, Tabor G, Walker B, Wiens J, Woinarski J, Zavaleta E (2008) A checklist for ecological management of landscapes for conservation. Ecol Lett 11:78–91Google Scholar
  39. Luoy D, Habel JC, Schmitt T, Assmann T, Meyer M, Müller P (2007) Strongly diverging population genetic patterns of three skipper species: role of habitat fragmentation and dispersal ability. Conserv Genet 8:671–681CrossRefGoogle Scholar
  40. Manel S, Schwartz MK, Luikart G, Taberlet P (2003) Landscape genetics: combining landscape ecology and population genetics. Trends Ecol Evol 18:189–197CrossRefGoogle Scholar
  41. McRae BH, Dickson BG, Keitt TH, Shah VB (2008) Using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology 89:2712–2724CrossRefPubMedGoogle Scholar
  42. Mergey M, Helder R, Roeder JJ (2011) Effect of forest fragmentation on space use patterns in the European pine marten (Martes martes). J Mamm 92:328–335CrossRefGoogle Scholar
  43. Mergey M, Larroque J, Ruette S, Vandel J, Helder R, Queney G, Devillard S (2012) Linking habitat characteristics with genetic diversity of the European pine marten (Martes martes) in France. Eur J Wildl Res 58:909–922CrossRefGoogle Scholar
  44. Natali C, Banchi E, Ciofi C, Manzo E, Bartolommei P, Cozzolino R (2010) Characterization of 13 polymorphic microsatellite loci in the European pine marten Martes martes. Conserv Genet Resour 2:397–399CrossRefGoogle Scholar
  45. Nei M (1978) Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89:583–590Google Scholar
  46. Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H (2015) Vegan: Community Ecology Package. R package version 2.2-1. University of Oulu: Oulu, Finland.
  47. Paetkau D, Strobeck C (1994) Microsatellite analysis of genetic variation in black bear populations. Mol Ecol 3:489–495CrossRefPubMedGoogle Scholar
  48. Peakall R, Smouse PE (2005) Genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes 6:288–295CrossRefGoogle Scholar
  49. Pertoldi C, Barker SF, Madsen AB, Jørgensen H, Randi E, Muñoz J, Baagoe HJ, Loeschcke V (2008) Spatio-temporal population genetics of the Danish pine marten (Martes martes). Biol J Linn Soc 93:457–464CrossRefGoogle Scholar
  50. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  51. R Development Core Team (2007) R: a language and environment for statistical computing. R foundation for Statistical Computing, ViennaGoogle Scholar
  52. Rayfield B, Fortin MJ, Fall A (2010) The sensitivity of least-cost habitat graphs to relative cost surface values. Landscape Ecol 25:519–532CrossRefGoogle Scholar
  53. Rosenberg NA (2004) DISTRUCT: a program for the graphical display of population structure. Mol Ecol Notes 4:137–138CrossRefGoogle Scholar
  54. Ruiz-Gonzalez A, Cushman SA, Madeira MJ, Randi E, Gómez-Moliner BJ (2015) Isolation by distance, resistance and/or clusters? Lessons learned from a forest-dwelling carnivore inhabiting a heterogeneous landscape. Mol Ecol 24:5110–5129CrossRefPubMedGoogle Scholar
  55. Ruiz-González A, Gurrutxaga M, Cushman SA, Madeira MJ, Randi E, Gómez-Moliner BJ (2014) Landscape genetics for the empirical assessment of resistance surfaces: the European pine marten (Martes martes) as a target-species of a regional ecological network. PLoS ONE 9:e110552CrossRefPubMedPubMedCentralGoogle Scholar
  56. Schwartz MK, McKelvey KS (2009) Why sampling scheme matters: the effect of sampling scheme on landscape genetic results. Conserv Genet 10:441–452CrossRefGoogle Scholar
  57. Slatkin M (1973) Gene flow and selection in a cline. Genetics 75:733–756PubMedPubMedCentralGoogle Scholar
  58. Smouse P, Long J, Sokal R (1986) Multiple regression and correlation extensions of the Mantel test of matrix correspondence. Syst Zool 35:627–632CrossRefGoogle Scholar
  59. Smouse PE, Peakall R (1999) Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure. Heredity 82:561–573CrossRefPubMedGoogle Scholar
  60. Smouse PE, Peakall R, Gonzales E (2008) A heterogeneity test for fine-scale genetic structure. Mol Ecol 17(14):3389–3400CrossRefPubMedGoogle Scholar
  61. Storfer A, Murphy MA, Evans JS, Goldberg CS, Robinson S, Spear SF, Dezzani R, Delmelle E, Vierling L, Waits LP (2007) Putting the ‘landscape’ in landscape genetics. Heredity 98:128–142Google Scholar
  62. Sunnucks P (2000) Efficient genetic markers for populationbiology. Trends Ecol Evol 15:199–203CrossRefPubMedGoogle Scholar
  63. Templeton AR (2006) Population genetics and microevolutionary theory. Wiley, HobokenCrossRefGoogle Scholar
  64. Valière N (2002) Gimlet: a computer program for analysing genetic individual identification data. Mol Ecol Notes 2:377–379Google Scholar
  65. Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4:535–538CrossRefGoogle Scholar
  66. Virgos E, Zalewski A, Rosalino LM, Mergey M (2012) Habitat ecology of genus Martes in Europe: a review of the evidences. In: Aubry KB, Zielinski WJ, Proulx G, Buskirk SW (eds) Biology and Conservation of Martens, sables, and fishers. A new synthesis. Cornell University Press, New York, pp 255–266Google Scholar
  67. Wade TG, Riitters KH, Wickham JD, Jones KB (2003) Distribution and causes of global forest fragmentation. Conserv Ecol 7:7CrossRefGoogle Scholar
  68. Waits LP, Luikart G, Taberlet P (2001) Estimating the probability of identity among genotypes in natural populations: cautions and guidelines. Mol Ecol 10:249–256CrossRefPubMedGoogle Scholar
  69. Walker CW, Vila C, Landa A, Linden M, Ellegren H (2001) Genetic variation and population structure in Scandinavian wolverine (Gulo gulo) populations. Mol Ecol 10(1):53–63CrossRefPubMedGoogle Scholar
  70. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370PubMedGoogle Scholar
  71. Wright S (1943) Isolation by distance. Genetics 28:114–138PubMedPubMedCentralGoogle Scholar
  72. Zalewski A, Jedrzejewski W (2006) Spatial organisation and dynamics of the pine marten Martes martes population in Bialowieza Forest (E Poland) compared with other European woodlands. Ecography 29:31–43CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  • Marina Mergey
    • 1
    Email author
  • Clara Bardonnet
    • 1
  • Thomas Quintaine
    • 1
  • Maxime Galan
    • 2
  • Carole Bodin
    • 1
  • Pauline Hubert
    • 1
  • Rémi Helder
    • 1
  1. 1.URCA-CERFEBoult-Aux-BoisFrance
  2. 2.CBGP-INRAMontferrier-Sur-Lez CedexFrance

Personalised recommendations