Conservation Genetics

, Volume 14, Issue 2, pp 355–367 | Cite as

Landscape-level comparison of genetic diversity and differentiation in a small mammal inhabiting different fragmented landscapes of the Brazilian Atlantic Forest

  • Niko Balkenhol
  • Renata Pardini
  • Cintia Cornelius
  • Fabiano Fernandes
  • Simone SommerEmail author
Research Article


Habitat loss and fragmentation can have detrimental effects on all levels of biodiversity, including genetic variation. Most studies that investigate genetic effects of habitat loss and fragmentation focus on analysing genetic data from a single landscape. However, our understanding of habitat loss effects on landscape-wide patterns of biodiversity would benefit from studies that are based on quantitative comparisons among multiple study landscapes. Here, we use such a landscape-level study design to compare genetic variation in the forest-specialist marsupial Marmosops incanus from four 10,000-hectare Atlantic forest landscapes which differ in the amount of their remaining native forest cover (86, 49, 31, 11 %). Additionally, we used a model selection framework to evaluate the influence of patch characteristics on genetic variation within each landscape. We genotyped 529 individuals with 12 microsatellites to statistically compare estimates of genetic diversity and genetic differentiation in populations inhabiting different forest patches within the landscapes. Our study indicates that before the extinction of the specialist species (here in the 11 % landscape) genetic diversity is significantly reduced in the 31 % landscape, while genetic differentiation is significantly higher in the 49 and 31 % landscapes compared to the 86 % landscape. Results further provide evidence for non-proportional responses of genetic diversity and differentiation to increasing habitat loss, and suggest that local patch isolation impacts gene flow and genetic connectivity only in the 31 % landscape. These results have high relevance for analysing landscape genetic relationships and emphasize the importance of landscape-level study designs for understanding habitat loss effects on all levels of biodiversity.


Landscape genetics Landscape connectivity Meta-population Model selection Patch metrics Marsupial Marmosops incanus 



This study is part of the German-Brazilian research project BIOCAPSP (‘Biodiversity conservation in fragmented landscapes on the Atlantic Plateau of São Paulo’), and was funded by the German Federal Ministry of Education and Research (BMBF 01 LB 0202, 01 LB 0202B, PI Simone Sommer), the National Council for Scientific and Technological Development (CNPq, 690144/01-6), and São Paulo Research Foundation (FAPESP, 05/56555-4). We are grateful to Jean Paul Metzger, Christoph Knogge, and Klaus Henle for logistic support. We would like to thank Anke Schmidt and Ramona Taubert for assistance in the genetic laboratory analyses, and Adriana A. Bueno, Thomas Püttker, Fabiana Umetsu, Bruno T. Pinotti and field assistants for helping with field work. The comments and suggestions of the associate editor Craig Primmer and two anonymous referees considerably improved the manuscript.

Supplementary material

10592_2013_454_MOESM1_ESM.doc (240 kb)
Supplementary material 1 (DOC 240 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Niko Balkenhol
    • 1
    • 2
  • Renata Pardini
    • 3
  • Cintia Cornelius
    • 4
    • 5
  • Fabiano Fernandes
    • 1
    • 3
  • Simone Sommer
    • 1
    Email author
  1. 1.Leibniz-Institute for Zoo and Wildlife Research (IZW), Evolutionary GeneticsBerlinGermany
  2. 2.Department of Forest Zoology & Forest ConservationGeorg-August-University of GoettingenGoettingenGermany
  3. 3.Departmento de ZoologiaInstituto de Biociências, Universidade de São Paulo, Rua do MatãoSão PauloBrazil
  4. 4.Departmento de EcologiaInstituto de Biociências, Universidade de São Paulo, Rua do MatãoSão PauloBrazil
  5. 5.Departmento de Biologia, Instituto de Ciências BiológicasUniversidade Federal do AmazonasManausBrazil

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