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Combining genetic non-invasive sampling with spatially explicit capture-recapture models for density estimation of a patchily distributed small mammal

  • Helena Sabino-Marques
  • Clara Mendes Ferreira
  • Joana Paupério
  • Pedro Costa
  • Soraia Barbosa
  • Cláudia Encarnação
  • Russell Alpizar-Jara
  • Paulo Célio Alves
  • Jeremy B. Searle
  • António Mira
  • Pedro Beja
  • Ricardo Pita
Original Article

Abstract

Estimating the size of animal populations is essential for understanding the demography and conservation status of species. Genetic Non-Invasive Sampling (gNIS) combined with Spatially Explicit Capture-Recapture (SECR) modelling may provide a practical tool to obtain such estimates. Here, we evaluate for the first time the potential and limitations of this approach to estimate population densities for small mammals inhabiting patchily distributed habitats, focusing on the endemic Iberian Cabrera vole (Microtus cabrerae). Using 11 highly polymorphic microsatellites and two sex-linked introns, we compared population estimates in November/December 2011 based on live-trapping and gNIS and assessed the impact of distinct consensus criteria to differentiate unique genotypes. Live-trapping over 21 days captured 31 individuals, while gNIS over 5 days recorded 65–69 individuals. SECR models indicated that individual detectability was positively affected by live-trapping capture success on the previous occasion, while for gNIS, it was mainly affected by genotyping success rates and patch size. Live-trapping produced the lowest density estimates (mean ± SE) of 16.6 ± 3.2 individuals per hectare of suitable habitat (ind/ha). Estimates based on gNIS were higher and varied slightly between 25.2 ± 4.0 and 28.8 ± 4.5 ind/ha depending on assuming one or two genotyping errors, respectively, when differentiating individual genetic profiles. Results suggest that live-trapping underestimated the vole population, while the larger number of individuals detected through gNIS allowed better estimates with lower field effort. Overall, we suggest that gNIS combined with SECR models provides an effective tool to estimate small mammal population densities in fragmented habitats.

Keywords

Cabrera vole SECR model Population biology Population size estimates Fragmented habitats Faecal DNA 

Notes

Acknowledgments

This study was funded by FEDER through the Programa Operacional Factores de Competitividade—COMPETE and the Portuguese Foundation for Science and Technology—FCT—within the scope of the projects PERSIST (PTDC/BIA-BEC/105110/2008), NETPERSIST (PTDC/AAG-MAA/3227/2012) and MateFrag (PTDC/BIA-BIC/6582/2014). HSM was supported by the FCT grant SFRH/BD/73765/2010. JP was supported by a postdoctoral grant funded by the project ‘Genomics and Evolutionary Biology’ co-financed by North Portugal Regional Operational Programme 2007/2013 (ON.2 - O Novo Norte), under the National Strategic Reference Framework, through the ERDF. PB was supported by EDP Biodiversity Chair. RP was supported by the FCT grants SFRH/BPD/73478/2010 and SFRH/BPD/109235/2015. We thank Estrela Matilde for her assistance in fieldwork. We are grateful to Murray Efford for guidance through the secr package and, together with Tiago Marques, for advice regarding data analysis. Ana Galantinho provided useful feedback on a previous version of the manuscript. We also thank two anonymous reviewers who provided valuable suggestions to improve the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All applicable international, national and/or institutional guidelines for the care and use of animals were followed. All procedures were carried out under permission from the Portuguese biodiversity conservation agency (ICNF—Instituto de Conservação da Natureza e das Florestas, permit nos. 76, 77 and 80/2011/CAPT) and conformed to the guidelines approved by the American Society of Mammalogists (Sikes et al. 2011).

Supplementary material

10344_2018_1206_MOESM1_ESM.pdf (369 kb)
ESM 1 (PDF 369 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Helena Sabino-Marques
    • 1
    • 2
  • Clara Mendes Ferreira
    • 3
    • 4
  • Joana Paupério
    • 3
  • Pedro Costa
    • 1
    • 2
  • Soraia Barbosa
    • 3
    • 4
    • 5
  • Cláudia Encarnação
    • 1
    • 2
  • Russell Alpizar-Jara
    • 6
  • Paulo Célio Alves
    • 3
    • 4
    • 7
  • Jeremy B. Searle
    • 3
    • 5
  • António Mira
    • 1
    • 2
  • Pedro Beja
    • 3
    • 8
  • Ricardo Pita
    • 1
    • 2
    • 8
  1. 1.CIBIO/InBio-UE—Centro de Investigação em Biodiversidade e Recursos Genéticos, Pólo de ÉvoraUniversidade de ÉvoraÉvoraPortugal
  2. 2.Unidade de Biologia da Conservação, Departamento de BiologiaUniversidade de ÉvoraÉvoraPortugal
  3. 3.CIBIO/InBio—Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoVairãoPortugal
  4. 4.Departamento de BiologiaFaculdade de Ciências da Universidade do PortoPortoPortugal
  5. 5.Department of Ecology and Evolutionary BiologyCornell UniversityIthacaUSA
  6. 6.CIMA—Centro de Investigação em Matemática e Aplicações, IIFA, Departamento de Matemática, Escola de Ciências e TecnologiaUniversidade de ÉvoraÉvoraPortugal
  7. 7.Wildlife Biology Program, Department of Ecosystem and Conservation SciencesUniversity of MontanaMissoulaUSA
  8. 8.CEABN/InBIO—Centro de Ecologia Aplicada “Professor Baeta Neves”, Instituto Superior de AgronomiaUniversidade de LisboaLisboaPortugal

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