Combining genetic non-invasive sampling with spatially explicit capture-recapture models for density estimation of a patchily distributed small mammal
- 158 Downloads
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.
KeywordsCabrera vole SECR model Population biology Population size estimates Fragmented habitats Faecal DNA
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.
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).
- AEMET, IM (2011) Atlas climático Ibérico / Iberian climate atlas. Agencia Estatal de Meteorología, Ministerio de Medio Ambiente y Rural y Marino, Madrid. Instituto de Meteorologia de PortugalGoogle Scholar
- Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach, 2nd edn. Springer-Verlag, New YorkGoogle Scholar
- De Barba M, Miquel C, Lobréaux S, Quenette PY, Swenson JE, Taberlet P (2017) High-throughput microsatellite genotyping in ecology: improved accuracy, efficiency, standardization and success with low-quantity and degraded DNA. Mol Ecol Resour 17:492–507. https://doi.org/10.1111/1755-0998.12594 CrossRefPubMedGoogle Scholar
- Efford M (2014) secr: Spatially explicit capture-recapture models. R package version 2.8.2 http://www.otago.ac.nz/density. Accessed 30 April 2014
- Efford M (2018) Polygon and transect detectors in secr 3.1. http://www.otago.ac.nz/density/pdfs/secr-polygondetectors.pdf. Accessed 16 March 2018
- Efford MG, Borchers DL, Byrom AE (2009) Density estimation by spatially explicit capture–recapture: likelihood-based methods. In: Thomson DL, Cooch EG, Conroy MJ (eds) Modeling demographic processes in marked populations. Springer, Boston, pp 255–269. https://doi.org/10.1007/978-0-387-78151-8_11 CrossRefGoogle Scholar
- Ferreira CM, Sabino-Marques H, Paupério J, Barbosa S, Costa P, Encarnação C, Alpizar-Jara R, Pita R, Beja P, Mira A, Searle JB, Alves PC (2018) Genetic non-invasive sampling (gNIS) as a cost-effective tool for monitoring elusive small mammals. Eur J Wildl Res in-press. https://doi.org/10.1007/s10344-018-1188-8
- Garrido-García JA, Soriguer RC (2014) Topillo de Cabrera Iberomys cabrerae (Thomas, 1906) In: Calzada J, Clavero M, Fernández A. (eds). Guía virtual de los indicios de los mamíferos de la Península Ibérica, Islas Baleares y Canarias. Sociedad Española para la Conservación y Estudio de los Mamíferos (SECEM). http://www.secem.es/guiadeindiciosmamiferos/. Accessed 20 April 2016
- Kalinowski ST, Sawaya MA, Taper ML (2006) Individual identification and distribution of genotypic differences between individuals. J Wildl Manag 70:1148–1150. https://doi.org/10.2193/0022-541X(2006)70[1148:IIADOG]2.0.CO;2Google Scholar
- López-Bao JV, Godinho R, Pacheco C, Lema FJ, García E, Llaneza L, Palacios V, Jiménez J (2018) Toward reliable population estimates of wolves by combining spatial capture-recapture models and non-invasive DNA monitoring. Sci Rep 8:2177. https://doi.org/10.1038/s41598-018-20675-9 CrossRefPubMedPubMedCentralGoogle Scholar
- Manly BFJ (2004) Two-phase adaptive stratified sampling. In: Thompson WL (ed) Sampling rare or elusive species: concepts, designs, and techniques for estimating population parameters. Island Press, Washington DC, pp 123–133Google Scholar
- McKelvey KS, Schwartz MK (2004) Genetic errors associated with population estimation using non-invasive molecular tagging: problems and new solutions. J Wildl Manag 68:439–448. https://doi.org/10.2193/0022-541X(2004)068[0439,GEAWPE]2.0.CO;2Google Scholar
- Mills LS, Citta JJ, Lair KP, Schwarz MK, Tallman DA (2000) Estimating animal abundance using noninvasive DNA sampling: promise and pitfalls. Ecol Appl 10:283–294. https://doi.org/10.1890/1051-0761(2000)010[0283:EAAUND]2.0.CO;2Google Scholar
- Mollet P, Kéry M, Gardner B, Pasinelli G, Royle JA (2015) Estimating population size for capercaillie (Tetrao urogallus L.) with spatial capture-recapture models based on genotypes from one field sample. PLoS One 10:e0129020. https://doi.org/10.1371/journal.pone.0129020 CrossRefPubMedPubMedCentralGoogle Scholar
- Murphy SM, Augustine BC, Ulrey WA, Guthrie JM, Scheick BK, McCown JW, Cox JJ (2017) Consequences of severe habitat fragmentation on density, genetics, and spatial capture-recapture analysis of a small bear population. PLoS One 12:e0181849. https://doi.org/10.1371/journal.pone.0181849 CrossRefPubMedPubMedCentralGoogle Scholar
- Piñero FS, Garrido-García JA, Soriguer RC (2012) Dung beetles (Scarabaeidae, Coleoptera) of latrines of the Iberian endemic rodent Microtus cabrerae (Rodentia: Cricetidae: Microtinae) at Sierra de Segura (S. Iberian Peninsula). Bol Asoc Esp Entomol 36:451–455Google Scholar
- Rodgers TW, Giacalone J, Heske EJ, Janečka JE, Phillips CA, Schooley RL (2014) Comparison of noninvasive genetics and camera trapping for estimating population density of ocelots (Leopardus pardalis) on Barro Colorado Island, Panama. Trop Conserv Sci 7:690–705. https://doi.org/10.1177/194008291400700408 CrossRefGoogle Scholar
- Rosário IT (2012) Towards a conservation strategy for an endangered rodent, the Cabrera vole (Microtus cabrerae Thomas): insights from ecological data. Ph.D. Dissertation, University of LisbonGoogle Scholar
- Royle JA, Chandler RB, Sollmann R, Gardner B (2014) Spatial capture-recapture. Academic Press, WalthamGoogle Scholar
- Thompson WL (ed) (2004) Sampling rare or elusive species: concepts, designs, and techniques for estimating population parameters. Island Press, Washington DCGoogle Scholar
- Turner MG, Gardner RH, O’Neill RV (2001) Landscape ecology in theory and practice: pattern and process. Springer-Verlag, New YorkGoogle Scholar
- Valière N (2002) GIMLET: a computer program for analysing genetic individual identification data. Mol Ecol Notes 2:377–379. https://doi.org/10.1046/j.1471-8286.2002.00228.x-i2 Google Scholar
- Waits JL, Leberg PL (2000) Biases associated with population estimation using molecular tagging. Anim Conserv 3:191–199. https://doi.org/10.1111/j.1469-1795.2000.tb00103.x CrossRefGoogle Scholar