Toward reliable population estimates of wolves by combining spatial capture-recapture models and non-invasive DNA monitoring

• Type: Article in International Scientific Journal
• Date: 2018

Authors

Lopez Bao, JV (Author) Other; godinho, r (Author) FCUP; Pacheco, C (Author) Other; Lema, FJ (Author) Other; Garcia, E (Author) Other; Llaneza, L (Author) Other; Palacios, V (Author) Other; Jimenez, J (Author) Other

Journal

Title: Scientific Reports

Vol. 8

ISSN: 2045-2322

Publisher: Springer Nature

Indexing

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Other information

Authenticus ID: P-00N-KPQ

DOI: 10.1038/s41598-018-20675-9

Abstract (EN): Decision-makers in wildlife policy require reliable population size estimates to justify interventions, to build acceptance and support in their decisions and, ultimately, to build trust in managing authorities. Traditional capture-recapture approaches present two main shortcomings, namely, the uncertainty in defining the effective sampling area, and the spatially-induced heterogeneity in encounter probabilities. These limitations are overcome using spatially explicit capture-recapture approaches (SCR). Using wolves as case study, and non-invasive DNA monitoring (faeces), we implemented a SCR with a Poisson observation model in a single survey to estimate wolf density and population size, and identify the locations of individual activity centres, in NW Iberia over 4,378 km(2). During the breeding period, posterior mean wolf density was 2.55 wolves/100 km(2) (95% BCI = 1.87-3.51), and the posterior mean population size was 111.6 +/- 18.8 wolves (95% BCI = 81.8-153.6). From simulation studies, addressing different scenarios of non-independence and spatial aggregation of individuals, we only found a slight underestimation in population size estimates, supporting the reliability of SCR for social species. The strategy used here (DNA monitoring combined with SCR) may be a cost-effective way to generate reliable population estimates for large carnivores at regional scales, especially for endangered species or populations under game management.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8