Making the most of sparse data to estimate density of a rare and threatened species: a case study with the fosa, a little‐studied Malagasy carnivore. (22nd April 2018)
- Record Type:
- Journal Article
- Title:
- Making the most of sparse data to estimate density of a rare and threatened species: a case study with the fosa, a little‐studied Malagasy carnivore. (22nd April 2018)
- Main Title:
- Making the most of sparse data to estimate density of a rare and threatened species: a case study with the fosa, a little‐studied Malagasy carnivore
- Authors:
- Murphy, A.
Gerber, B. D.
Farris, Z. J.
Karpanty, S.
Ratelolahy, F.
Kelly, M. J. - Abstract:
- Abstract: Sparse detections in camera trap surveys commonly hinder density estimation for threatened species. By combining detections across multiple surveys, or using informative priors in Bayesian model fitting, researchers can improve parameter estimation from sparse capture–recapture data. Using a spatial mark–resight model that incorporates site‐level heterogeneity in the spatial scale parameter via a hierarchical process and prior information, we estimated the density of a threatened carnivore (fosa, Cryptoprocta ferox ) from multiple sparse datasets collected during extensive camera trapping surveys in northeastern Madagascar (2008–2015). Our objectives were to estimate density for six sites, examine the response of fosa density and movement to habitat degradation, monitor annual density trends across 7 years at two sites, and estimate fosa abundance in the Makira–Masoala protected area complex. We obtained a mean of 16.1 (se = 0.52; range = 2–49) fosa detections and three observers identified a mean of 3.62 (se = 0.09; range = 1–8) marked individuals per survey. Fosa daily baseline encounter rate was very low (λ0 = 0.004; 0.003–0.006) and density/movement estimates were similar across forest types. Density estimates at resurveyed sites suggested annual variability in density, with estimates trending lower during the final surveys [e.g. D = 0.39 (0.14–1.11) versus 0.08 (0.05–0.31) individuals per km 2 ]. We estimated fosa abundance across the Makira–MasoalaAbstract: Sparse detections in camera trap surveys commonly hinder density estimation for threatened species. By combining detections across multiple surveys, or using informative priors in Bayesian model fitting, researchers can improve parameter estimation from sparse capture–recapture data. Using a spatial mark–resight model that incorporates site‐level heterogeneity in the spatial scale parameter via a hierarchical process and prior information, we estimated the density of a threatened carnivore (fosa, Cryptoprocta ferox ) from multiple sparse datasets collected during extensive camera trapping surveys in northeastern Madagascar (2008–2015). Our objectives were to estimate density for six sites, examine the response of fosa density and movement to habitat degradation, monitor annual density trends across 7 years at two sites, and estimate fosa abundance in the Makira–Masoala protected area complex. We obtained a mean of 16.1 (se = 0.52; range = 2–49) fosa detections and three observers identified a mean of 3.62 (se = 0.09; range = 1–8) marked individuals per survey. Fosa daily baseline encounter rate was very low (λ0 = 0.004; 0.003–0.006) and density/movement estimates were similar across forest types. Density estimates at resurveyed sites suggested annual variability in density, with estimates trending lower during the final surveys [e.g. D = 0.39 (0.14–1.11) versus 0.08 (0.05–0.31) individuals per km 2 ]. We estimated fosa abundance across the Makira–Masoala region to be 1061 (95% HPDI: 596–1780) adult individuals. On the basis of our estimate and the size of the region, we believe Makira–Masoala harbors a significant portion of the global fosa population. The conservation and management of rare species is commonly limited due to lack of population estimates. By combining detections across surveys, we overcame estimation issues and obtained valuable information on a threatened carnivore, allowing us to better assess its status and prioritize conservation actions. We advocate for practical use of sparse datasets for such data‐deficient species. Abstract : When surveying apex predators, researchers typically have to contend with small sample sizes. Being able to group data from various surveys and use information from other studies can help researchers provide much needed populations estimates. Using camera trap surveys and a group spatial mark‐resight model, we provide the first density estimates for a threatened carnivore, the fosa ( Cryptoprocta ferox ). … (more)
- Is Part Of:
- Animal conservation. Volume 21:Number 6(2018)
- Journal:
- Animal conservation
- Issue:
- Volume 21:Number 6(2018)
- Issue Display:
- Volume 21, Issue 6 (2018)
- Year:
- 2018
- Volume:
- 21
- Issue:
- 6
- Issue Sort Value:
- 2018-0021-0006-0000
- Page Start:
- 496
- Page End:
- 504
- Publication Date:
- 2018-04-22
- Subjects:
- camera trap -- carnivore -- Cryptoprocta ferox -- fosa -- informed prior -- Madagascar -- small‐sample sizes -- spatial capture–recapture
Conservation biology -- Periodicals
Wildlife conservation -- Periodicals
Conservation de la biodiversité
Conservation de la faune
Périodique électronique (Descripteur de forme)
Ressource Internet (Descripteur de forme)
333.95416 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1469-1795 ↗
http://www.blackwell-synergy.com/loi/acv ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/acv.12420 ↗
- Languages:
- English
- ISSNs:
- 1367-9430
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0903.230000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 9138.xml