Density Estimation by Spatially Explicit Capture–Recapture: Likelihood-Based Methods

By M. Efford, David L. Borchers, Andrea E. Byrom. 2009

265 citations recorded by the source corpus.

Subfields: Ecology, Genetics

View Paper: https://www.semanticscholar.org/paper/265d19f62decd729595edd883c43081f6d5d6fc7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. B. Harmsen
2. R. Foster
3. D. Dawson
4. E. Howe
5. M. Obbard
6. C. Kyle
7. Qamar Qureshi
8. Yadvendradev Jhala

In Genetics

1. D. Dawson
2. Sarah P. Saunders
3. Elise F. Zipkin
4. E. Howe
5. M. Obbard
6. C. Kyle
7. R. Foster
8. B. Harmsen

Citations in the corpus

• Do occupancy or detection rates from camera traps reflect deer density? (2017, methodology): “We fit maximum-likelihood, spatially explicit capture-recapture models (hereafter SECR) using package secr in Program R (Efford et al. 2009; Team 2015; Efford 2017).”
• Synthesizing multiple data types for biological conservation using integrated population models (2018, methodology): “Development of IPMs using spatially explicit capture-recapture data (Efford et al., 2009; Royle et al., 2013) extends the utility of conventional IPMs by (1) accounting for spatial variation in demographic, movement, and detection parameters and (2) enabling the ability to make spatially-explicit pr”
• A critique of density estimation from camera-trap data† (2012, background): “Spatially explicit capture–recapture models combine information about the capture locations of individuals with their capture probability at point locations, to estimate density (Efford 2004; Borchers and Efford 2008; Efford et al. 2009a, b; Royle et al. 2009a, b).”
• Empirical comparison of density estimators for large carnivores (2010, methodology): “In any case, densities estimated from SECR models were robust to the choice of detection function (Efford et al. 2009).”
• Evaluating capture–recapture population and density estimation of tigers in a population with known parameters (2010, methodology): “The best approach in the absence of telemetry-based home-range data is to use the spatial capture histories of camera traps in a likelihood-based density estimation framework (Borchers & Efford, 2008; Efford et al., 2008; Royle et al., 2008).”
• Bird population density estimated from acoustic signals (2009, methodology): “Mist nets were treated as binary proximity detectors (Efford et al. 2009a), and density was estimated by fitting a ‘hazard rate’ detection function (cf. Hayes & Buckland 1983): g(d) = g0 (1–exp(–(d ⁄ r))z)), where d is the distance between a net and the bird’s home range centre.”