Statistical Science

Spatial Capture–Recapture Models

David Borchers and Rachel Fewster

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There has been a rapid growth in spatial capture–recapture (SCR) methods in the last decade. This paper provides an overview of existing SCR models and suggestions on how they might develop in future. The core of the paper is a likelihood framework that synthesises existing SCR models. This is used to illustrate similarities and differences between models.

The key difference between conventional capture–recapture models and SCR models is that the latter include a spatial point process model for individuals’ locations and allow capture probability to depend on location. This extends the kinds of inferences that can be drawn from capture–recapture surveys, allowing them to address questions of a fundamentally spatial nature, relating to animal distribution, habitat preference, movement patterns, spatial connectivity of habitats and dependence of demographic parameters on spatial variables.

Article information

Statist. Sci., Volume 31, Number 2 (2016), 219-232.

First available in Project Euclid: 24 May 2016

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Zentralblatt MATH identifier

Capture–recapture competing risks detection hazard Poisson process spatial modelling


Borchers, David; Fewster, Rachel. Spatial Capture–Recapture Models. Statist. Sci. 31 (2016), no. 2, 219--232. doi:10.1214/16-STS557.

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  • Borchers, D. L. and Efford, M. G. (2008). Spatially explicit maximum likelihood methods for capture–recapture studies. Biometrics 64 377–385.
  • Borchers, D. L. and Kidney, D. (2014). Flexible density surface estimation for spatially explicit capture–recapture surveys. Technical report, Univ. St Andrews.
  • Borchers, D. L., Distiller, G., Foster, R., Harmsen, B. and Milazzo, L. (2014). Continuous-time spatially explicit capture–recapture, with an application to a jaguar camera-trap survey. Methods in Ecology & Evolution 5 565–665.
  • Borchers, D. L., Stevenson, B. C., Kidney, D., Thomas, L. and Marques, T. A. (2015). A unifying model for capture–recapture and distance sampling surveys of wildlife populations. J. Amer. Statist. Assoc. 110 195–204.
  • Chandler, R. B. and Royle, J. A. (2013). Spatially explicit models for inference about density in unmarked or partially marked populations. Ann. Appl. Stat. 7 936–954.
  • Cormack, R. (1964). Estimates of survival from the sighting of marked animals. Biometrika 51 429–438.
  • Dawson, D. K. and Efford, M. G. (2009). Bird population density estimated from acoustic signals. Ecology 46 1201–1209.
  • Distiller, G. and Borchers, D. L. (2015). A spatially explicit capture–recapture estimator for single-catch traps. Ecol. Evol. 5 5075–5087.
  • Efford, M. G. (2004). Density estimation in live-trapping studies. Oikos 106 598–610.
  • Efford, M. G. (2011). Estimation of population density by spatially explicit capture–recapture analysis of data from area searches. Ecology 92 2202–2207.
  • Efford, M. G. (2013). secr: Spatially explicit capture–recapture. Version 2.7.0. Univ. Otago, Available at
  • Efford, M. G. (2014). Bias from heterogeneous usage of space in spatially explicit capture–recapture analyses. Methods in Ecology & Evolution 5 599–602.
  • Efford, M. G., Borchers, D. L. and Byrom, A. E. (2009). Density estimation by spatially explicit capture–recapture: Likelihood-based methods. In Modeling Demographic Processes in Marked Populations (D. L. Thompson, E. G. Cooch and M. J. Conroy, eds.) 255–269. Springer, New York.
  • Efford, M. G., Borchers, D. L. and Mowat, G. (2013). Varying effort in capture–recapture studies. Methods in Ecology & Evolution 4 629–636.
  • Efford, M. G. and Dawson, D. K. (2009). Bird population density estimated from acoustic signals. J. Appl. Ecol. 46 1201–1209.
  • Efford, M. G., Dawson, D. K. and Borchers, D. L. (2009). Population density estimated from locations of individuals on a passive detector array. Ecology 90 2676–2682.
  • Efford, M. G. and Mowat, G. (2014). Compensatory heterogeneity in spatially explicit capture–recapture data. Ecology 95 1341–1348.
  • Efford, M. G., Dawson, D. K., Jhala, Y. V. and Qureshi, Q. (2015). Density-dependent home-range size revealed by spatially explicit capture–recapture. Ecography 38 1–13.
  • Ergon, T. and Gardner (2013). Separating mortality and emigration: Modelling space use, dispersal and survival with robust-design spatial capture–recapture data. Methods in Ecology & Evolution 5 1327–1336.
  • Fewster, R. M., Stevenson, B. C. and Borchers, D. L. (2016). Trace-contrast models for capture–recapture without capture histories. Statist. Sci. 31 245–258.
  • Gardner, B., Repucci, J., Lucherini, M. and Royle, J. A. (2010). Spatially explicit inference for open populations: Estimating demographic parameters from camera-trap studies. Ecology 91 3376–3383.
  • Illian, J., Penttinen, A., Stoyan, H. and Stoyan, D. (2009). Statistical Analysis and Modelling of Spatial Point Patterns. Wiley, New York.
  • Jolly, G. M. (1965). Explicit estimates from capture–recapture data with both death and immigration-stochastic model. Biometrika 52 225–247.
  • King, R., McClintock, B. T., Kidney, D. and Borchers, D. L. (2016). Capture–recapture abundance estimation using a semi-complete data likelihood approach. Ann. Appl. Stat. 10 264–285.
  • Link, W. A. (2003). Nonidentifiability of population size from capture–recapture data with heterogeneous detection probabilities. Biometrics 59 1123–1130.
  • Link, W. A., Yoshizaki, J., Bailey, L. L. and Pollock, K. H. (2010). Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification. Biometrics 66 178–185.
  • Marques, T. A., Thomas, L., Martin, S. W., Mellinger, D. K., Jarvis, S., Morrissey, R. P., Ciminello, C. and DiMarzio, N. (2010). Spatially explicit capture recapture methods to estimate minke whale abundance from data collected at bottom mounted hydrophones. Journal of Ornithology 152 S445–S455.
  • McClintock, B. T., Bailey, L. L., Dreher, B. P. and Link, W. A. (2014a). Probit models for capture–recapture data subject to imperfect detection, individual heterogeneity and misidentification. Ann. Appl. Stat. 8 2461–2484.
  • McClintock, B. T., Hill, J. M., Fritz, L., Chumbley, K., Luxa, K. and Diefenbach, D. R. (2014b). Mark-resight abundance estimation under incomplete identification of marked individuals. Methods in Ecology & Evolution 5 1295–1304.
  • Ornstein, L. S. and Uhnlenbeck, G. E. (1930). On the theory of Brownian motion. Phys. Rev. 36 823–841.
  • Otis, D. L., Burnham, K. P., White, G. C. and Anderson, D. R. (1978). Statistical inference from capture data on closed animal populations. Wildlife Monographs 62 1–135.
  • Pledger, S. (2000). Unified maximum likelihood estimates for closed capture–recapture models using mixtures. Biometrics 56 434–442.
  • Reich, B. J. and Gardner, B. (2014). A spatial capture–recapture model for territorial species. Environmetrics 25 630–637.
  • Royle, A. J., Fuller, A. K. and Sutherland, C. (2016). Spatial capture–recapture models allowing Markovian transience of dispersal. Population Ecology 58 53–62.
  • Royle, J. A. and Young, K. V. (2008). A hierarchical model for spatial capture–recapture data. Ecology 89 2281–2289.
  • Royle, A. J., Chandler, R. B., Sun, C. C. and Fuller, A. K. (2013). Integrating resource selection information with spatial capture–recapture. Methods in Ecology and Evolution 4 520–530.
  • Royle, J. A., Chandler, R. B., Sollmann, R. and Gardner, B. (2014). Spatial Capture–Recapture. Academic Press, San Diego, CA.
  • Royle, J. A., Sutherland, C., Fuller, A. K. and Sun, C. C. (2015). Likelihood analysis of spatial capture–recapture models for stratified or class structured populations. Ecosphere 6 1–11.
  • Schofield, M. R. and Barker, R. J. (2016). 50-year-old curiosities: Ancillarity and inference in capture–recapture models. Statist. Sci. 31 161–174.
  • Seber, G. A. F. (1965). A note on the multiple-recapture census. Biometrika 52 249–259.
  • Sollmann, R., Gardner, B., Chandler, R. B., Shindle, D. B., Onarato, D. P., Royle, J. A. and O’Connell, A. F. (2013a). Using multiple data sources provides density estimates for endangered Florida panther. J. Appl. Ecol. 50 961–968.
  • Sollmann, R., Gardner, B., Parsons, A. W., Stocking, J. J., McClintock, B. T., Simons, T. R., Pollock, K. J. and O’Connell, A. F. (2013b). A spatial mark-resight model augmented with telemetry data. Ecology 94 553–559.
  • Stevenson, B. C., Borchers, D. L., Altwegg, R., Swift, R. J., Gillespie, D. M. and Measey, G. J. (2015). A general framework for animal density estimation from acoustic detections across a fixed microphone array. Methods in Ecology & Evolution 6 38–48.
  • Sutherland, C., Fuller, A. K. and Royle, J. A. (2015). Modelling non-Euclidean movement and landscapte connectivity in highly structured ecological networks. Methods in Ecology & Evolution 6 169–177.
  • Wright, J. A., Barker, R. J., Schofield, M. R., Frantz, A. C., Byrom, A. E. and Gleeson, D. M. (2009). Incorporating genotype uncertainty into mark-recapture-type models for estimating abundance using DNA samples. Biometrics 65 833–840.