Spatial (and other) capture-recapture methods

What are spatial capture-recapture methods?

Spatial capture-recapture (SCR) methods are extensions of capture-recapture methods. They use the locations of captures and recaptures to improve estimation of density, abundance and distribution of wildlife populations.

When spatial information is not available, capture-recapture information can still tell us a lot about a species. For example factors affecting survival, changes in abundance and detection probabilities. We can also investigate species behaviour such as duration of stay at migratory stopovers, or age of recruitment to the breeding population.

What species are surveyed using these methods?

Spatial capture-recapture methods can be used to survey any species in which individual animals can be uniquely identified, by means of natural markings, by being individually tagged by surveyors, or even by acoustic detection (although in this case it may be only calls rather than individuals that can be uniquely identified). They are widely used with camera traps to survey large cats (tigers, leopards, snow leopards and others) that have unique markings that allow individuals to be distinguished from one another, they are used with hair snares to survey things like bears and possums (in which case identification is by genetic analysis), they are used with mistnet traps for birds (in which case identification is by means of rings attached to captured birds), and they are used with acoustic detectors to survey vocal species like gibbons and frogs.

A snow leopard inspecting a camera trap, with mountains in the background
A snow leopard at a camera trap. Credit: The Snow Leopard Trust

Who in CREEM works on these methods?

A few relevant publications by CREEM staff

Borchers, D.L. and Fewster, R.M. 2016. Spatial capture-recapture models. Statistical Science 31: 219-232.

Borchers, D.L. and Efford, M. Spatially explicit maximum likelihood methods for capture-recapture studies. Biometrics 64: 377-385.

Dupont, G., Linden, D.W. and Sutherland, C. 2022. Improved inferences about landscape connectivity from spatial capture-recapture by integration of a movement model. Ecology, 103: e3544.

Durbach, I., Borchers, D.L., Sutherland, C. and Sharma, K. 2021. Fast, flexible alternatives to regular grid designs for spatial capture-recapture. Methods in Ecology and Evolution 12: 298–310.

Glennie, R., Borchers, D.L., Murchie, M., and Harmsen, B.J. and Foster, R.J. 2019. Open population maximum likelihood spatial capture-recapture. Biometrics, 75: 1345-1355.

Stevenson, B.C., Borchers, D.L., Measey, G.J., Altwegg, R.A 2015. A general framework for animal density estimation from acoustic detections across a fixed microphone array. Methods in Ecology and Evolution 6: 38-48.

Worthington, H., King, R., McCrea, R., Smout, S. and Pomeroy, P. 2021. Modeling recruitment of birth cohorts to the breeding population: A hidden Markov model approach. Frontiers in Ecology and Evolution 9:

Some relevant links

Online SCR training material for: