Special Issue. Modelling Demographic Processes in Marked Populations: Proceedings of the EURING 2013 Analytical Meeting
Separating mortality and emigration: modelling space use, dispersal and survival with robust-design spatial capture–recapture data
Article first published online: 20 DEC 2013
© 2013 The Authors. Methods in Ecology and Evolution © 2013 British Ecological Society
Methods in Ecology and Evolution
Special Issue: MODELLING DEMOGRAPHIC PROCESSES IN MARKED POPULATIONS: PROCEEDINGS OF THE EURING 2013 ANALYTICAL MEETING
Volume 5, Issue 12, pages 1327–1336, December 2014
How to Cite
Ergon, T., Gardner, B. (2014), Separating mortality and emigration: modelling space use, dispersal and survival with robust-design spatial capture–recapture data. Methods in Ecology and Evolution, 5: 1327–1336. doi: 10.1111/2041-210X.12133
- Issue published online: 12 DEC 2014
- Article first published online: 20 DEC 2013
- Accepted manuscript online: 28 OCT 2013 12:15PM EST
- Manuscript Accepted: 22 OCT 2013
- Manuscript Received: 7 JUN 2013
- Research Computing Services group at USIT
- University of Oslo
- arvicoline (Arvicolinae) rodents;
- Bayesian analysis;
- competing risks;
- dispersal ecology;
- hierarchical modelling;
- individual random effects;
- life-history evolution;
- posterior predictive checks;
- spacing behaviour
- Capture–recapture (CR) techniques are commonly used to gain information about population dynamics, demography and life-history traits of populations. However, traditional CR models cannot separate mortality from emigration. Recently developed spatial–capture–recapture (SCR) models explicitly incorporate spatial information into traditional CR models, thus allowing for individuals' movements to be modelled explicitly.
- In this paper, we extend SCR models using robust-design data to allow for both processes in which individuals can disappear from the population, mortality and dispersal, to be estimated separately. We formulate a general robust-design spatial capture–recapture (RD-SCR) model, explore the properties of the model in a simulation study and compare the results to a Cormack–Jolly–Seber model and a non-spatial robust-design model with temporary emigration. In the case study, we fit several versions of the general model to data on field voles (Microtus agrestis) and compare the results with those from the non-spatial models fitted to the same data. We also evaluate assumptions of the fitted models with a series of simulation-based posterior predictive goodness-of-fit checks that are applicable to the SCR models in general and the RD-SCR model in particular.
- The simulation results show that the model preforms well under a wide range of dispersal distances. Our model outperforms the traditional CR models in terms of both accuracy and precision for survival. The case study showed that adult females have an c. 3·5 times higher mortality rate than adult males. Males have larger home ranges and disperse longer distances than females, but both males and females mostly move their activity centres within their previous home range between trapping sessions at 3-week intervals.
- Our RD-SCR model has several advantages compared to other approaches to estimate ‘true’ survival instead of only ‘apparent’ survival. Additionally, the model extracts information about space use and dispersal distributions that are relevant for behavioural studies as well as studies of life-history variation, population dynamics and management. The model can be widely applied due to the flexible framework, and other variations of the model could easily be implemented.