Data from: Separating mortality and emigration: modelling space use, dispersal and survival with robust-design spatial-capture-recapture data

1. 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. 2. 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 SCR models in general and the RD-SCR model in particular. 3.
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 approximately 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 three week intervals. 4. 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.