Incorporating movement into models of grey seal population dynamics

J Anim Ecol. 2006 May;75(3):634-45. doi: 10.1111/j.1365-2656.2006.01084.x.

Abstract

1. One of the most difficult problems in developing spatially explicit models of population dynamics is the validation and parameterization of the movement process. We show how movement models derived from capture-recapture analysis can be improved by incorporating them into a spatially explicit metapopulation model that is fitted to a time series of abundance data. 2. We applied multisite capture-recapture analysis techniques to photo-identification data collected from female grey seals at the four main breeding colonies in the North Sea between 1999 and 2001. The best-fitting movement models were then incorporated into state-space metapopulation models that explicitly accounted for demographic and observational stochasticity. 3. These metapopulation models were fitted to a 20-year time series of pup production data for each colony using a Bayesian approach. The best-fitting model, based on the Akaike Information Criterion (AIC), had only a single movement parameter, whose confidence interval was 82% less than that obtained from the capture-recapture study, but there was some support for a model that included an effect of distance between colonies. 4. The state-space modelling provided improved estimates of other demographic parameters. 5. The incorporation of movement, and the way in which it was modelled, affected both local and regional dynamics. These differences were most evident as colonies approached their carrying capacities, suggesting that our ability to discriminate between models should improve as the length of the grey seal time series increases.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animal Migration / physiology*
  • Animals
  • Demography
  • Female
  • Male
  • Models, Biological*
  • North Sea
  • Population Dynamics
  • Reproduction / physiology*
  • Seals, Earless / growth & development
  • Seals, Earless / physiology*
  • Stochastic Processes
  • Time Factors