Simulation modelling as a tool for examining the consequences of spatial structure and connectivity on local and regional population dynamics

• Published in: ICES Journal of Marine Science
• Main Authors: Kerr, Lisa A., Cadrin, Steven X., Secor, Dave H.
• Format: Text
• Language: English
• Published: Oxford University Press 2010
• Subjects: Article; Kerr; atlantic cod
• Online Access: http://icesjms.oxfordjournals.org/cgi/content/short/fsq053v1; https://doi.org/10.1093/icesjms/fsq053

<qd> Kerr, L. A., Cadrin, S. X., and Secor, D. H. 2010. Simulation modelling as a tool for examining the consequences of spatial structure and connectivity on local and regional population dynamics. – ICES Journal of Marine Science, 67. </qd>An understanding of the mechanisms underlying population persistence makes fisheries management more effective. A model framework is described, which can test hypotheses about spatial structure and connectivity within and between populations and their influence on the productivity (spawning-stock biomass, SSB), stability (variation in SSB), resilience (time to rebuild SSB after environmental disturbance), and sustainability (maximum sustainable fishing mortality and yield) of systems. The general model consists of linked age-structured submodels that incorporate the unique demographics and dynamics of population components, along with the degree and type of connectivity between them. The flexibility of this framework is illustrated with three case studies examining (i) spatial structure within a population of white perch, (ii) different types and degrees of connectivity between populations of Atlantic herring, and (iii) spatial heterogeneity and connectivity within a stock of Atlantic cod. System variance is reduced by abundant, stable population components, and the asynchronous responses of those components. Components with high productivity contributed disproportionately to the resilience of systems. Increased synchrony of component responses to environmental forcing decreased the stability of the overall system. Simulation modelling is a useful approach to evaluate the consequences of spatial structure and connectivity, and can be used to understand better the productivity and dynamics of local and regional populations.