Abstract
Spatial distributions of structured populations are usually estimated by fitting
abundance surfaces for each stage and at each point of time separately, ignoring correlations that emerge from growth of individuals. Here, we present a statistical model that combines spatio-temporal correlations with simple stock dynamics, to estimate simultaneously how size distributions and spatial distributions develop in time. We demonstrate the method for a cod population sampled by trawl surveys. Particular attention is paid to correlation between
size classes within each trawl haul due to clustering of individuals with similar size. The model estimates growth, mortality and reproduction, after which any aspect of size-structure, spatio-temporal population dynamics, as well as the sampling process can be probed. This is illustrated by two applications: 1) tracking the spatial movements of a single cohort through time, 2) predicting the risk of by-catch of undersize individuals. The method demonstrates that it is possible to combine stock assessment and spatio-temporal dynamics, however at
a high computational cost. The model can be extended by increasing its ecological fidelity, although computational feasibility eventually becomes limiting
abundance surfaces for each stage and at each point of time separately, ignoring correlations that emerge from growth of individuals. Here, we present a statistical model that combines spatio-temporal correlations with simple stock dynamics, to estimate simultaneously how size distributions and spatial distributions develop in time. We demonstrate the method for a cod population sampled by trawl surveys. Particular attention is paid to correlation between
size classes within each trawl haul due to clustering of individuals with similar size. The model estimates growth, mortality and reproduction, after which any aspect of size-structure, spatio-temporal population dynamics, as well as the sampling process can be probed. This is illustrated by two applications: 1) tracking the spatial movements of a single cohort through time, 2) predicting the risk of by-catch of undersize individuals. The method demonstrates that it is possible to combine stock assessment and spatio-temporal dynamics, however at
a high computational cost. The model can be extended by increasing its ecological fidelity, although computational feasibility eventually becomes limiting
Original language | English |
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Journal | Canadian Journal of Fisheries and Aquatic Sciences |
Volume | 71 |
Issue number | 2 |
Pages (from-to) | 326-336 |
ISSN | 0706-652X |
DOIs | |
Publication status | Published - 2014 |