Incorporating intra-annual variability in fisheries abundance data to better capture population dynamics
Abstract To reduce the risk of overexploitation and the ensuing conservation and socio-economic consequences, fisheries management relies on receiving accurate scientific advice from stock assessments. Biomass dynamics models used in stock assessment tend to rely primarily on indices of abundance and commercial landings data. Standard practice for calculating the indices used in these models typically involves taking averages of survey tow data over large, diverse spatial domains. There is a lot of variability in the choice of methodologies used to propagate index uncertainty into the assessment model, many of which require specifying it through expert knowledge or prior distributions. Here…
Explicit incorporation of spatial variability in a biomass dynamics assessment model
Abstract The sustainable management of fisheries has largely relied on stock assessment models that assume stocks are homogeneous throughout their domain. However, ignoring complex underlying spatial patterns can lead to increased risk of failures in management. Utilizing geostatistical approaches in conjunction with a traditional fishery biomass dynamics model, we develop a spatially-explicit modelling framework that treats the underlying population dynamics as spatial processes. Simulation experiments demonstrate that this approach reliably estimates variance parameters and accurately captures true patterns of population change. We further demonstrate the utility of our modelling framewor…