Abstract
Over recent years the summer feeding distribution of Northeast Atlantic mackerel (NEAM, Scomber scombrus) has expanded from its traditional core in the Norwegian Sea, northwards towards Svalbard, and westward as far as Greenland. Food availability, temperature and an increase in spawning stock biomass (SSB) are reported to be possible drivers of the distribution, but quantifying the relative contributions of these factors is difficult. Previously we developed a bioenergetics individual-based model (IBM) that uses satellite-derived maps of food availability and temperature to predict NEAM population dynamics. Here, we extend the model to explore the ways in which individuals move in search of food in the summer. We construct models of four possible search mechanisms differing in (1) the extent of the area over which individuals can perceive the environment; and (2) whether or not individuals respond to the local density of conspecifics by avoiding areas in which competition is more intense. We report that the best matches to available data over 2007–2015 are obtained when the local density of competitors is taken into account, and individuals move in response to local gradients in feeding opportunities. To determine whether the IBM is able to reproduce the observed north and westward expansion, we record total distribution area, and predicted centre of gravity in terms of latitude and longitude, over 2005–2015. The IBM successfully predicts an increase in distribution area, and a northward shift in centre of gravity, over the time series. It also predicts a westward shift in centre of gravity, but to a much lesser extent than has been observed in surveys and the fishery. The inability of our IBM to capture the full extent of the westward expansion suggests that it does not account for all relevant drivers of the NEAM summer distribution. Going forward we hope that our model can be: (1) extended to explore additional drivers of the summer distribution (e.g. currents); and (2) used in a strategic capacity to predict how the NEAM stock may respond to future climate and management scenarios.
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