A standard stock assessment approach assumes that the spatial distribution of fish is uniform across a management unit. This is rarely the case, and this assumption can lead to local overfishing because fishing boats target the most productive areas. Ignoring spatial structure can eventually lead to overexploitation on a regional scale. Where the spatial distribution is not uniform, areas of persistent high density can indicate high population productivity and have positive consequences for the fitness of individual fish. This article explores how spatial reference points, based on areas of high density, can contribute to management based solely on spawning stock biomass (SSB).
The authors assess six groundfish populations on Canada's Scotian Shelf, where a decline in areas of high density (HDAs) beyond a certain threshold is associated with disproportionately large declines in SSB. A way of estimating the threshold below which SSB decreases at an increasingly faster rate per unit of HDA decline is introduced. The spatial threshold among these six stocks was found to be remarkably consistent: when stocks lose 70– 80% of HDAs, disproportionately large SSB declines are likely to occur.
One key point to emerge from the analysis is the proposition that spatial thresholds could serve as spatial reference points in conjunction with existing SSB limit reference points. In some cases, spatial thresholds correspond to SSB levels that exceed those associated with SSB-based limit reference points, suggesting that a review of these SSB points has merit. For other stocks, spatial reference points can be used in conjunction with SSB-based reference points, strengthening efforts to incorporate a precautionary approach.
This work provides a means by which spatial structure can be incorporated into a reference-point framework for fisheries management. Its general utility across a broader array of stocks should be given further attention.
Atlantic cod in aquaculture pen in Newfoundland, Canada; Photo: Gilbert Van Ryckevorsel, WWF-Canada