Abstract
Conventional yield-per-recruit (Y/R) and spawning-stock biomass-per-recruit (SSB/R) models make no allowance for spatial heterogeneity in fishing mortality, natural mortality, or growth across the stock area, although variability in these processes can affect model results. For example, areas with higher growth and/or lower natural mortality rates should be fished at a lower rate to maximize Y/R; however, these areas may be especially attractive to fishers and are often fished harder. Here, Y/R and SSB/R models are developed that simultaneously account for spatial heterogeneity in growth and fishing effort. These models are applied to the US Atlantic sea scallop (Placopecten magellanicus) fishery. The spatial variability in growth uses depth-integrated models from the literature and variability in effort is based on, alternatively, uniform, observed, and relative-optimal spatial harvesting distributions. The observed effort patterns are derived from vessel monitoring system positions, and illustrate one application for these widely collected but underutilized spatial data. In this example, the distribution of observed fishing effort reduces Y/R compared with the relative-optimal, or the uniform effort distribution implicitly assumed by conventional Y/R analysis. SSB/R was in some cases considerably higher under the relative-optimal distribution of effort than when calculated using observed or uniform effort patterns. Such more realistic spatially integrated Y/R and SSB/R models can help to evaluate the impact of effort patterns on fishery yield and stock egg production. These models demonstrate that the spatial distribution of effort can be as important as the overall average fishing mortality when managing fisheries to optimize Y/R, SSB/R, and yield.
Effects of spatial heterogeneity in growth and fishing effort on yield-per-recruit models: an application to the US Atlantic sea scallop fishery