Fishery management seeks to balance economic productivity and biological diversity. Due to imperfect knowledge of the biogeographical environment and issues of uncertainty and confidentiality associated with fishery dependent data, fishermen within a fleet are often considered homogeneous and average values are used to describe fishing effort and catch in stock harvest models.

This research shows that heterogeneity in individual behavior and fishing performance exists among fishermen within a fishing fleet and addresses the role of this heterogeneity on fish stock size and fleet catch. Analysis of catch and effort anomalies in California Department of Fish and Game fish block data reveals fleets with large, tightly clustered portions of below average effort and catch and smaller but more widely spread portions of far above average effort and catch. I show that individuals are consistent in their performance and that fishermen in different portions of a fleet have some distinctly different characteristics and responses to environmental and fishery-specific variables. Furthermore, I find significant spatial and temporal differences between the behavior of the consistently high catch per unit effort (CPUE) fishermen and the rest of the fishermen in the fleet.

This research employs a variety of techniques to model and predict fishing fleet effort allocation and harvest. These include analytical and multivariate regression models, discrete choice random utility (Logit) models, and Generalized Geoadditive Mixed Models.

As a result of this heterogeneity, the fish biomass removed by the below average portions of the fishing fleets does not balance the above average portions to generate predicted “average” fleet catches. The imbalance suggests that harvest models using average values for fishing effort and harvested biomass could significantly underestimate fleet impacts on fish stocks. This research ends with a discussion of management implications under heterogeneous fisheries.