A sociobioeconomic model (SBM) of the Texas inshore shrimp fishery is developed an an extension of a General Bioeconomic Fisheries Simulation Model (GBFSM) for annual crop fisheries. The SBM is a heuristic model which redefines the traditional concept of a vessel class to include social and cultural variables that describe the vessel operators. Sociocultural variables that are hypothesized to affect harvesting capability of fishermen, or relative fishing power ( rfp) of the vessels that they operate, are identified and referred to as Fishing Advantage variables. Fishing Advantage variables, age of operator, years of experience, and innovativeness, are quantified and incorporated into the GBFSM through modification of an equation which calculates rfp of different SBM vessel classes. Sociocultural variables hypothesized to affect decisions of vessel operators to exert fishing effort, or nominal days fished ( ndf), are identified and referred to as Motivational variables. These include deferred gratification orientation, work orientation, and vessel ownership status of the vessel operator. A method using decision trees to direct decision-making based on Motivational variables and economic feedback is incorporated into the GBFSM to adjust ndj by different vessel classes. Five idealized inshore vessel classes representing different types of Texas inshore shrimp vessels, whose operators differ in Fishing Advantage and Motivation, are included in the SBM. SBM predictions of landings, effort, revenue, and rent under baseline and two different inshore management policies, an open season inshore policy and a closed season inshore policy, are (1) compared with GBFSM predictions under the same conditions, (2) compared across management policies, and (3) compared between each inshore vessel class. Predictions of inshore landings, effort, revenue, and rent were not significantly ( P > 0.05) different between models under any policy conditions. SBM predictions of inshore landings, effort, revenue, and rent were significantly different ( P < 0.05) between policies. Under an open inshore policy total inshore landings and effort increased relative to baseline, resulting in a 38% increase in rent to the inshore fishery. Under a closed inshore policy total inshore landings and effort decreased, resulting in a 92% decrease in rent to the inshore fishery Examination of the performance of individual inshore vessel classes indicated that policy changes have different economic impacts on different groups of fishermen, with revenue and rent of the lowest producers being most sensitive to policy changes. Explicit representation of sociocultural variables in bioeconomic models of commercial fisheries differentiates performance of different fishermen. It thereby illustrates effects of different management policies on those fishermen more clearly than is possible using models in which only the ‘average’ fisherman is represented.
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