Regulatory Impact Analysis for Pelagic Fishery Management in Hawaii : A Spatially Disaggregated Nonlinear Programming Model

A major challenge confronting pelagic fisheries management in Hawaii is to simultaneously achieve two different and possibly conflicting objectives: conserving protected species (sea turtles and sea birds) while maintaining a viable fishery. To illustrate the difficulty of achieving these objectives, recent regulatory policy—the prohibition of all shallow longline sets (that primarily target swordfish at depths less than 100 m), combined with a spatial and seasonal closure south of 15°N during April–May—substantially reduced incidental sea turtle takes, but probably contributed to a sharp decline of the ex-vessel revenue (from $50 million in 2000 to $33 million in 2001) accruing to the Hawaii-based longline fishery (HILLF). We have developed a nonlinear programming model to evaluate the impacts of existing and possible alternative policies on the HILLF. We did this by incorporating (i) recent data from stock assessment and ecological studies for pelagic species in the Pacific Ocean, and (ii) detailed economic factors, including ex-vessel fish prices, operational costs, labor costs, annual fixed costs involved in longline operations, and entry conditions for vessel owners, crews, and fishing trips. A specialized data management methodology was developed to support a flexible area, season, target, and species classification system for the model. The baseline case, in which the HILLF was assumed to be in an open access situation (i.e., where the fishing trips are allocated until the economic rent is dissipated) without any major regulatory actions, over-allocated longline sets by 27% in 1993 and 15% in 1998 compared to the actual data. This probably occurred because the model took no account of imperfect competition or inefficient allocation of fishing effort due to uncertainty in fish abundances and prices. However, the revenue per set, as a crude measure of productivity, suggests that the model predictions were similar to the actual. Although there was little change in the total number of sets from 1993 to 1998, the primary target shifted toward bigeye tuna (from 39% in 1993 to 63% in 1998). Because a tuna set (targeting bigeye tuna), in general, yielded less revenue with lower operating costs (despite its use of greater number of hooks deployed) compared to a swordfish set, this shift in the primary target resulted in a considerable decrease (13%) in the fleet-wide revenue from 1993 to 1998. The model predictions captured those changes. Moreover, the model overall accurately predicted the changes due to the recent management regulations for sea turtle conservation in terms of productivity and effort distribution by target and area. However, the actual total number of fishing sets was much more than the model predicted; in fact, it increased despite the aforementioned revenue loss caused by the tight regulations. Possible reasons include (i) the employment of foreign crew to reduce costs involved in longline operations, and (ii) considerable variation in CPUE and RPUE of major species as well as their market prices and weights. The model demonstrated its usefulness in analyzing the impacts of various regulatory policy options for the HILLF, such as time/area closures. Improvement in the accuracy of the model predictions depends on the availability of updated information from stock assessment and socio-economic studies.