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Analyzing the Technical and Economic Structure of Hawaii's Pelagic Fishery

Progress Reports (PDF): FY 2001, FY 2000

Project Overview
The main objective of this project is to determine the technological and economic interrelationships in Hawaii's pelagic fishery using a multi-product dual revenue function approach. A secondary objective is to provide a preliminary test of incorporating these estimated relations into the existing allocation model.

The significant pelagic species landed in Hawaii's markets include:

  • tuna - yellowfin, bigeye, albacore, skipjack
  • billfish - blue marlin, striped marlin, swordfish
  • other pelagic species - mahimahi (dorado), ono (wahoo), moonfish
These species are mostly targeted by the same group of fishermen in similar waters using similar gear. Thus, it is very likely that economic and technological interrelationships among these species exist in Hawaii's pelagic fisheries. Previous studies have indicated that failure to recognize the technical and economic interrelationship among the different species in multi-species fisheries may lead to unintended, negative outcomes for fishery management (¹Kirkley and Strand, 1988; ²Squires and Kirkley, 1991; ³Thunberg et al., 1995; 4 Diop and Kazmierczak, 1996).

Conflicts between different fishing fleets (longliners, trollers, handliners), impacts on endangered species, and the possibility of localized overfishing were the basis for regulations for the domestic longline fishery in 1990 and subsequent regulations for longliners under the Pelagic Fishery Management Plan. As an effort to analyze the potential impact of limited entry programs on various Hawaii fisheries, and on the economic performance of various fishing fleets, a linear programming model (LP) of Hawaii's commercial fisheries was developed by the E.R.G. Pacific, Inc. company. This model was subsequently modified and extended by the National Marine Fisheries Service (NMFS). Recognizing the fact that the typical fishery policy problem is characterized by (1) more than one objective or goal that decision-makers wish to optimize, and (2) decision making at fishermen and policy levels, with policy-makers having incomplete control over all variables, Leung et al. (1998) have extended the NMFS LP model into a two-level and two-objective mathematical programming model.

This extended allocation model can assist fishery manages to identify the optimal fleet mix spatially (by area) and temporally (by season) given the estimated amount of fishery resources under various management options. Although fishery incidental catch is considered in the model, the amount and proportion of targeted catch and incidental catch are assumed to vary depending on fleet, target, area, season, as well as total fishing effort based on the average of the trips taken in 1993. Using a fixed proportion of targeted catch and incidental catch for 1993 or any other year may create unrealistic 'corner' solutions in the event that the resource of a incidental catch species becomes binding. The proposed research can resolve the above problem in the present allocation model by providing more realistic technical and economic relationships among the different species in Hawaii's multi-species pelagic fishery. In general, understanding of these interactions is imperative in allocation and management options to better manage the multi-species pelagic fishery in Hawaii.

Year 1 funding for this project awarded in October 1999.

¹Kirkley, J.E. and I.E. Strand, 1988. The technology and management of multi-species fisheries. Applied Economics, 20(10): 1279-1292.
²Squires, D. and J. Kirkley, 1991. Production quota in multiproduct Pacific fisheries. Journal of Environmental Economics and Management, 21(2): 109-126.
³Thunberg, E.M., E.W. Bresnayan, and C.M. Adams, 1995. Economic analysis of technical interdependencies and the value of effort in a multi-species fishery. Marine Resources Economics, 10(1): 59-76.
&sup4Diop, H. and R.F. Kazmierczak, 1996. Technology and management in Mauritanian cephalopod fisheries. Marine Resources Economics, 11(1): 71-84.

Principal Investigator:
Dr. PingSun Leung
Department of Agricultural & Resource Economics
University of Hawaii at Manoa
3050 Maile Way, Gilmore 115
Honolulu, Hawaii 96822
Phone (808) 956-8562/7039
FAX (808) 956-2811
email: psleung@hawaii.edu

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This page updated August 17, 2006