Models and Fisheries: A Case Study in Implementation

Hilborn, Ray; Walters, Carl J.; Peterman, Randall M.; Staley, Michael J.

doi:10.1577/1548-8659(1984)4<9:maf>2.0.co;2

Cited by 11 publications

(4 citation statements)

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“…Presenting model results deterministically, without uncertainty and risk, increases the likelihood of making a poor decision. Third, uncertainty requires managers to take an adaptive strategy (Hilborn et. al 1984;Walters 1986) or an experimental management strategy (McAllister and Peterman 1992).…”

Section: Resultsmentioning

confidence: 99%

Decision Making and Modeling in Freshwater Sport-fisheries Management

Radomski

Goeman

1996

Fisheries

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Models are used increasingly to predict the efficacy of sport‐fishery management actions. With model use may come model misuse. Appropriate use of models starts with a fundamental and holistic approach, presents uncertainty and model assumptions, and appropriately weighs model output with basic biological and sociological information in the decision‐making process. In addition, understanding human behavior as it relates to angling, and incorporating this knowledge into models, will improve chances of successful sport‐fish management.

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Section: Resultsmentioning

confidence: 99%

Decision Making and Modeling in Freshwater Sport-fisheries Management

Radomski

Goeman

1996

Fisheries

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“…Statistical principles of experimental design can promote scientifically defensible fishery management (McAllister and Peterman 1992). While a number of papers describe the application of computer modeling in fishery management decision making (e.g., ; Hilborn et al 1984; ), we were unable to find any published study that developed a procedure or algorithm for systematically allocating hatchery‐produced fish to best accommodate a management objective related to the benefits of the fishing public.…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Allocation of Hatchery-Produced Fish among Multiple Stocking Sites

Cowley

Ward

Deitner

et al. 2003

North American Journal of Fisheries Management

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We describe a two‐stage procedure to increase recreational angler use through optimal allocation of hatchery‐produced fish among sites. In stage 1, data on historical fish stocking, angler‐days, and attributes of individual fishing sites are used to formulate a regression equation that shows the relation between angler‐days and the number of fish stocked (stocking elasticity). In stage 2, this stocking elasticity is used in conjunction with data on the hatchery supply of rainbow trout Oncorhynchus mykiss to formulate a reallocation of fish among fishing sites. The algorithm allocates the limited production of hatchery rainbow trout among receiving sites to maximize total angler‐days by equalizing the potential gain in angler‐days from stocking one additional fish at each site. Application of the procedure to selected fishing sites in New Mexico suggests that total angler‐days could be increased by 16% with no increase in budget or other resources. An optimized fish stocking program would produce several benefits: (1) increased angler‐days by the fishing public, (2) a fish stocking schedule that is easily updated any time hatchery supply or on‐site facilities change, and (3) an objective and defensible stocking program that meets the demands of rigorous public scrutiny.

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“…Application of IPM to aquatic ecosystems does not represent a new management paradigm per se but rather represents an addition of a strategy that can complement and add value to existing paradigms. Fisheries managers have been using adaptive management for several decades (e.g., Hilborn et al 1984), although the definition of adaptive management seems to vary with the discipline and motivation of the practitioner (McLain and Lee 1996). Adaptive management is itself adapted to meet the needs of the system under management.…”

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confidence: 99%

“…Fisheries managers have been using adaptive management for several decades (e.g., Hilborn et al. 1984), although the definition of adaptive management seems to vary with the discipline and motivation of the practitioner (McLain and Lee 1996). Adaptive management is itself adapted to meet the needs of the system under management.…”

mentioning

confidence: 99%