Use and abuse of fishery models

Recent failures of important fish stocks give mathematical models a poor re putation as tools for fishery management. This paper examines the role of m odels in fish stock assessment and identifies reasons why they can fail. St arting with laws of arithmetic, models attempt to relate observed data to u nknown quantities, such as the stock biomass and abundance. Typically, the number of unknowns greatly exceeds the number of observations, and models m ust impose hypothetical constraints to give useful estimates. We use the wo rd "fishmetic" (rhymes with arithmetic) to represent uncertainty in the con version of arithmetic to practical fishery models. Arbitrary assumptions ca nnot be avoided, even though different choices can greatly influence the ou tcome of the analysis. We compare the modeling process in fisheries with th at in other sciences. World literature also offers useful analogies. Potent ial reasons for failure suggest possible improvements to the application of fishery models. We recommend that modelers remain skeptical, expand their knowledge base, apply common sense, and implement robust strategies for fis hery management. Particularly creative thought must be applied to the probl em of translating scientific knowledge into management practice. Comparison s between fish stocks and financial stocks illustrate some possibilities.