A Fuzzy Logic Expert System for Estimating the Intrinsic Extinction Vulnerabilities of Seamount Fishes to Fishing

Fishing has become a major conservation threat to marine fishes. Effective conservation of threatened species requires timely identification of vulnerable species. However, evaluation of extinction risk using conventional methods is difficult for the majority of fish species as the population data normally required by such methods are unavailable. This paper presents a fuzzy expert system that integrates life history and ecological characteristics of marine fishes to estimate vulnerability to fishing. We extract heuristic rules describing the known relationship between biological characteristics and vulnerability of marine fishes from published literature. The rules consist of the conclusions from one or more conditions connected by IF-THEN clauses. Input and output variables are defined by fuzzy sets which deals explicitly with the uncertainty associated with knowledge framed in qualitative terms. Conclusions inferred from input parameters are combined through fuzzy inference and defuzzification processes. Our fuzzy system provides vulnerability estimates that correlate with observed declines more closely than existing alternatives. The system has advantages in flexibility of input data requirements, in explicit representation of uncertainty and in high adaptability to new knowledge. This fuzzy expert system can be used as a decision support tool in fishery management and marine conservation planning.