A fuzzy logic expert system to estimate intrinsic extinction vulnerabilities of marine 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 because 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 their intrinsic vulnerability to fishing. We extract heuristic rules (expressed in IF-THEN clauses) from published literature describing known relationships between biological characteristics and vulnerability. Input and output variables are defined by fuzzy sets which deal explicitly with the uncertainty associated with qualitative knowledge. Conclusions from different lines of evidence are combined through fuzzy inference and defuzzification processes. Our fuzzy system provides vulnerability estimates that correlate with observed declines more closely than previous methods, and has advantages in flexibility of input data requirements, in the explicit representation of uncertainty, and in the ease of incorporating new knowledge. This fuzzy expert system can be used as a decision support tool in fishery management and marine conservation planning.