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Experimental Design in the Management of Fisheries: A Review
Author(s) -
McAllister Murdoch K.,
Peterman Randall M.
Publication year - 1992
Publication title -
north american journal of fisheries management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 72
eISSN - 1548-8675
pISSN - 0275-5947
DOI - 10.1577/1548-8675(1992)012<0001:editmo>2.3.co;2
Subject(s) - overexploitation , fishing , fisheries management , fish stock , stock (firearms) , population , yield (engineering) , fishery , fish <actinopterygii> , business , environmental resource management , economics , computer science , engineering , biology , materials science , demography , sociology , metallurgy , mechanical engineering
Despite the accumulating theoretical interest in experimental management, there are few practical applications of it. Because most fisheries management plans lack rigorous experimental design, managers often face controversy when results appear consistent with several alternative mechanisms or when results yield little information about causes of fish population dynamics. We provide a synthesis of the problems of experimental design in fisheries science and management, and we show how these problems can be solved to generate better information and better decisions, especially when combined with proper statistical practices and formal decision analysis. Reasons why experimental management is currently rare are (1) lack of unfamiliarity of management agencies with designing management actions to yield information, (2) logistical constraints placed on replication by fish migratory patterns, (3) resistance by fishermen who fear experimentation will lower incomes, or (4) risk of stock collapse, However, recent applications show that these constraints can be overcome if (1) experimentation is done on a small scale, such as on small stocks, (2) fishermen are compensated when cuts in fishing effort are required, (3) fishermen believe that experimentation is in their best interest (e.g., when it is likely to increase harvests), or (4) control populations are held in reserve in case overharvesting occurs in a treated population. Several quantitative decision analyses that include uncertainty show that experimentation sometimes has much higher expected economic value than not experimenting.