Assessment of net change of productive capacity of fish habitats: the role of uncertainty and complexity in decision making

• Published in: Canadian journal of fisheries and aquatic sciences Vol. 60; no. 1; pp. 100 - 116
• Main Authors: Minns, Charles K, Moore, James E
• Format: Journal Article
• Language: English
• Published: Ottawa, Canada NRC Research Press 01.01.2003; National Research Council of Canada; Canadian Science Publishing NRC Research Press
• Subjects: Animal, plant and microbial ecology; Applied ecology; Aquatic habitats; Biological and medical sciences; Decision making; Development projects; Ecology; Exploitation and management of natural biological resources (hunting, fishing and exploited populations survey, etc.); Fish; Fisheries management; Freshwater; Fundamental and applied biological sciences. Psychology; Habitat loss; Habitats; Lakes; Marine; Marine ecosystems; Monte Carlo simulation; Uncertainty; Wildlife management; Canada; North America; America; North America, Great Lakes; Evaluation; Uncertainty; Decision making; Environmental management; Biological productivity; Complexity; Freshwater environment; Vertebrata; Fishery; Pisces; Lakes; Habitat; Production capacity
• ISSN: 0706-652X; 1205-7533
• DOI: 10.1139/f02-168

Canada's fish habitat management is guided by the principle of "no net loss of the productive capacity of fish habitat" (NNL). Many development proposals are assessed using habitat information alone, rather than fish data. Because fish–habitat linkages are often obscured by uncertainty, uncertainty must be factored into NNL assessments. Using a quantitative framework for assessing NNL and lake habitats as a context, the implications of uncertainty for decision making are examined. The overall behaviour of a net change equation given uncertainty is explored using Monte Carlo simulation. Case studies from Great Lakes development projects are examined using interval analysis. The results indicate that uncertainty, even when large, can be incorporated into assessments. This has important implications for the habitat management based on NNL. First, schemas to specify relative levels of uncertainty using simple habitat classifications can support robust decision making. Second, attaining NNL requires greater emphasis on minimizing habitat loss and creating new areas to compensate for losses elsewhere and less on detailing small incremental changes in modified habitats where the fish response is difficult to demonstrate. Third, the moderate to high levels of uncertainty in fish–habitat linkages require that created compensation is at least twice the losses to reasonably ensure NNL.