Evaluation of methods for monitoring changes in abundance and productivity of pacific salmon populations

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Estimates of abundance and productivity for Pacific salmon populations often have wide confidence limits and are subject to bias. This situation can lead to misclassification of a population's level of endangerment based on conservation criteria. Such misclassifications may increase biological conservation risks or unnecessarily decrease social and economic benefits of fishing or other uses of aquatic systems. However, budgets for monitoring are limited. We therefore propose to use empirically based computer simulations to identify reliable, cost-effective monitoring and assessment methods for salmon. Such methods will consist of various data collection schemes, spatial and temporal patterns of sampling, and techniques for analyzing the resulting data. We will identify methods that can estimate salmon abundance and productivity, as well as their conservation status, with low bias and high precision. Those methods will reduce the chance of misclassifying the status of salmon populations and thereby increase the chance of maintaining them in a productive state.