Evaluation of visual survey programs for monitoring coho salmon escapement in relation to conservation guidelines

Canada's Wild Salmon Policy (WSP) requires that quantitative survey designs be used to monitor annual trends in Pacific salmon escapement. Visual survey methods, in which periodic counts of spawning fish are made throughout a season, are often employed for this purpose. Coho salmon populations are difficult to monitor using visual survey methods due low probability of fish detection and high variability in the annual timing of fish presence in the survey area. I developed a Monte Carlo simulation procedure to evaluate the power of peak-count, mean-count, trapezoidal area-under-the-curve (AUC), and likelihood AUC methods to detect 30% declines in coho salmon escapement over 10 years, which is the magnitude of trend that would warrant listing a population as threatened under the Canadian Species at Risk Act (SARA). My results suggest that a simple mean-count method would be best suited for monitoring coho salmon abundance in relation to SARA and WSP guidelines.