Evaluation of visual survey methods for monitoring Pacific salmon (Oncorhynchus spp.) escapement in relation to conservation guidelines

Abstract

Canada’s Wild Salmon Policy requires that biological status of conservation units of Pacific salmon (Oncorhynchus spp.) be assessed regularly in relation to abundance-based benchmarks. Visual survey methods, in which periodic counts of spawning fish are made throughout a season, will likely be used for this purpose because they provide a cost-effective means of monitoring interannual trends in escapement. Trend detection performance for visual survey methods depends mainly upon consistency in (i) the ability of observers to detect fish and (ii) the annual timing of fish presence in the survey area. We developed a Monte Carlo simulation procedure to evaluate the ability of four visual survey methods (peak count, mean count, trapezoidal area-under-the-curve (AUC), and likelihood AUC) to detect 30% declines in coho salmon (Oncorhynchus kisutch) escapement over 10 years (i.e., the magnitude of trend that would warrant listing a coho population as threatened using the listing criteria of the Committee on the Status of Endangered Wildlife in Canada (COSEWIC)) given realistic levels of variability in these two factors. The mean count outperformed all other approaches across a wide range of scenarios about true population dynamics and survey designs, suggesting that a simple mean count method is suitable for monitoring coho escapements in relation to COSEWIC guidelines.

Idiosyncratic responses of Pacific salmon species to land cover, fragmentation, and scale

“…Many researchers have expressed reservations over the use of escapement time series to detect responses to environmental change. Such data reflect many sources of variation, including variation in freshwater and marine survival, age at maturity, fishing mortality (Pella and Myren 1974), and measurement‐error (Cousens et al 1982, Shardlow et al 1987, Holt and Cox 2008), which vary within and between watersheds and years and may all but obscure the relationships ofinterest (Pella and Myren 1974, Bradford et al 2005). However, they are often the only data available that characterize salmon abundance over large areas and long periods.…”

Genetic Stock Identification Reveals That Angler Harvest Is Representative of Cryptic Stock Proportions in a High‐Profile Kokanee Fishery

“…). The variability in the expansion factor between streams is unknown and may be influenced by factors such as stream width, depth, and water clarity (Bevan ; Holt and Cox ). Therefore, we recommend that future studies estimate the expansion factor independently for each system being assessed in order to account for unique characteristics and environmental variables influencing the resident kokanee population.…”

Application of the Genetic Mark–Recapture Technique for Run Size Estimation of Yukon River Chinook Salmon

“…Escapement on Anvik and Nulato rivers is monitored opportunistically by aerial survey (2,000-4,000 fish for both rivers combined), while that of Gisasa river is monitored at the weir (1,000-3,000 fish) (JTC 2013). Aerial surveys generally underestimate escapements (Holt and Cox 2008), and the number of radio-tagged fish that moved into the Anvik and Nulato rivers was about 6.5 times higher than the number that moved into Gisasa river (Eiler et al 2004(Eiler et al , 2006a(Eiler et al , 2006b. However, even with this adjustment, total monitored Lower stock escapements would be 7,000-23,000 fish.…”