Incorporation of depensation to extinction risk analysis for Columbia River salmonids.

In the extinction risk analysis of this project, the focus was on (i) run trends, (ii) depensatory mechanism, and (iii) meta-analysis. These analyses were possible even with limited data about run trends and stock-recruitment. With analysis of run trends, I calculated key parameters that determine population extinction status. The results were expressed as probability distributions rather than point estimates, leading to a decision analysis regarding population status in terms of extinction risk.
Abundance itself is also a critical risk metric. Abundance level is not related to run trends. When abundance of spawners is small, the population may not find mates, and inbreeding or predator saturation may occur. Therefore, when population size becomes sufficiently small, depensation may accelerate a population decline, and delay or prevent population recovery. However, most fish population dynamics models do not have the assumption of depensation. I allowed depensation in a stock-recruitment model, and investigated depensation possibility.
Usually we cannot control a large-scale ecosystem, and also it is hard to repeat the same long-term experiment. Under the circumstances, meta-analysis is a powerful technique because it enables us to combine individual experiments and to extract information of interest from those experiments. Under a meta-analysis framework, I re-calculated management parameters such as Ricker model parameters, and optimum size for maximum sustainable yield (MSY).
Target species were Snake River spring/summer Chinook salmon, Snake River fall Chinook salmon, Snake River summer steelhead, Upper Columbia River spring Chinook salmon, Warm Spring River spring Chinook salmon, Yakima River steelhead, and John Day River spring Chinook salmon.

Important results of this research were to identify salmon populations in order of extinction severity. Three categories were considered: (i) serious extinction risk, (ii) minor extinction risk, and (iii) no risk. These results help managers to prioritize recovery efforts in order of extinction severity. Also, estimates of optimum stock size for maximum sustainable yield were calculated. Detailed results are shown in separately submitted final report.