10-11 Falling Behind: Delayed Growth Explains Life-History Variation in Snake River Fall Chinook Salmon

Alex Perkins , Center for Population Biology, University of California, Davis, CA
Henriette Jager , Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN

Fall Chinook salmon typically migrate to the ocean as age-0 subyearlings, but the appearance of a strategy whereby juveniles over-winter in freshwater and migrate to the ocean as age-1 yearlings has arisen over the past few decades in Idaho’s Snake River population. The recent appearance of the yearling strategy has conservation implications for this threatened population because of survival and reproductive differences between the two life histories. Different proportions of juveniles adopt the yearling life history in different river reaches and years, and temperature differences are thought to play some role in accounting for this variation. The specific circumstances under which juveniles pursue this life history are poorly understood. We advance a hypothesis for the mechanism by which juveniles adopt a life history, formalize it with a model, and present the results of fitting this model to life-history data. The model captures patterns of variation in yearling proportions among reaches and years and appears robust to uncertainty in a key unknown parameter. From fitting the model to empirical yearling proportions, our results suggest that juveniles commit to a life history earlier in development than the time at which smoltification typically begins. Specifically, juveniles that become yearlings do so soon after emergence if they are too far behind a typical growth schedule given temperature and photoperiod cues at that time. We also discuss (1) how the model can be applied to historical temperature data to explore the role of temperature changes in accounting for the recent life-history shift, (2) how the model can be applied to temperature data from climate change projections to forecast future life-history changes, and (3) the model's role in population viability analysis for this threatened population.