Inferring Global and Regional Effects on Spatial Population Coherence of Chinook Salmon

A central problem in understanding how species respond to global change is in parsing the effects of local drivers of population dynamics from regional and global drivers that are shared among populations. One way of addressing this challenge is to analyze time series data from multiple populations across large geographic scales using multivariate statistics. We applied Dynamic Factor Analysis to a dataset of productivity time series from 15 Chinook salmon populations covering a broad geographical range in the eastern North Pacific Ocean in order to characterize how population trends covary in space and to quantify the spatial-temporal complexity of population responses to environmental change. Our results show that productivity dynamics of Chinook populations strongly covary at the regional scale, but are less coherent at larger spatial scales. The timing of river ice break-up during the year of smolt outmigration was identified as an important driver of regional productivity dynamics, whereas broad-scale variability in population productivity was most strongly associated with the North Pacific Gyre Oscillation, a dominant pattern of sea surface height variability. Our findings also suggest intraspecific variation in population-specific responses to the same environmental drivers.