The role of variable stressor impacts on juvenile sockeye salmon in return abundance and escapement

Abundance of Fraser River Sockeye salmon peaked in the early 1990s, and began declining from 1995 onward, hitting an all time, and highly unpredicted low in 2009 (Grant et al. 2017). The ongoing decline in productivity and abundance, and the unpredictable nature of the variation along that decline, prompted the call for a judicial inquiry. Science presented at the Cohen Commission of Inquiry, and generated since that time, all point to the early marine environment as a critical temporal period influencing variations in year-class strength (Rensel et al. 2010; Beamish et al. 2012; Peterman and Dorner 2012; Thomas et al. 2012). Studies undertaken to better understand the drivers of variation in early marine survival coalesce into four main themes: food limitation (e.g. Chittenden et al. 2010; Irvine and Akenhead 2013; Beamish et al. 2012), predation (Thomas et al. 2016), environmental stress (Hare et al. 1996; Duffy et al. 2011 Rensel et al. 2010; Healey 2011), and disease (Price et al. 2011; Miller et al. 2011; Miller et al. 2014; Tucker et al. 2018). Our genomics research focuses in on two of these themes: environmental stress and disease.
While environmental monitoring can provide information on seasonal and annual variations in temperature, salinity, oxygen, and harmful algal bloom events, salmon may be able to behaviorally avoid exposure to stressors, especially in the ocean, and it is unclear how much such variation may affect them. However, we now have the ability to detect variability in stressor impacts on the salmon themselves. We have developed biomarker panels to specifically identify the presence of different classes of stressors (e.g. thermal, hypoxic, and osmotic stress), physiological states indicative of poor health (e.g. inflammation, viral disease response, and state of immune stimulation), signatures repeatedly associated with imminent mortality, and the presence of harmful algal bloom species and key pathogens, all based on gill biopsy samples. We can run these biomarker panels simultaneously on a microfluidics qPCR “salmon Fit-Chip”.
We have accumulated 10 years of collections of juvenile Sockeye salmon originating from the Fraser River, which covers a period of extreme climactic variability as well as a large range of variation in Sockeye salmon year-class strength (as indicated by ocean survival and productivity). These fish have already been identified to stock through GSI, potentially allowing characterization of stressor impacts by stock.
We will apply the salmon Fit-Chips on 2,395 juvenile Fraser River Sockeye salmon sampled as smolt outmigrants in freshwater and ocean migrants in the Strait of Georgia through the Queen Charlotte Strait from 2008-2015. Bayesian hierarchical models will be applied to Fit-Chip data to examine the explanatory power of genomic stress indicators on estimates of ocean survival (smolt to adult including downstream migration) and spawner-recuit analysis. PCA-derived models that include monitoring data on environmental parameters will also be explored to examine how closely stress indices in salmon match the environmental triggers of specific stressors present in the regions where salmon were caught. Inclusion of a substantial number of fish from the Chilko indicator stock will strongly benefit model exploration on smolt to adult survival.