A Dynamic Stress-Scape Framework to Evaluate Potential Effects of Multiple Environmental Stressors on Gulf of Alaska Juvenile Pacific Cod - Blaisdell, Josiah; Thalmann, Hillary L.; Klajbor, Willem; Zhang, Yue; Miller, Jessica A.; Laurel, Benjamin J.; Kavanaugh, Maria T. (Frontiers in Marine Science, 2021)
Quantifying the spatial and temporal footprint of multiple environmental stressors on marine fisheries is imperative to understanding the effects of changing ocean conditions on living marine resources. Pacific Cod (Gadus macrocephalus), an important marine species in the Gulf of Alaska ecosystem, has declined dramatically in recent years, likely in response to extreme environmental variability in the Gulf of Alaska related to marine heatwave conditions in 2014-2016 and 2019. Here, we evaluate the effects of two potential environmental stressors, temperature variability and ocean acidification, on the growth of juvenile Pacific Cod in the Gulf of Alaska using a novel machine-learning framework called “stress-scapes,” which applies the fundamentals of dynamic seascape classification to both environmental and biological data. Stress-scapes apply a probabilistic self-organizing map (prSOM) machine learning algorithm and hierarchical agglomerative clustering (HAC) analysis to produce distinct, dynamic patches of the ocean that share similar environmental variability and Pacific Cod growth characteristics and are robust to nonlinear biological patterns. We then compare stress-scape output classes to Pacific Cod growth rates in the field using otolith increment analysis to contrast our classification output with observed growth. Our work resolved five dynamic stress-scapes in the coastal Gulf of Alaska ecosystem from 2010-2016. We utilized stress-scapes to compare conditions during the 2014-2016 marine heatwave to cooler years immediately prior and found that the stress-scapes captured distinct heatwave and non-heatwave classes, highlighting high juvenile Pacific Cod predicted growth and anomalous environmental conditions. Dominant stress-scapes underestimated juvenile Pacific Cod growth when compared to observed field growth estimates, suggesting potential for selective mortality or biological parameters currently missing in the stress-scape model. However, a sensitivity analysis of the stress-scape classification showed that by including growth rate data in the classification, the prSOM was better able to distinguish between heatwave and normal ocean conditions. Classifications that relied solely on environmental data failed to distinguish these changing ocean conditions. By incorporating environmental and physiological variables across a wide spatio-temporal scale, stress-scapes present an emerging methodology for evaluating a marine fisheries’ response to changing ocean conditions in any dynamic marine system where sufficient data are available.