Incorporating Industrial and Climatic Covariates into Analyses of Fish Health Indicators Measured in a Stream in Canada’s Oil Sands Region

Industrial and other human activities in Canada’s oil sands region (OSR) influence the environment. However, these impacts can be challenging to separate from natural stresses in flowing waters by comparing upstream reference sites to downstream exposure locations. For example, health indicators of lake chub (Couesius plumbeus) compared between locations in the Ells River (Upper and Lower) in 2013 to 2015 and 2018 demonstrated statistical differences. To further examine the potential sources of variation in fish, we also analyzed data at sites over time. When fish captured in 2018 were compared to pooled reference years (2013–2015), results indicated multiple differences in fish, but most of the differences disappeared when environmental covariates were included in the Elastic Net (EN) regularized regression models. However, when industrial covariates were included separately in the EN, the large differences in 2018 also disappeared, also suggesting the potential influence of these covariables on the health of fish. Further ENs incorporating both environmental and industrial covariates along with other variables which may describe industrial and natural influences, such as spring or summer precipitation and summer wind speeds and distance-based penalty factors, also support some of the suspected and potential mechanisms of impact. Further exploratory analyses simulating changes from zero and the mean (industrial) activity levels using the regression equations respectively suggest effects exceeding established critical effect sizes (CES) for fish measurements may already be present or effects may occur with small future changes in some industrial activities. Additional simulations also suggest that changing regional hydrological and thermal regimes in the future may also cause changes in fish measurements exceeding the CESs. The results of this study suggest the wide applicability of the approach for monitoring the health of fish in the OSR and beyond. The results also suggest follow-up work required to further evaluate the veracity of the suggested relationships identified in this analysis.