Potential Influence of Sewage Phosphorus and Wet and Dry Deposition Detected in Fish Collected in the Athabasca River North of Fort McMurray

Abstract

The health of fish is a primary indicator of ecosystem response in the Oil Sands Region of northeastern Alberta. However, industrial activity is accompanied by other stressors, such as the discharge of sewage, municipal activity, forest fires, and natural weathering and erosion of bitumen. To combat the spatial confounding influences, we examined white sucker (Catostomus commersonii) captured in the Athabasca River at sites over time (2011–2019) and included covariates to account for the possible sources of influence. The analyses suggest spatially heterogeneous influences of natural factors on fish, such as discharge and air temperature, but also the influence of sewage phosphorus and precipitation. Among the stressors examined here, precipitation may be the most complex and may include a mixture of sources including inputs from tributaries, urban activity, industrial development, and forest fires. Although suggestive, the attribution of variance and detection of changes are affected by sample sizes in some years; these analyses may have missed effects or misspecified important relationships, especially in males. Despite these limitations, the analyses suggest potential differences may be associated with precipitation and highlight the need to integrate robust information on known and suspected stressors in future monitoring of aquatic ecosystems in the oil sands region and beyond.

Exploring the Influence of Industrial and Climatic Variables on Communities of Benthic Macroinvertebrates Collected in Streams and Lakes in Canada’s Oil Sands Region

“…If additional analyses are conducted, care may also be needed to characterize climatic and natural stresses. While MST and MSP were included here to account for background variation, other factors such as stream discharge may further explain some of the differences over time [58,59,64,101]. While better characterizing natural exposures would be beneficial, some, such as discharge in OSR tributaries, may be influenced by industrial activity, e.g., [46,56].…”

“…While better characterizing natural exposures would be beneficial, some, such as discharge in OSR tributaries, may be influenced by industrial activity, e.g., [46,56]. Consequently, defining factors such as stream discharge as representing 'natural conditions' may, in some instances, not be accurate [59]. This may also be true of the influence of precipitation and subsequent runoff to waterbodies in the OSR [46,59].…”

“…The approach has been used successfully to document changes in both chemical and biological status in lakes and bogs [7,9,22] and in some studies of streams [8,[55][56][57]. Second, while changes may be documented at a site over time, data on natural covariates, including temperature and precipitation [58,59], and descriptors of potential industrial influence, including mining intensity [8] and land disturbance [55] can also be included to identify potential drivers. The utility of combining climatic and industrial predictors in a site-specific and temporal analysis of monitoring data has recently been demonstrated in both the deposition of CoCs in snow and in the health of fish (slimy sculpin; Cottus cognatus) in the Steepbank River [8] further supporting the broad usefulness of this approach in the OSR.…”

Challenges and Benefits of Approaches Used to Integrate Regional Monitoring Programs

“…Integrated analyses in OSM have included combining individual studies undertaken in overlapping periods to enhance interpretation (e.g., Fisher and Burton 2018;Eccles et al, 2019;Kilgour et al, 2019). Integrated analyses have also been conducted using closely related data collected by few researchers examining similar questions (Wasiuta et al, 2019) and may include digested data summarized for study areas in a weight-of-evidence approach (Culp et al, 2018;Culp et al, 2020), or the combination of several raw datasets for a originally collected for different purposes, such as discharge and water quality (Arciszewski et al, 2018), discharge, air temperature, and health of fishes (Kilgour et al, 2019;Arciszewski and McMaster, 2021), and land use and water quality (Schwalb et al, 2015;Alexander and Chambers, 2016). Studies have also conducted formal geospatial analyses and modeling (Eccles et al, 2019) and compared novel measurement techniques with conventional emissions reporting (Li et al, 2017).…”

“…Although it may be tempting to derive strong inferences and conclusions from integrated interpretation or integrated analysis, the information generated in a retrospective and integrated analysis adopts the limitations and assumptions embedded in the original papers or datasets (Liu et al, 2012;Arciszewski and McMaster 2021). The results of a posteriori integration are necessarily limited to hypothesis generation (Lindenmayer and Likens 2010;Arciszewski et al, 2017a;Arciszewski et al, 2017b) since there may be challenges with multi-causality of issues (Liu et al, 2012) and over-simplification of complex (multi-covariate) analyses (Nilssen et al, 2015).…”