An integrated knowledge synthesis of regional ambient monitoring in Canada's oil sands
Notice bibliographique
Résumé
Abstract The desire to document and understand the cumulative implications of oil sands (OS) development in the ambient environment of northeastern Alberta has motivated increased investment and release of information in the past decade. Here, we summarize the knowledge presented in the theme-based review papers in this special series, including air, surface water, terrestrial biology, and Indigenous community-based monitoring in order to (1) consolidate knowledge gained to date, (2) highlight key commonalities and gaps, and (3) leverage this knowledge to assess the state of integration in environmental monitoring efforts in the OS region and suggest next steps. Among air, water, and land studies, the individual reviews identified a clear focus on describing stressors, including primarily (1) contaminant emission, transport, transformation, deposition, and exposure, and (2) landscape disturbance. These emphases are generally partitioned by theme; air and water studies focus heavily on chemical stressors, whereas terrestrial monitoring focuses on biological change and landscape disturbance. Causal attribution is often stated as a high priority objective across all themes. However, studies often rely on spatial proximity to attribute cause to industrial activity, leaving causal attribution potentially confounded by spatial covariance of both OS- and non-OS-related stressors in the region, and by the complexity of interacting pathways between sources of environmental change and ecological receptors. Geospatial and modeling approaches are common across themes and may represent clear integration opportunities, particularly to help inform investigation-of-cause, but are not a replacement for robust field monitoring designs. Cumulative effects assessment remains a common focus of regional monitoring, but is limited in the peer-reviewed literature, potentially reflecting a lack of integration among monitoring efforts beyond narrow integrated interpretations of results. Addressing this requires greater emphasis on a priori integrated data collection and integrated analyses focused on the main residual exposure pathways, such as atmospheric deposition. Integr Environ Assess Manag 2022;18:428–441. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). KEY POINTS Our summary of the peer-reviewed literature since 2010 from the Alberta oil sands region reveals an emphasis on chemical stressors and their association with atmospheric emissions, transport, transformation, and deposition, as well as an emphasis on landscape disturbance and associated effects. System-wide gaps in the literature, including topics of concern to local Indigenous communities, derive from a disconnect between theme areas (air, water, land), contribute to an incomplete knowledge of functional linkages, and may undermine the ability to inform regulatory or policy action. Combining papers not explicitly designed together creates interpretative and analytical challenges, and overcoming these may require future optimization of and integration between targeted monitoring projects and entire theme areas.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».