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Towards democratizing water quality monitoring processes for the lower Grand River and nearshore Lake Erie

2021· dissertation· en· W6987653464 sur OpenAlex

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Notice bibliographique

RevueUWSpace (University of Waterloo) · 2021
Typedissertation
Langueen
DomaineSocial Sciences
ThématiqueWater Resources and Governance
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWater qualityIndigenousContext (archaeology)Corporate governanceWatershedBenthic zoneFreshwater ecosystemCladophoraLimnologyWater securityEcosystem
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Freshwater quality issues are among the most pressing challenges of our time. Such issues are increasingly complex and tend to recur when we fail to acknowledge the interacting stressors that influence them. One example of a recurring issue is the prolific growth of Cladophora (a benthic nuisance alga) in the eastern basin of Lake Erie. Water managers thought they had corrected the issue by controlling nutrient loading from the 1970s to the1990s; however, the Cladophora issue returned in the mid-2000s and has persisted due to new factors changing the way the ecosystem works. The Grand River in Southern Ontario remains Lake Erie’s largest contributor of nutrients in Canada, and so is the focus of current management efforts. Problems like this, which are caused by several interacting factors in a given space over time, are known as cumulative effects. 
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\nMuch of the literature on cumulative effects and/or water quality monitoring in this dissertation reflects conventional practice focused on the perspectives of water scientists and managers; however, this dissertation does not replicate this approach. Instead, the social-ecological context surrounding freshwater quality monitoring in the study area is critically considered by incorporating diverse community perspectives alongside conventional perspectives. In the study area, Indigenous communities have treaty rights to participate in the governance of the watershed (which sits entirely within the Haldimand Tract), but these communities – like others – have not been engaged as partners in water quality monitoring or management. One reason for this is that community and Indigenous knowledges often come in different formats than conventional scientists are used to dealing with, and so these forms of community ‘data’ are not easily integrated with conventional data. As Canada moves towards a mandate for reconciliation with Indigenous communities, ignoring the challenge of bringing together different ‘ways of knowing’ is no longer acceptable. Inspired by the Cladophora challenge and the need to diversify monitoring practice, this research strives to answer the following question: How can cumulative effects water quality monitoring be enabled and involve diverse perspectives in the Grand River-Lake Erie interface?
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\nThis research encourages the democratization of water quality monitoring to ensure more diverse persons can participate in the gathering of water quality information and that their diverse ways of knowing may supplement conventional science in management and decision-making. In other words, this dissertation explores approaches for diversifying perspectives that contribute to our understanding of freshwater quality in the study area. A multimethod approach to research was undertaken to explore what may be done differently. Methods used in this research include a systematic review of monitoring programs (Chapter 3), key informant interviews (Chapter 4), in-person and online workshops (Chapters 5, 7, and 8), and artistic research (Chapter 6) – a new approach in the context of water quality monitoring and management in the study area. First, the systematic review of monitoring programs highlighted aspects of current monitoring to maintain and improve upon. Then, key informant interviews raised 106 strengths, weaknesses, opportunities, and threats, as well as 51 recommendations. I also discuss a culture shift towards more holistic thinking and more collaborative water governance, which study participants deemed necessary to develop a strong and resilient cumulative effects monitoring program. To enable this culture shift, two examples of artistic research were implemented to demonstrate potential approaches for diversifying practice. Following, eight recommendations are provided for implementing cumulative effects monitoring in the study area. 
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\nThe multimethod approach results in a framework for collaboration (i.e., organizational structure and process framework) to enable more diverse and collaborative water quality monitoring in the study area that contributes to our ability to understand and address cumulative effects. The proposed framework is community-led (whether catalyzed by community members or invited by government) and incorporates equal weighting of Indigenous and western priorities and monitoring indicators – a unique and potentially transformative contribution to literature and practice. The use of artistic research as an equitable means of community involvement is also new in the study area. Finally, because involving diverse persons to contribute their perspectives demanded the development of different approaches than currently practiced, the research process and its process-related lessons and recommendations may contribute to raising the standard for future research and practice in water quality monitoring.
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\nThis research also has implications that extend beyond strengthening the practice of water quality monitoring. The core outcomes of the later chapters – e.g., recommendations towards collaborative and community-based monitoring processes coupled with a culture shift regarding the creation and application of knowledge – would, if practiced, support at least three broader transformations in society: a formal sharing of responsibility over natural resources, increased collaboration that is mindful of diversity, and systemic changes in support of Canadian-Indigenous reconciliation. While many aspects of the future scenarios described in the concluding chapter are likely a generation away (or longer) and are far beyond the scope of any one thesis project, my hope is that possible actions catalyzed by this research and other efforts like it will collectively move society in a different, more equitable direction.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,562
Score d'incertitude au seuil0,952

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,024
Tête enseignante GPT0,264
Écart entre enseignants0,240 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle