Local environmental stewardship and social-ecological bright spots in New York City
Notice bibliographique
Résumé
Due to a wide range of benefits, some of which are highly visible, urban vegetation, including tree canopy, lawns, gardens, vacant lots, and urban agriculture, has become an important focus for urban sustainability planning. As many major cities invest large amounts of public funds into programs to increase urban vegetation cover, city planners require scientific understanding to help them determine effective and equitable greening strategies. Because cities are complex social-ecological systems, with a range of ecological, socioeconomic, and technological factors driving vegetation dynamics, developing this understanding will require new, multi-disciplinary thinking to understand the many drivers of urban greening and the emergent interactions between them. In particular, in human dominated ecosystems such as cities, human visions, values, and the social relations that shape urban forests need to be incorporated into assessments of urban vegetation.In this thesis, I examine the impacts of local environmental stewardship groups, an important part of environmental governance in many major US cities, on vegetation change and management in New York City.In Chapter 1, I review the development of the field of urban ecology, outline the body of literature on environmental governance with a specific focus on local environmental stewardship, and discuss applications for urban vegetation modelling and management. In this review, I develop a framework that can be used to empirically assess the multiple drivers of urban vegetation change; integrate metrics of stewardship into urban vegetation modelling; and learn from examples of stewardship success to identify best practices for stewardship group organizing.In Chapter 2, I examine the relationship between the presence of neighborhood stewardship groups and vegetative change in New York City between 2008-2016. Using a combination of remote sensing methods and linear mixed effects models, I estimate the statistical effect of stewardship presence on neighborhood-scale ecological change across the entire city. I found that the number of stewardship groups present in a neighborhood has a significant, positive relationship with decade-scale vegetative change in New York City.In Chapter 3, I investigate bright spots of stewardship practice, neighborhoods with much better ecological outcomes than expected, by examining the enablers and barriers to capacity building that shape effective stewardship action. To amplify the impact of effective stewardship actions, we must first understand the capacities that enable them and how capacity building can be best supported. Using a mixed methods approach combining modelling, interviews, and qualitative analysis, I examine three assets that contribute to stewardship group capacity. I show that stewards believe that their most effective actions are nurtured through the human-to-human relationships built with volunteers, policymakers, and communities, and that they are hindered through lack of access to knowledge, agency, and funding.In Chapter 4, I investigate which characteristics of stewardship are generalizable and which are tied to specific local contexts through a comparison of the capacity building processes of stewardship groups in urban New York City and suburban Greater Montreal. Using qualitative content analysis, comparing results from interviews in both systems, I found that stewardship groups in each context resemble each other, but work within vastly different contexts and ultimately, via vastly different processes. I hypothesize that key differences between stewardship communities can be further understood by the mediation of demographic contexts present.Overall, I show that local environmental stewardship groups play an important role in urban vegetation change in New York City and highlight the importance of incorporating the many ways of understanding stewardship in managing complex social-ecological systems
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 source (Gemma direct ou Codex distillé), 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 ».