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Enregistrement W3184008437

Ecological legacies of long-term plant management along the Central Coast of British Columbia

2021· dissertation· en· W3184008437 sur OpenAlexaboutno aff
Alana Closs

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2021
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueCoastal wetland ecosystem dynamics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTerm (time)GeographyEcologyEnvironmental resource managementEnvironmental scienceBiology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Quantifying long-term human impacts to landscapes allows us to understand the ways in which ecosystems respond to constant human pressure and the effects this pressure has on permanently influencing ecological processes and functions. Permanent ecosystem changes due to human activity are described as ecological legacies. As the global population steadily increases and resource demands heighten, understanding how humans drive ecosystems can contribute to the effective development of strategies that protect sensitive species and manage resource landscapes responsibly. Many modern management techniques have devastating ecological consequences, resulting in species endangerment and extinction, habitat fragmentation, and the loss of ancient cultural landscapes similar to that of the Great Bear Rainforest of British Columbia (BC). Here, the Coastal Indigenous peoples of BC have been modifying the temperate rainforests to increase food sources for hundreds, in some cases, thousands of years, enhancing the biotic potential of the Pacific Northwest ecosystem through complex, sustainable methods of management. Since before colonization, Indigenous landscape management along the Pacific Northwest Coast has supported and enhanced ecological processes and functions, proving to be significantly less destructive than management techniques practiced by commercial industries today. Though discrete in nature, ecological and Indigenous methodologies can be used to uncover the legacies of these sustainable management systems, detectable in the present-day composition of plant communities, fire occurrence patterns, and local habitat structure. As modern resource management encroaches on coastal rainforests, these ecological legacies become increasingly threatened. Localized field surveys that identify present-day distributions and spatial boundaries of edible and economic plants, as well as highlight habitat and phenotypic characteristics can help protect and uphold cultural landscapes and valued species. \nThe objective of this study was to collect ecological data on the distribution, community composition, ecological niche, abundance, and species richness of culturally valued plants on a set of historic islands in the Great Bear Rainforest. The overarching goal of this study is to assess if the legacy effects of long-term Indigenous management still persist in these ecological variables today and collect data on the habitat, community composition, and phenotypic traits associated with large populations of edible species. Our goal is also to determine which sections of coastline surveyed in our study hold the greatest overall cultural significance and identify populations of edible plants that may have been subject to high human management. All field research was carried out in collaboration with Indigenous community and council members. One if the goals for this collaboration was to bridge the gap between western and Indigenous knowledge and identify components that led to meaningful relationships, stronger research, and the ability to exhibit “two-eyed seeing”. \nFrom the results of our study, we can conclude that the landscape surrounding all sampled sites holds high cultural and economic value, with higher richness and abundance of culturally valued species around places with known long-term human presence. Additionally, almost all of the plants identified in this study have some known management technique associated with them, with the highest managed plants subject to 11 unique and complex strategies. We believe our results are legacies of these management techniques traditionally utilized for thousands of years to increase productivity and richness of edible and economic plants. Data of this type will complement existing Indigenous Knowledge on the current location and spatial distribution of culturally important plants to support local Nations as they implement ecosystem-based-management strategies within their territories. In addition to the ecological data collected, pathways to work collaboratively with a diverse team of researchers who embody different ways of knowing were also uncovered. These included building trust, establishing respect, honoring diversity, communicating openly, and possessing cultural awareness. Our hope is that other research teams will reflect upon our experiences and use them as a path to guide their own knowledge collaborations.

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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil0,145

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0030,001
Communication savante0,0020,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,005
Tête enseignante GPT0,164
Écart entre enseignants0,159 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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