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Enregistrement W7026968896

Broadening genetic approaches for interdisciplinary, multi-scale, biocultural research; implications for conceptual and applied research for bear conservation in British Columbia

2021· dissertation· en· W7026968896 sur OpenAlexaboutno aff

Notice bibliographique

RevueUVic’s Research and Learning Repository (University of Victoria) · 2021
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueWildlife Ecology and Conservation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésScope (computer science)PopulationHabitatResource (disambiguation)Resource management (computing)Distribution (mathematics)Adaptation (eye)Local adaptation
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The use of genetic evidence to facilitate management outcomes for species of conservation or cultural concern can benefit from broadening the scope of inquiry. These efforts can include not only multiple geographic and genomic scales but also other academic disciplines and ways of knowing, which can identify unconventional drivers of genetic patterns. Genetic patterns revealed through such a broad approach can provide key information to managers regarding population differentiation, viability, isolation, and adaptive capacity, and can be incorporated into long-term precautionary management plans at local and regional scales. In this dissertation, I addressed several applied questions using multi-scale, interdisciplinary, and community-led approaches. The dramatic variation in habitat types and resource distribution in British Columbia, especially along the coastal to interior ecotone, allowed for investigation of potential genetic differentiation, landscape resistance, and local adaptation in two wide-ranging, omnivores. Grizzly bears (Ursus arctos) and black bears (Ursus americanus) in the area now known as British Columbia (BC) also hold high cultural value. Additionally, bears and people have been cohabitating and sharing resources on this landscape for millennia, prompting investigations of how this relationship and shared landscape might have shaped both. This relationship is reflected in Indigenous-led long term bear monitoring on the central coast of BC by the Nuxalk, Haíɫzaqv, Kitasoo/Xai’xais, Gitga’at, and Wuikinuxv First Nations. In the bear system of the central coast and larger BC there are management opportunities for the integration of local and regional monitoring, intergovernmental collaboration, and using genetic data to re-assert Indigenous-led management goals. Finally, given that black bear populations of the area contain a single genetic variant responsible for creating white phase or Spirit bear individuals, relevant genetic evidence that can be considered in the management of bears in BC ranges from a single genetic variant to genome-wide investigations of local adaptation across the coastal to interior ecotone. In my first data-driven chapter (Chapter 2), I used microsatellite markers to examine the pattern of genetic structure and its potential drivers among grizzly bears on the central coast of BC. We incorporated potential landscape resistance factors informed by relevant literature. Also recognizing the dramatic changes in Indigenous settlement density following European colonization and the potential for genetic markers to reflect historical patterns, we estimated resistance surfaces reflective of both pre and post colonization periods. Although no resistance surface explained a consequential proportion of genetic differentiation, we found a significant spatial overlap between Indigenous language families and the three bear genetic groups. We suspect that this pattern reflects a similar response of bears and people to unknown resource and geographic discontinuities across the landscape. This work contributes to the emerging intersection of landscape genetic and biocultural scholarship that includes non-traditional landscape factors at multiple temporal scales and considers parallel responses of wildlife and people to the landscapes they share. Additionally, given that current Provincially-designated management unit boundaries misalign to spatial patterns shown by genetic groups this research contributes detailed and actionable management implications. In Chapter 3, I used similar genetic methods to identify patterns of genetic differentiation for black bears of the central coast. In contrast with the three genetic groups of grizzly bears, we found eight genetic groups of black bears at a similar scale. This pattern likely reflects the differences in home range sizes and foraging ecology between these species. We also identified groups with low genetic diversity, with two of these groups containing high frequencies of the Spirit bear allele. We additionally found that wide waterways corresponded to genetic differentiation between groups and areas of lower than average estimated migration. We provide management recommendations based on these results that focus on balancing sufficient gene flow to ensure long-term viability of isolated and genetically depauperate genetic groups with ensuring that the rare Spirit bear variant is not swamped by an influx of genetic material. With this work, we show that linear landscape features other than roads (i.e. waterways) can provide resistance to even highly mobile species and that more gene flow is not always optimal for all scales of genetic conservation. In my third data chapter (4), I broadened the investigation of grizzly bear genetic differentiation from the scale of the central coast used in Chapter 2 to the ecotone spanning coastal and interior BC. Using whole genome resequencing, we additionally expanded the scale of genetic data to identify potential signatures of local adaptation. We found two broad-scale genetic groups corresponding to coastal and interior populations admixed along valleys that bisect the North to South Coast Mountain Range. We additionally identified potential signatures of local adaptation in genes associated with growth, development of muscle and bone, and immunity in the coastal genetic group, as well as those related to DNA repair and growth inhibition in the interior group. The functions of these candidate genes broadly align with morphological differences observed between larger coastal bears with consistent access to salmon and smaller interior bears with intermittent access to protein resources and exposure to more extreme environmental conditions. In a management context, this work highlights vulnerabilities to rapid environmental or resource changes in potentially locally adapted populations, and supports management efforts to protect connectivity via valleys that bisect the Coast Mountain Range. Finally, I summarize and discuss the conceptual and management contributions of this work and opportunities for future research (Chapter 5; dissertation conclusion). I highlight the contribution of Indigenous stewardship partners and their traditional and local ecological knowledge in defining, shaping, and expanding the scope of this dissertation, as well as applying management- relevant results. Our research methods and findings support the inclusivity of broad scientific and non-scientific communities and knowledge in genetic research and the application of genetic research to local management.

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)0,008
score de la tête « metaresearch » (Gemma)0,010
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,073
Score d'incertitude au seuil0,407

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0030,007
Études des sciences et des technologies0,0120,021
Communication savante0,0100,004
Science ouverte0,0030,004
Intégrité de la recherche0,0010,004
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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 Opus0,072
Tête enseignante GPT0,316
Écart entre enseignants0,245 · 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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Même revueUVic’s Research and Learning Repository (University of Victoria)→Même sujetWildlife Ecology and Conservation→Travaux en français237 207→