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Enregistrement W4386649563 · doi:10.1101/2023.09.07.556613

Indigenous Knowledge as a sole data source in habitat selection functions

2023· preprint· en· W4386649563 sur OpenAlexafffund
Rowenna Gryba, Andrew VonDuyke, Henry P. Huntington, Billy Adams, Justin Gatten, Qaiyyan Harcharek, Robert Sarren, Greg H. R. Henry, Marie Auger‐Méthé

Notice bibliographique

RevuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Langueen
DomaineHealth Professions
ThématiqueIndigenous Studies and Ecology
Établissements canadiensUniversity of British ColumbiaFisheries and Oceans Canada
Organismes subventionnairesNatural Sciences and Engineering Research Council of CanadaNorth Pacific Research BoardAssociation of Canadian Universities for Northern Studies
Mots-clésHabitatIndigenousGeographySubsistence agricultureTraditional knowledgeDocumentationWildlifeEcologyEnvironmental resource managementBiologyAgricultureComputer scienceEnvironmental science

Résumé

récupéré en direct d'OpenAlex

While Indigenous Knowledge (IK) contains a wealth of information on the behaviour and habitat use of species, it is rarely included in the species-habitat models frequently used by ‘Western’ species management authorities. As decisions from these authorities can limit access to species that are important culturally and for subsistence, exclusion of IK in conservation and management frameworks can negatively impact both species and Indigenous communities. In partnership with Iñupiat hunters, we developed methods to statistically characterize IK of species-habitat relationships and developed models that rely solely on IK to identify species habitat use and important areas. We provide methods for different types of IK documentation and for dynamic habitat types (e.g., ice concentration). We apply the method to ringed seals (natchiq in Iñupiaq) in Alaskan waters, a stock for which the designated critical habitat has been debated in part due to minimal inclusion of IK. Our work demonstrates how IK of species-habitat relationships, with the inclusion of dynamic habitat types, expands on existing mapping approaches and provides another method to identify species habitat use and important areas. The results of this work provide a straightforward and meaningful approach to include IK in species management, especially through co-management processes. “Agencies have a traditional way they do science and including Indigenous Knowledge is less traditional.” - Taqulik Hepa, subsistence hunter and Director, North Slope Borough Department of Wildlife Management Statement of Positionality This study and the conversion and application of Indigenous Knowledge (IK) for habitat use models was initiated through discussions with the North Slope Borough Department of Wildlife Management (DWM). The DWM is an agency of the regional municipal government representing eight primarily Iñupiat subsistence communities in Northern Alaska. One of the goals of the DWM is to “assure participation by Borough residents in the management of wildlife and fish… so that residents can continue to practice traditional methods of subsistence harvest of wildlife resources in perpetuity” (1). Additionally, this project was presented to the Ice Seal Committee (ISC) for review, input, and approval. The ISC is an Alaskan Native organization with representatives from five regions that cover ice-associated seal ranges and “was established to help preserve and enhance ice seal habitat; protect and enhance Alaska Native culture, traditions-particularly activities associated with the subsistence use of ice seals” (2). Both the DWM and the ISC have mandates to manage ice-associated seals considering both IK and ‘Western’ scientific knowledge (1, 2), and this study was developed to meet those mandates. Iñupiat hunters from Utqiaġvik, Alaska (Figure 1) were collaborators on this project, five of whom are co-authors (B. Adams, B. Frantz, J. Gatten, Q. Harcharek, and R. Sarren), while the other hunter chose to remain anonymous for this publication. The other authors are not Indigenous: R. Gryba was a PhD candidate at the University of British Columbia, M. Auger-Méthé and G. Henry are professors at the University of British Columbia, A. Von Duyke is a researcher at the DWM, and H. Huntington is an independent social scientist. Significance Statement Indigenous Knowledge (IK) is an extensive source of information of species habitat use and behavior, but is still rarely included in statistical methods used for species conservation and management. Because current conservation practices are frequently still rooted in ‘Western’ practices many Indigenous organizations are looking for ways for IK to be better included and considered. We worked with Iñupiat hunters to develop a new statistical approach to characterize IK and use it as a sole data source in habitat models. This work expands on mapping approaches, that are valuable, but cannot be applied to dynamic habitat types (e.g., ice concentration). This work shows how IK can be meaningfully included in modelling and be considered in current approaches for species 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)0,012
score de la tête « metaresearch » (Gemma)0,056
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: aucune
Score de désaccord entre enseignants0,047
Score d'incertitude au seuil0,094

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0120,056
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0050,007
Études des sciences et des technologies0,0010,001
Communication savante0,0030,004
Science ouverte0,0020,004
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0110,005

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 Opus0,065
Tête enseignante GPT0,339
Écart entre enseignants0,275 · 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

Citations2
Publié2023
Routes d'admission2
Résumé présentoui

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