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Enregistrement W7133289869

Science Response : Rapid Status Assessments for Pacific Salmon

2024· other· en· W7133289869 sur OpenAlexfundaboutno aff
Fisheries and Oceans Canada, Pêches et Océans Canada

Notice bibliographique

RevueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2024
Typeother
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesFisheries and Oceans Canada
Mots-clésChinook windOncorhynchusFisheries managementBiodiversityFish stockPacific oceanPopulationAdaptive management
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Regular tracking of the state and distribution of salmon biodiversity is increasingly important in a changing climate. Broad declines in Canadian Pacific salmon abundances have been linked to global climate change and other factors such as deteriorating habitats, increased fish disease, and invasive species (Grant et al. 2019). To track salmon biodiversity change, we present a Wild Salmon Policy (WSP) rapid status assessment approach for Pacific salmon. This approach can assign a Red, Amber, or Green status, with High, Medium or Low confidence to salmon conservation units (CUs) with applicable data. Pacific salmon adaptive diversity occurs at a range of scales that include the species, CU, population and deme. The WSP identifies diversity at the scale of CUs, which are fundamental units that cannot be recolonized if lost (DFO 2005; Holtby and Ciruna 2007; Wade et al. 2019). Fisheries and Oceans Canada (DFO)’s WSP covers five species of Pacific salmon: Sockeye (Oncorhynchus nerka), Chinook (O. tshawytscha), Coho (O. kisutch), Pink (O. gorbuscha) and Chum Salmon (O. keta). DFO has the authority to manage these salmon under the Fisheries Act (2019). Steelhead (O. mykiss) are managed provincially, and therefore are not included in WSP rapid status assessments. This Canadian Science Advisory Secretariate (CSAS) review of the WSP rapid status assessment approach was requested by DFO Science Branch to support the evaluation of Pacific salmon Stock Management Unit (SMU) statuses relative to their Limit Reference Points (LRPs). An SMU defines a group of one or more Pacific salmon CUs that are managed together with the objective of achieving a joint status. The LRP represents the status below which serious harm is occurring to the stock, based on biological criteria established by DFO Science through peer review. An SMU below its LRP triggers a rebuilding plan. A recent CSAS process recommended that LRPs for SMUs be defined as a percentage, with the objective being that 100% of all CUs in the SMU are above the WSP Red status zone (DFO 2023; Holt et al. 2023a, 2023b). An SMU falls below the LRP if one or more CUs in an SMU are in the WSP Red status zone. The WSP rapid status approach was recommended for assessing LRP status (DFO 2023; Holt et al. 2023a). Subsequently through the current report’s CSAS process, a recommended next step is the vetting of the individual CU WSP rapid status results, and LRP status determination, by experts in a structured process. Existing WSP integrated status assessments provide a foundational approach to tracking annual salmon CU status. This approach uses an expert decision-making process to combine statuses across individual WSP metrics, and additional related information, into a single integrated status. However, the WSP integrated status assessment approach only gets us part way to tracking annual CU status, since it is time- and labor-intensive, and as a result, has only been completed for 11% of the current 377 CUs, and is 5–10 years out of date. To expand the number of CUs assessed, and provide annual CU status updates, this paper presents a new WSP rapid status approach that approximates the expert decision-making process used in the integrated status assessments. Annual WSP rapid statuses are estimated using an algorithm implemented with computer code for British Columbia (BC) and Yukon CUs with applicable data. The WSP rapid status approach provides more complete coverage of WSP statuses across CUs. Expanding the number of assessed CUs will require input from stock assessment experts to select appropriate escapement enumeration sites and years, and to perform data treatments such as gap filling as applicable. Experts would work iteratively to explore specifications for use with the WSP rapid status algorithm, such as identifying applicable WSP rapid status metrics for these data, and reviewing the WSP rapid statuses generated by the algorithm to finalize the approach for their CUs. The establishment of a governance strategy for this work is recommended, including the identification of roles and responsibilities, to ensure the inclusion of new CUs, and annual updates across CUs. The WSP rapid status approach is integrated into DFO’s Pacific Salmon Status Scanner. DFO’s Salmon Scanner is an interactive data visualization tool specifically designed for experts to support scientific exploration and help them incorporate science into decision-making processes. Experts are those with expertise on Pacific salmon including stock assessment biologists, Indigenous technical experts, research scientists, habitat, harvest, and hatchery management biologists, etc. The objectives of this Science Response are to: 1. Summarize the methods, results, and conclusions of the WSP rapid status approach. The development of this approach included three key components: a. a performance evaluation of candidate WSP rapid status algorithms against existing CSAS reviewed WSP integrated statuses; b. an evaluation of the application of the rapid status algorithm to years and CUs that currently do not have WSP integrated statuses completed; c. a measure of confidence in WSP rapid status results. 2. Document the review processes that have occurred to develop the rapid status algorithm. 3. Provide advice on next steps and future work. This Science Response Report results from the regional peer review of November 18, 2022 on the Rapid status approximations for Pacific salmon derived from integrated expert assessments under Fisheries and Oceans Canada Wild Salmon Policy.

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)0,018
score de la tête « metaresearch » (Gemma)0,041
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: aucune
Score de désaccord entre enseignants0,787
Score d'incertitude au seuil0,424

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0180,041
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,002
Études des sciences et des technologies0,0050,002
Communication savante0,0040,003
Science ouverte0,0040,005
Intégrité de la recherche0,0170,016
Charge utile insuffisante (le modèle a refusé de juger)0,0670,029

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 Opus0,014
Tête enseignante GPT0,282
Écart entre enseignants0,269 · 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
Publié2024
Routes d'admission2
Résumé présentoui

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