Notice bibliographique
Résumé
The work presents an approach for compiling and quantifying a large amount of spatial information to estimate threats to fish and fish habitat in the Fraser River Basin (FRB), including nine anthropogenic threats, four climate-change related threats, and cumulative threat scores, using readily available data. For this document, threats are defined as the exposure of fish and fish habitat to anthropogenic activities and climate change. Additional information on the sensitivity of focal fish and fish habitats to the identified threats (such as stressor-response relationships) was beyond the scope of this analysis but would be needed to develop cumulative effects mapping. The approaches to estimating each of the indicators provide an initial broad-scale standardized framework that can be applied to characterize threats throughout the Pacific Region. Further, the approach presented incorporates many of the desirable features of geospatial mapping tools for fish and fish habitat identified in DFO (2022). Generally, Species At Risk (SAR) habitat with limited ranges (i.e., Coastrange Sculpin, Green Sturgeon, Nooksack Dace, and Salish Sucker) had higher median human activity cumulative threat scores relative to all streams in the FRB. Conversely, median human activity threat scores tended to be similar among Salmon Conservation Units (CUs) and relative to all streams, which is driven in part by the large extent of CUs that inherently capture a greater range of threat scores across streams. Re-assessing threats temporally was considered largely feasible based on updates to the included data, and by using the current threat assessment as a baseline. Example applications of the threat scores and associated inputs for informing management and prioritization decisions for Salmon habitat in the Thompson-Nicola Ecological Drainage Unit (EDU), particularly in the context of climate change were conducted: The Deadman and Adams River watershed groups were identified as having high cumulative composite scores under current and future climate conditions across Salmon species in the EDU. The riparian input composite score identified high scores including along the North Thompson River, Eagle River, and Shuswap River based on nonpoint source inputs, riparian disturbance, and modeled environmental favourability (probability of occurrence) for Salmon spawning. The water resource composite score found the South Thompson River watershed had high scores across Salmon species based on co-occurrence of high water withdrawal allowances and low stream flows. The anadromous fragmentation score identified high variation in this metric across the EDU, based on modeled environmental favourability above dams that are full barriers. Considerations for application: The analytical approach would be strengthened by sensitivity analyses and validation with independent data. Currently, confidence in the relative characterization of threat scores (including cumulative threat scores) is uncertain. Recommendations for future analyses include developing and applying metrics for levels of confidence in threat scores, which could be based on expert review or formal criteria. A variety of improvements and alternatives to individual and cumulative threat scores are provided for consideration. It is recommended that uncertainty in outputs be considered prior to applying the approach to inform fish and fish habitat management decisions. This broad-scale tool can provide insight into within-watershed planning and prioritization. Local-scale application may be further informed by local expertise, Indigenous knowledge, salmon population data, and finer-scale tools.
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 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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,010 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».