Preliminary assessment of the State of Fish and Fish Habitat in Fisheries and Oceans Canada’s Ontario and Prairie Region
Notice bibliographique
Résumé
With the modernization of the Fisheries Act, DFO committed to producing ‘State of Fish and Fish Habitat’ (SOFFH) reports for Canada’s freshwater ecosystems. As part of this initiative, DFO’s Ontario and Prairie (O&P) Region selected the Lake Erie and Lake Ontario drainage basins (Lower Great Lakes Area; LGLA) and the Alberta East Slopes Area (AESA) as focal areas for reporting on in 2023. A Canadian Science Advisory Secretariat meeting was held June 29‒30, 2021, to elicit input from academic, environmental practitioners, FFHPP, and DFO Science on the appropriate indicators, metrics, and data that could be used for the O&P SOFFH report. The five indicators selected by DFO O&P were: Biodiversity, Water Quality, Connectivity, Land Use and Land Cover, and Climate Change. Data for up to six metrics per indicator were summarized for each of the reporting areas. The findings indicated that LGLA has high fish species richness. However, a number of fishes and mussel species have been listed as species at risk. Water quality parameters often exceeded thresholds in areas with the greatest urban and agricultural development, and there was also an absence of natural riparian cover in those areas. Ninety-two per cent of the barriers within the LGLA are known to prevent fish movement. Forward and backward bioclimatic velocities were found to be highest in the assessment units surrounding the Greater Toronto Area and assessment units in the Lake Ontario basin. Flood forecasts showed variable changes in the location and heights of 100-yr floods with climate change. The AESA has lower fish species richness relative to the LGLA and a correspondingly, lower number of species at risk. Water quality parameters were often consistent with guidelines for the protection of aquatic life and connectivity varied amongst watercourses in the area. Land use and land cover in the AESA showed high spatial variance, with rangeland and crops in the southeast and trees and snow/ice in the western and northeastern regions. Due to the presence of large national and provincial parks, entire assessment units were protected in the mountainous regions of AESA. Forward bioclimatic velocities were two times faster and flood heights were also higher in the AESA compared to LGLA. This report provides insight into the SOFFH within the AESA and LGLA. However, limited data were available for some metrics, resulting in high uncertainty related to the SOFFH in some assessment units. As such, we identified key data gaps and limitations of the selected indicators and metrics. This information could be used to prioritize spatial extents and items for future research and monitoring projects. The process outlined in this report demonstrates how a quantitative approach to reporting on the SOFFH could be applied by DFO in other regions.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,004 | 0,009 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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 ».