MétaCan
Menu
Retour à la cohorte
Enregistrement W7133281679

State of fish and fish habitat reporting : part 2

2023· other· en· W7133281679 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 · 2023
Typeother
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesFisheries and Oceans Canada
Mots-clésHabitatSpecies richnessResource (disambiguation)Fish habitatWeightingAquatic ecosystemEcosystemUnit (ring theory)Sampling (signal processing)Fish <Actinopterygii>
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

A synthesis of the available and relevant data on the State of Fish and Fish Habitat in the Ontario and Prairie Region (SOFFH-OPR), that focused on the Lower Great Lakes and Alberta East Slopes priority reporting areas, was conducted based on previously selected indicators (Biodiversity, Water Quality, Connectivity, Land Use and Land Cover, and Climate Change) and their constituent metrics (2 to 6 per indicator). The value of SOFFH-OPR metrics in the Lower Great Lakes and Alberta East Slopes varied among reporting areas and assessment units, but generally reflected geographical patterns in species richness and habitat, and the effects of agriculture, urbanization, resource extraction, and other development on watersheds. Data gaps limited reporting and led to uncertainty in the SOFFH-OPR for some metrics and assessment units. These gaps could be filled, and uncertainties managed, through increased spatial and temporal sampling and the continued development of standardized monitoring programs towards the measurement of metrics that influence and are sensitive to changes in aquatic ecosystem health. Overall scores of the SOFFH-OPR for each assessment unit or reporting area were not produced for this report. Combining metrics and indicators would require decisions related to the weighting of metrics to generate the overall scores. Additionally, the indicators and metrics selected may be differentially important to the various species, life stages, and habitat features. The development of reporting thresholds and classification schemes is not a requirement for reporting on the state of ecosystems (including SOFFH-OPR), but can support objectivity, simplify communication with non-specialist audiences, and can help to integrate data from multiple jurisdictions. However, developing classification schemes is associated with several challenges including ignoring important differences among habitat types, and exaggerating differences among data points that fall close to, but on opposite sides of, a reporting threshold value. Classification schemes for reporting on the SOFFH could be based on functional relationships with management objectives, thresholds established in other guidelines, policy, regulations or other reporting initiatives, relative ranking, or expert opinion. Where management objectives are quantitatively defined, and the relationship between management objectives and metrics is known, developing classification schemes based on management objectives is the recommended method as it allows for SOFFH reporting to be aligned with management activities. Comparing multiple metric approaches is valuable to ensure synergy across management and ecosystem objectives and thresholds. Reporting thresholds (i.e., values of a metric used to define different categories of ecosystem state) are not necessarily equivalent with ecological thresholds (i.e., values of a metric beyond which ecosystems show rapid or categorical change, also known as ‘tipping points’). Not all metrics or indicators demonstrate ecological thresholds, and even when they exist, it will not always be appropriate to equate the two concepts. Reporting on the SOFFH-OPR should be accompanied by reporting on the quality, uncertainty, and representativeness of data. Similar reporting initiatives have used checklists that include sample size, the recency and temporal range, and the geographic coverage of the dataset to estimate the quality of data. Data quality considerations for SOFFH-OPR could include power analyses, species accumulation curves for fish species richness, and evaluation of data resolution and monitoring design. Data limitations and challenges with developing reporting thresholds resulted in a number of uncertainties related to the metrics within the reporting areas of SOFFH-OPR. Improved and expanded geospatial data, targeted research, and adaptive management can address uncertainties and knowledge gaps. The information presented here is a synthesis of data related to the current SOFFH-OPR. As conditions, environmental drivers, and scientific knowledge change, the SOFFH in the two reporting areas are likely to change and may need to be reassessed. Reporting on the SOFFH-OPR should also be informed by other sources of knowledge (including Indigenous and local knowledge), which could help address informational gaps and inform our understanding of historical and desired ecosystem states.

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)0,013
score de la tête « metaresearch » (Gemma)0,026
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,468
Score d'incertitude au seuil0,941

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0130,026
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0230,034
Études des sciences et des technologies0,0010,000
Communication savante0,0040,001
Science ouverte0,0030,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0140,003

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 GPT0,247
Écart entre enseignants0,232 · 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'étudeSans objet
Domainenon disponible
GenreAutre

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
Publié2023
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du CanadaTravaux en français237 207