2021 Musquash monitoring review
Notice bibliographique
Résumé
Twelve indicators have previously been identified to monitor the ecosystem-level conservation objectives for the Musquash MPA (i.e., productivity, biodiversity, habitat quality), as well as to monitor potential threats to these conservation objectives. For this review, twenty-three datasets were assessed for their progress/applicability to date in supporting the ongoing monitoring of the Musquash MPA, as per the established monitoring plan. This review concluded that these datasets provide a valuable foundation for monitoring the state of the Musquash Estuary ecosystem; however, further work is needed to develop these into a more consistent, long-term monitoring program with clear links between the conservation objectives, potential threats to these conservation objectives, and the effectiveness of management measures to prevent or mitigate these threats. It was recognized that there are other sources of information, in addition to the twenty-three datasets reviewed here, that contribute to the baseline characterization of the MPA. The incorporation of these datasets into the monitoring program requires additional discussion on how they can be developed into explicit indicators that are clearly linked to conservation priorities and/or potential threats. Currently, there are no established benchmarks against which to evaluate adequacy for each indicator in the Musquash MPA Monitoring plan. It was recommended that further consideration be given to the evaluation of indicators against thresholds, i.e., what is understood as meaningful change, especially in the context of a changing climate. It was agreed that the status and trends of Musquash MPA monitoring indicators also need to be considered and reported on within a broader regional context, i.e., within the context of the Bay of Fundy and Scotian Shelf-Bay of Fundy bioregional conservation network. Musquash monitoring is conducted by several external partners, in addition to DFO. Consequently, it was identified that further steps to standardize sampling protocols and downstream data analysis, and regularize reporting, were needed to support enhanced integration of the various monitoring data streams into a coherent assessment of status and efficacy. Gaps and uncertainties in baseline information were identified to guide future improvements for long-term monitoring of the MPA. Given the diversity of expertise and interest in this area, gaps were not prioritized at this meeting. Opportunities to fill these gaps will continue to be explored, and the results of exploratory monitoring indicators will continue to be assessed and presented for review at future meetings. Given the diversity of data sources that will be required to implement a long-term monitoring program, the development of robust data management and reporting strategies would help improve periodic assessments on the status of the MPA and its monitoring program
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 | 0,003 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,008 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,037 | 0,009 |
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 ».