Wetlands of Canada and Climate Change: Observation Strategy and Baseline Data
Notice bibliographique
Résumé
In 1999, a workshop on the Canadian component of the Global Climate Observing System took place. One of the recommendations was to address the observation requirements and existing data for wetlands, in view of their ubiquity in Canada and their important role in the global biogeochemical cycles involving greenhouse gases. Following the approval of a proposal to the Climate Change Impact Fund, a workshop was organised for January, 2000. It was attended by scientists from government, universities and non-government agencies. The objectives of the workshop were to: 1. Confirm objectives of an observation system for wetlands; 2. Identify critical observations for such a system (satellite and in situ); 3. Review currently available data, gaps, and options for improvement of the observations; 4. Define requirements and specifications for a baseline wetland data set, review current status of the data set assembly, and agree on next steps to be taken to complete the data set; 5. Prepare workshop report. Presentations and discussions at the workshop provided a clear understanding of the rationale for, and the configuration of, an observation system for Canada's wetlands from the perspective of climate and climate change. It identified the key policy issues with scientific implications; the information required to address these issues; the characteristics and configuration of an observing system to provide such information; and the status of the national wetland data base and the next steps in its improvement. The following recommendations are made. 1. Observations of Canada's wetlands and an assessment of their roles in the climate system should be an integral part of a system designed to address these issues for all Canadian ecosystems, and should be implemented as part of the Canadian Climate Observing System. Its components should include observations, data processing and analysis, and scientific use of the resulting information. 2. Improvements in the observing capabilities for wetlands are essential and urgent. The three critical areas are: (i) sites instrumented for flux measurements (minimum of 3 stationary and 2 roving; 1 stationary (0 roving) in place); (ii) their long-term operation (0 in place); (iii) a well-structured, ongoing acquisition and processing of satellite data (now a R&D effort). 3. Supporting research program is necessary that will encompass three areas: (i) The development, validation and maintenance of accurate models used in combination with the input data (ii) Development of methods for the extraction of wetland information from satellite data, with emphasis on new variables and taking advantage of the new sensors and data available over the next 5 years; (iii) Use of the observations to obtain new insights into the functioning of the wetlands and to provide inputs to policy discussions regarding the response to climate change and the management of the terrestrial carbon cycle. 4. The national wetlands data base should be further developed by: i. Completing the first version of a self-contained digital database by March 2001 and developing a plan for further improvements of this database. ii. In consultation with the user groups, decide which existing regional data sets should be incorporated into the first version of the database and, if necessary, modify the database structure to accommodate these additional sources. iii. Ensure peer review of the database before publication in 2001.
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 | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,004 | 0,013 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».