Méthode de classification des milieux humides du Québec boréal à partir de la carte écoforestière du 3e inventaire décennal
Bibliographic record
Abstract
<em>See Abstract in English below</em> <strong>Résumé</strong> Si beaucoup d’efforts ont été déployés depuis 20 ans à la caractérisation du milieu terrestre boréal québécois, il en est tout autrement pour les milieux humides. Bien qu’il existe une volonté de mieux gérer ces milieux, celle-ci se voit rapidement freinée par une lacune importante : l’absence d’un outil de caractérisation des milieux humides utilisable sur l’ensemble de la forêt boréale à des coûts raisonnables. Dans un rapport technique, Breton <em>et al</em>. (2005, Rapport technique CIC-Québec Q2005-1) ont contribué à combler cette lacune en adaptant une méthode de classification des habitats de la sauvagine par photo-interprétation (Rempel <em>et al.</em> 1997, J. Wildl. Manage. 61), de façon à ce qu’elle soit utilisable avec la carte écoforestière québécoise. En appliquant cette classification sur un territoire correspondant à la quasi-totalité du Québec forestier, nous avons décelé certaines faiblesses qui nous ont amenés à revoir certains éléments, tant en ce qui concerne la typologie que le traitement géomatique. Il en a résulté un système de classification différent de celui de Breton <em>et al.,</em> mais mieux adapté à la diversité du territoire québécois. Le système proposé contient deux niveaux hiérarchiques : 1) la Classe (Aquatique, Rivage, Marécage, Dénudé humide), et 2) le Système (Réservoir, Lac, Rivière, Étang, Étang isolé), pour un total de 22 types de milieux humides. Il permet de classifier rapidement et à peu de frais les milieux humides de la forêt boréale sur de vastes territoires. Bien que le système ait été conçu pour une étude sur la régionalisation des milieux humides du Québec, nous croyons qu’il sera également fort utile pour appuyer des études fauniques et comme outil de conservation, d’aménagement et de gestion du territoire. De même, il peut aussi être adapté à d’autres provinces canadiennes et compétences législatives, puisque les systèmes de cartographie forestière montrent souvent des similitudes. ====================================================== <strong>Abstract</strong> Although numerous efforts have been invested, over the last 20 years, at characterising the terrestrial component of forest-dominated landscapes, it has truly been otherwise for wetlands. In spite of a general willingness to improve the knowledge of these ecosystems, there were no attempt to map wetlands across the boreal forest in Quebec, obviously because of the absence of a functional tool allowing wetland characterisation at low costs. In a technical report, Breton <em>et al</em>. (2005, Rapport technique CIC-Québec Q2005-1) tried to fill this gap by adapting a wetland habitat classification system that originally used aerial photography to map boreal forest waterfowl habitat (Rempel <em>et al</em>. 1997, J. Wildl. Manage. 61) in order to be applicable with Quebec’s digitized forest inventory maps. When we tried to applying this classification to a very large area that included nearly all Quebec’s forests, we found out that the system had some weaknesses. That led us to rethink some elements, from typology to geomatic processing. The resulting classification system is quite different from the one developed by Breton <em>et al.,</em> but is more adapted to the diversity of Quebec’s territory. Our classification system has two hierarchical levels: 1) the Class (Aquatic, Shoreline, Swamp, Bare wetland), and 2) the System (Reservoir, Lake, river, Pond, Isolated pond), totalling 22 types of wetland habitats. The system allows to rapidly classify the wetland habitats of forest dominated landscapes over vast regions at low costs. Though the system has been developed for a wetland habitat regionalisation study, we believe that it would be useful for wildlife habitat studies and that it could serve as a tool for wetland management and conservation. It could also be adapted to other Canadian provinces and other jurisdictions, because their forest mapping systems are often similar.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".