A Standardized Ecosystem Classification for the Coordination and Design of Long-term Terrestrial Ecosystem Monitoring in Arctic-Subarctic Biomes
Bibliographic record
Abstract
A Canadian Arctic-Subarctic Biogeoclimatic Ecosystem Classification (CASBEC) is proposed as a standardized classification approach for Subarctic and Arctic terrestrial ecosystems across Canada and potentially throughout the circumpolar area. The CASBEC is grounded in long-standing terrestrial ecosystem classification theory and builds on concepts developed for ecosystems in British Columbia, Quebec, and Yukon. The fundamental classification unit of the CASBEC, the plant association, is compatible with the lower-level classifications of the Arctic Vegetation Classification (AVC), the Canadian National Vegetation Classification (CNVC), and the United States National Vegetation Classification (USNVC) and is used to generate a classification and nomenclature for Arctic and Subarctic terrestrial ecological communities. The use of a multi-scalar ecosystem framework, such as that developed by the British Columbia Biogeoclimatic Ecosystem Classification, provides an ecological context to use classified plant associations to delineate and define climatically equivalent regional scale climate units (biogeoclimatic subzones) and ecologically equivalent local-scale site units within biogeoclimatic subzones. A standardized framework and taxonomy of ecosystem classification for Subarctic and Arctic terrestrial ecological communities will facilitate the planning, coordination, and applicability of terrestrial ecological monitoring and research. The CASBEC classification and high-resolution ecosystem mapping are being used to develop an effective experimental design, to select ecosite types for long-term monitoring, and to extrapolate results to landscape scales in the Experimental and Reference Area of the Canadian High Arctic Research Station (CHARS) in Cambridge Bay. Widespread adoption of the CASBEC could provide a spatial and functionally scalable framework and a common language for interpreting, integrating, coordinating, and communicating Arctic and Subarctic monitoring, research, and land management activities across the Canadian North and around the circumpolar area.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; a candidate call from one teacher head, not a consensus.
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".