Central Interior Ecoregional Assessment: Terrestrial Representation in Regional Conservation Plannning
Bibliographic record
Abstract
This article describes the approach used to incorporate terrestrial ecological systems into regional conservation planning as part of the ecoregional assessment completed by the Nature Conservancy of Canada for the Central Interior of British Columbia, a vast area of 25.7 million ha. The goal of our assessment was to develop a suite of conservation areas that, once protected or managed for conservation, would represent all of the biodiversity and ecosystem functions of the Central Interior. The process involved several teams focussed on different areas (aquatic and terrestrial ecosystems; plant, and animal species).This article describes the efforts of the terrestrial coarse-scale ecological systems team. We developed an ecological systems classification to be used as coarse-filter argets, created an ecoregion-wide map of distribution, and modelled distributions of riparian ecosystems and fine-scale ecological land units to capture elevation and micro-topographic slope and aspect diversity. We also developed minimum dynamic area criteria for large-scale forest ecosystems. The final set of prioritized potential conservation areas covers 7.7 million ha (30%) of the Central Interior. We also integrated climate adaptive strategies into a plan that included large, enduring landscapes with topographic diversity, which allows for species movement or migration and populations of species at the northern limit of their range within the Central Interior.
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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 | 0.000 | 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) | 0.003 | 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".