Red-Listed Ecosystem Status of Interior Wetbelt and Inland Temperate Rainforest of British Columbia, Canada
Bibliographic record
Abstract
The Interior Wetbelt (IWB) of British Columbia, which includes the globally rare Inland Temperate Rainforest (ITR), contains primary forests poorly attributed and neglected in conservation planning. We evaluated the IWB and ITR using four IUCN Red List of Ecosystems Criteria: geographic distribution, environmental degradation (abiotic and biotic factors), and likelihood of ecosystem collapse. Clearcut logging (3.2M ha) represented 57% of all anthropogenic disturbances, reducing potential primary forest by 2.7 million ha (28%) for the IWB and 524,003 ha (39%) for the ITR. Decadal logging rates nearly doubled from 5.3% to 10.2% from 1970s–2000s. Core areas (buffered by 100-m from roads and developments) declined by 70% to 95% for the IWB and ITR, respectively. Vulnerable was assigned to karst, the only abiotic factor assessed, because it was associated with rare plants. For biotic factors, Old-Growth Birds were Vulnerable, Southern Woodland Caribou (Rangifer tarandus caribou) habitat and Sensitive Fish were Endangered, and Old-Growth Lichens habitat was Critical. Overall, the IWB was ranked as Endangered and the ITR as Critical with core area collapse possible within 9 to 18 years for the ITR, considered one of the world’s most imperiled temperate rainforests.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".