Monitoring ecological representation in currently non-harvestable areas: Four British Columbia case studies
Bibliographic record
Abstract
We evaluated representation of ecosystem types in non-harvestable areas within managed forests, as a coarse-filter indicator for biodiversity monitoring, with four case studies in British Columbia: Weyerhaeuser's coastal tenure, Clayoquot Sound on western Vancouver Island, Arrow Lakes in southwestern B.C. and Okanagan highlands of south-central B.C. Representation of some coarser- and finer-level ecosystem units was poor in the two studies with lower amounts of non-harvestable area, and more equitable in the two studies with more diverse harvesting constraints. Under-representation of highly productive sites and high proportions of edge area were concerns for most ecosystems. Representation would be improved with the addition of proposed new reserves in two of three study areas. We discuss specific management implications and broader recommendations for monitoring representation, including the need for regional analyses, tests with habitat structures and organisms, effects of other disturbances and updating monitoring results. Key words: biodiversity monitoring, ecological indicators, ecosystem representation, landscape planning, unmanaged areas
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".