Lifeboat or sinking ship: will the size and shape of Old-Growth Management Areas provide viable future habitat for temperate rainforest lichens?
Bibliographic record
Abstract
The Kispiox Timber Supply Area, a 1.3 million ha region in northwestern British Columbia, Canada, supports a significant assemblage of temperate rainforest (oceanic) lichens that depend on old forests. Given their known sensitivity to edge effects, we ask whether or not the current configuration of Kispiox Old-Growth Management Area (OGMA) reserves will provide viable future habitat for oceanic lichens as surrounding landscapes are progressively logged in coming decades. Landscape indicators were calculated from provincial map data sets. Old Interior Cedar–Hemlock biogeoclimatic zone forests, the primary habitat for Kispiox oceanic lichens, had a landscape shape index of 6.4 in OGMAs, indicative of elongate shapes susceptible to edge effects. Mean patch size in OGMAs was 43 ha, with the largest patch size being 1 378 ha. In contrast, the landscape shape index for pre-industrial old cedar–hemlock forests was 1.3, with a mean patch size of 1 293 ha and largest patch size of 23 357 ha. When modelled edge effects were extended to 120 m, only 25% of cedar–hemlock forests in Kispiox OGMAs remained interior habitat (7 754 ha total). Adoption of silvicultural practices that maintain buffer zones around existing OGMAs, and the designation of additional OGMAs, especially in watersheds with intact old cedar–hemlock forests, is recommended to conserve oceanic lichen communities in the Kispiox region.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".