Linking woodland caribou abundance to forestry disturbance in southern British Columbia, Canada
Bibliographic record
Abstract
Abstract The decline of many woodland caribou (Rangifer tarandus caribou) populations is thought to be linked with habitat disturbances resulting from industrial development, including timber harvesting and its network of haul roads. Defining a disturbance‐abundance relationship offers a tool to assess and potentially manage for the influence of disturbance on caribou abundance. Defining this relationship is challenged by limited historical land use and abundance data, the choice of a disturbance measure, and variability in the relationship between subpopulations and across core versus matrix habitat. For 12 subpopulations of woodland caribou within the southern mountain population, we linked longitudinal caribou abundance data with historical forestry disturbances simulated from forest harvest data. We compared disturbance measures estimating the proportion of forested area commercially harvested with even‐aged, regeneration treatments (cutblocks) and converted to roads for transporting timber within subpopulation‐specific core and matrix habitats as predictors of caribou abundance. Non‐linear mixed models provided evidence that disturbances in matrix habitats negatively influenced caribou abundance, with the effects in core habitat being variable between subpopulations. Of the disturbance types evaluated, the best predictors included roads buffered by 50 m (R50), cutblocks ≤80 years old, and the cumulation of cutblocks ≤80 years old plus roads buffered by 50 m. The top‐ranked model was composed of R50 present in core and in matrix habitats. This model predicted a 42% (95% CI = 33–51%) reduction in caribou abundance for every 1% increase in matrix R50 (holding core R50 constant). Given the lack of pre‐forestry abundance data, we failed to directly derive critical disturbance thresholds; however, our models could be used to estimate subpopulation‐specific habitat‐disturbance thresholds necessary to achieve abundance targets. We recommend that in addition to existing protections of core habitat, few if any new roads should be built in core habitat, and that timber harvest in matrix habitat should be designed to minimize the establishment of associated roads.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".