When the protection of a threatened species depends on the economy of a foreign nation
Bibliographic record
Abstract
A significant challenge of conservation biology is to preserve species in places where their critical habitat also attracts significant economic interest. The problem is compounded when species distributions occur across large spatial extents. Threatened boreal caribou (Rangifer tarandus caribou) epitomize this problem: their critical habitat encompasses a vast expanse of forest that also supplies much of Canada's merchantable timber. Boreal caribou were protected under the Canada Species at Risk Act in 2003. We investigated putative drivers of reduced disturbance for caribou habitat since then. Where the cumulative logging footprint slowed within caribou habitat, this has resulted neither from decreases in annual allowable cut of timber nor the creation or expansion of protected areas. Rather, it has fluctuated with the American economy relative to that of Canada. For each $0.05 US lost over the $CAD, 129 km2 of caribou habitat was not disturbed by logging in a given year. Recent population declines have been occurring even though logging typically remained at <70% of allowed levels. Our study raises concerns about how caribou are functionally being conserved under the current application of existing legislation. In this globalized world, the economy of foreign nations is increasingly likely to govern national conservation objectives.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".