Science to inform policy: Linking population dynamics to habitat for a threatened species in Canada
Bibliographic record
Abstract
Abstract Boreal forests provide numerous ecological services, including the ability to store large amounts of carbon, and are of significance to global biodiversity. Increases in industrial activities in boreal landscapes since the mid‐20th century have added to concerns over biodiversity loss and climate change. Boreal forests are home to dwindling populations of boreal caribou Rangifer tarandus caribou in Canada, a species at risk that requires large, undisturbed landscapes for persistence. In 2012, the Canadian government defined critical habitat for boreal caribou by relating calf recruitment to disturbances. Some have questioned whether the recruitment relationship can be extrapolated beyond the environmental conditions represented in the analysis. We examined the effects of human disturbances and fire (alone and in combination) on variation in recruitment and adult female survival using data from 58 study areas in Canada. Top models were used in aspatial scenarios of landscape change to evaluate the efficacy of the critical habitat definition in achieving the recovery objectives for boreal caribou in two contrasting landscapes: Little Smoky, dominated by high levels of human disturbances, and the northern boreal shield of Saskatchewan (SK1), dominated by fire. The top recruitment model suggested the negative effect of fire was three to four times smaller than human disturbances. The top adult female survival model included human disturbances only. These results re‐affirm that human disturbances are the primary factor contributing to boreal caribou declines. Our aspatial scenarios suggested that undisturbed habitat would have to increase to ≥68% for Little Smoky to maintain a self‐sustaining population of boreal caribou with some degree of certainty. In contrast, the SK1 population was self‐sustaining with 40% undisturbed habitat when fire disturbance predominates, but could become vulnerable with increases in human disturbances (8%–9%). Policy implications . Boreal caribou are listed as threatened under Canada's Species at Risk Act. Our results suggest that the 65% undisturbed critical habitat designation in Canada's boreal caribou Recovery Strategy may serve as a reasonable proxy for achieving self‐sustaining populations of boreal caribou in landscapes dominated by human disturbances. However, some populations may be less or more vulnerable, as illustrated by the scenarios in a landscape dominated by fire (SK1). Continued population monitoring will be essential to assessing the effectiveness of land management strategies developed for boreal caribou recovery, especially with climate change.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".