Assessing cumulative human impacts on northern woodland caribou with traditional ecological knowledge and resource selection functions
Bibliographic record
Abstract
Woodland caribou (Rangifer tarandus caribou) are federally listed and declining across Canada because of the cumulative impacts of human infrastructure development. The Atlin northern mountain herd, in the territory of the Taku River Tlingit First Nation (TRTFN), British Columbia, is less affected by development than southern herds. However, recent low productivity in this herd suggests that the impacts of development (i.e., roads, mines, cabins and towns) may be accumulating. To predict the cumulative impact of human development on the Atlin herd, we developed seasonal resource selection functions (RSF) at 2 spatial scales with data from 10 global positioning system collared caribou. We modeled habitat selection and assessed cumulative effects by estimating the zone of influence (ZOI) around several types of human development. At the landscape and home range scale caribou avoided the ZOI and selected pine-lichen forests in winter and alpine habitats in summer. Approximately 8 and 2% of high quality habitat was lost due to avoidance of current development at the landscape scale in winter and summer, respectively. Future development of access roads to 2 mines would cause a further loss of 1% of high quality habitat. Negotiating the complex political dynamics that surround caribou conservation often requires new approaches to management and recovery planning. The incorporation of traditional ecological knowledge (TEK) with Western science could improve efficiency of management decisions and enhance the validity and robustness of ecological inferences. Therefore, we evaluated how well RSF and TEK habitat models predicted current woodland caribou observations and compared the spatial predictions of both modeling approaches. Habitat suitability index models were generated from TEK interviews with TRTFN members. Though comparison of habitat ranks between the 2 models showed spatial discrepancies in some cases, overall, both approaches had high model performance and successfully predicted caribou occurrence. Our results suggest TEK can be used to identify caribou habitat and is a useful approach in northern ecosystems that frequently lack long-term ecological data that are needed to inform management decisions. Combining TEK-based habitat suitability index models with cumulative effects assessments will facilitate recovery goals for woodland caribou across northern Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".