Cumulative Effects of Environmental Change on Culturally Significant Ecosystems in the Inuvialuit Settlement Region + Supplementary Appendices 1 to 3 (See Article Tools)
Bibliographic record
Abstract
The Inuvialuit Settlement Region (ISR) in the western Canadian Arctic is experiencing environmental changes that affect subsistence harvesting practices and are of concern to local communities. In order to assess the impacts of multiple disturbances on culturally important ecosystems in the ISR, we created a cumulative disturbance map that represents relative intensity of terrestrial disturbances across the study region. We then assessed the relative level of environmental disturbance in important harvesting areas and management zones. Subsequently, we modeled nine future disturbance scenarios that included combinations of increased human impacts and more frequent and widespread wildfires. Using the conservation planning software Marxan, we assessed the potential to conserve large, contiguous areas of unaffected harvesting lands across all scenarios. Our results show that important management zones, wildlife harvesting areas, and community planning zones are all affected by environmental disturbances. Marxan optimizations show that existing disturbance levels create thresholds for current conservation potential and indicate that future disturbances will further limit conservation potential. These results suggest that conservation planners in the region must take steps to anticipate more widespread natural and human-caused disturbance in the ISR and work to maintain large contiguous landscapes that can support wildlife harvesting in the face of ongoing environmental disturbance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.035 | 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".