Influence of In-Situ Oil Sands Development on Caribou (Rangifer tarandus) Movement
Bibliographic record
Abstract
In-situ oil sands development (ISD) involves a network of facilities, wells, roads and pipelines to extract and transport subsurface bitumen. This technology is rapidly expanding and there is uncertainty whether ISDs restrict animal movement, leading to increased extinction probabilities for some wide-ranging species. Here we test for effects of simulated future (i.e., 50 years from now) and current ISDs on simulated movements of woodland caribou (Rangifer tarandus), a threatened species across North America. In simulations of future scenarios, we varied the spacing and permeability of ISDs and the presence/absence of protected areas. Permeability was measured as the number of times simulated caribou crossed ISDs with different levels of modelled permeability. We estimated the effects of these factors on caribou step length and annual home range size, key metrics of small and large spatiotemporal scales of movement, respectively. Current caribou crossings of above-ground pipeline features of ISDs were measured using camera traps and compared to expected caribou crossing rates based on present-day caribou movement simulations. Current crossing rates were evaluated within the context of predicted future crossing success rates necessary to maintain caribou step lengths and home ranges. With few exceptions, permeability across ISDs was the main factor affecting caribou movement, more so than spacing between developments or the presence of protected areas. However, minimal permeability (crossing rates of c. 15% to 60%, relative to an undisturbed site was needed to maintain existing home range size and step lengths. The effect of permeability on home range size and step length was non-linear, suggesting that small increases in permeability would provide a disproportionately greater benefit to caribou movement. Our predictions demonstrate that maintaining permeability across ISDs is more important than spacing between leases or including protected areas, and thus provides clear direction for mitigation efforts for features that will exist on the landscape for decades to come.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".