Death by a thousand cuts : impacts of in situ oil sands development on Alberta's boreal forest
Bibliographic record
Abstract
In situ oil sands development techniques are significantly more damaging to the environment than conventional oil extraction methods. The area impacted by oil sands development in Alberta is expected to be in the region of 13.8 million hectares, equal to 21 per cent of the province. In this report, the 10,600 hectare OPTI-Nexen Long Lake project was used as a case study of a state-of-the art steam assisted gravity drainage (SAGD) operation. The study suggested that a total of 8.3 per cent of the Long Lake lease will be cleared for SAGD infrastructure. Approximately 80 per cent of the land parcel will be within 250 m of an industrial feature. Nearly 24,000 m{sup 3} of water will be needed each day for steam production and processing. If all leases for oil sands development in Alberta are subjected to the same industrial footprint as the Long Lake project, 296,00 hectares of forest will be cleared and over 30,000 km of access roads will be built. The boreal forest in which the SAGD developments are taking place is home to many wildlife species who are sensitive to industrial disturbances. Habitats for many wildlife species will be reduced to small scattered islands, which may result in a serious decline in regional biodiversity. Ecological tipping points for many species are already being exceeded at current levels of industrial development. This report presented evidence from studies of caribou, furbearers such as lynx and martens and forest birds which indicated that some species are at risk of extirpation from oil sands development. The report recommended the immediate implementation of conservation offset measures such as the establishment of wildlife reserves where industrial development is not permitted. It was recommended that a cap be placed on cumulative industrial impacts to maintain basic ecological function. It was concluded that there is an urgent need for the development of a regional strategic plan that includes long-term management objectives that are supported by appropriate policy and planning frameworks. 89 refs., 22 figs.
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 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 | 0.000 | 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) | 0.000 | 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".