The Extent of Anthropogenic Disturbance on Wetland Area in the Oil Sands Region of Alberta, Canada Between 2000 and 2018
Bibliographic record
Abstract
Wetlands globally have and continue to undergo modification from anthropogenic and natural environmental factors. To bridge this gap, this study utilised a GIS-based approach to quantify the areal extent of human footprint disturbances to wetlands over time. This approach attributed wetland disturbance by wetlands class, disturbance type and sector during two notable disturbance transitions, from 2000 to 2010 and from 2010 to 2018, in the oil sands region (OSR) of northern Alberta, Canada. The wetland disturbance area was calculated using a physical disturbance dataset intersected with the Alberta Merged Wetland Inventory. Results indicate that 3284 km2 (2616 km2 between 2000 and 2010, 668 km2 between 2010 and 2018) of wetlands have undergone disturbance in the OSR. Examination of disturbance by the industrial sector between 2010 and 2018 indicates that the oil and gas and forestry sectors are the greatest sources of disturbance (402 km2 and 179 km2, respectively). Monetary assessment of wetland ecosystem services per year results in a minimum yearly loss of USD 30.05 million for peatlands and USD 197.86 million for marshes and swamps in USD (2007). This analysis is valuable for quantifying the impact of human footprint on wetlands, which is critical for ensuring sustainable development in wetland-rich areas.
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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 | 0.000 | 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".