The Trans-Alaska Pipeline System Facilitates Shrub Establishment in Northern Alaska
Bibliographic record
Abstract
The Arctic tundra is undergoing many environmental changes in addition to increasing temperatures: these changes include permafrost degradation and increased shrubification. Disturbances related to infrastructure can also lead to similar environmental changes. The Trans-Alaska Pipeline System (TAPS) is an example of infrastructure that has made a major imprint on the Alaskan landscape. This paper assesses changes in shrub presence along the northernmost 255 km of the TAPS. We used historical satellite imagery from before construction of the TAPS in 1974 and contemporary satellite imagery from 2010 to 2016 to examine changes in shrub presence over time. We found a 51.8% increase in shrub presence adjacent to the pipeline compared to 2.6% in control areas. Additionally, shrub presence has increased significantly more in areas where the pipeline is buried, indicating that the disturbances linked to pipeline burial have likely created favorable conditions for shrub colonization. These results are important for predicting potential responses of tundra vegetation to disturbance, which will be crucial to forecasting the future of Arctic tundra vegetation.
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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) | 0.001 | 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; both teacher heads agree on what is shown here.
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".