Sixty‐year legacy of human impacts on a high Arctic ecosystem
Bibliographic record
Abstract
Summary The high Arctic is the world's fasting warming biome, allowing access to sections of previously inaccessible land for resource extraction. Starting in 2011, exploration of one of the Earth's largest undeveloped coal seams was initiated in a relatively pristine, polar desert environment in the Canadian high Arctic. Due to the relative lack of historic anthropogenic disturbance, significant gaps in knowledge exist on how the landscape will be impacted by development. At an abandoned airstrip located near the area of current exploration, we used a disturbance case–control approach to evaluate the long‐term ecological consequences of high Arctic infrastructure disturbance to vegetation and sensitive, ice‐rich permafrost. We quantified: (i) long‐term effects on vegetation diversity, soil nutrients and abiotic ground conditions and (ii) the alteration of the ground surface topography and legacy of subsurface thermal changes. We found that in over 60 years since abandonment, the disturbed landscape has not recovered to initial conditions but instead reflects a disturbance‐initiated succession towards a different stable‐state community. Microtopography greatly influenced recovery patterns in the landscape. The terrain overlaying buried ice (ice‐wedge polygon troughs) was the most sensitive to disturbance and had a different species composition, decreased plot‐level species richness, significant increases in vegetation cover and a drastically reduced seasonal fluctuation in subsurface temperatures. In contrast, disturbed polygon tops showed resiliency in vegetation recovery, but still had remarkable increases in depth of seasonal soil thaw (active layer). Synthesis and applications . Our results indicate that disturbance effects differ depending on microtopographic features, leading to an increased patchiness of the landscape as found elsewhere in the Arctic. Managers who wish to lessen their impact on high Arctic environments should avoid areas of sensitive, ice‐rich permafrost, constrain the geographic scale of near‐surface ground disturbance, limit vegetation removal where possible and reseed disturbed areas with native species.
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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 | 0.001 | 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) | 0.003 | 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".