Temporal assessment of cumulative impacts from interacting disturbances of wildfires and lake-level changes on a small lake in the Western Canadian Arctic
Bibliographic record
Abstract
We analysed long-term ecosystem change in a small lake in the Tuktoyaktuk Coastlands (Northwest Territories, Canada). Lake 2B (unofficial name) has a history of polycyclic thaw slumping, associated with oligotrophic, clearwater conditions in this region. In 1968, Lake 2B was impacted by a wildfire that resulted in eutrophication, inferred from a rapid increase in the meso-eutrophic diatom Cyclostephanos in a sediment core. Eutrophic conditions were confirmed by water sampling in 2007 and 2017. Analysis of remote-sensing data revealed that Lake 2B experienced catastrophic drainage in 2012, likely in response to an extreme summer rainfall event. Field sampling confirmed that the lake re-filled between 2017 and 2023, with the re-filling resulting in re-oligotrophication. However, subfossil diatom assemblages showed that Cyclostephanos remained dominant. This contrasts with many temperate lakes, where recovery from eutrophication has been effectively tracked using diatom assemblages. We propose the lake experienced a hysteresis where exposure to an earlier disturbance (wildfire) influenced ecological responses to subsequent disturbance (lake drainage and re-filling). Overall, Lake 2B provides an interesting case study for understanding how interacting climate-related disturbances influence trajectories of Arctic lake ecosystem change, though it remains unclear if other lakes would respond similarly to past wildfires, lake drainage, and re-filling.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".