Biological responses to permafrost thaw slumping in Canadian Arctic lakes
Bibliographic record
Abstract
Summary 1. Rapid environmental change occurring in high‐latitude regions has the potential to cause extensive thawing of permafrost. Retrogressive thaw slumps are a particularly spectacular form of permafrost degradation that can significantly impact lake–water chemistry; however, to date, the effects on aquatic biota have received little attention. 2. We used a diatom‐based palaeolimnological approach featuring a paired lake study design to examine the impact of thaw slumping on freshwater ecosystems in the low Arctic of western Canada. We compared biological responses in six lakes affected by permafrost degradation with six undisturbed, reference lakes. 3. Slump‐affected lakes exhibited greater biological change than the paired reference systems, although all systems have undergone ecologically significant changes over the last 200 years. Four of the six reference systems showed an increase in the relative abundance of planktonic algal taxa (diatoms and scaled chrysophytes), the earliest beginning about 1900, consistent with increased temperature trends in this region. 4. The response of sedimentary diatoms to thaw slumping was understandably variable, but primarily related to the intensity of disturbance and associated changes in aquatic habitat. Five of the slump‐affected lakes recorded increases in the abundance and diversity of periphytic diatoms at the presumed time of slump initiation, consistent with increased water clarity and subsequent development of aquatic macrophyte communities. Slump‐affected lakes generally displayed lower nutrient levels; however, in one system, thaw slumping, induced by an intense fire at the site in 1968, ostensibly led to pronounced nutrient enrichment that persists today. 5. Our results demonstrate that retrogressive thaw slumping represents an important stressor to the biological communities of lakes in the western Canadian Arctic and can result in a number of limnological changes. We also show that palaeolimnological methods are effective for inferring the timing and response of aquatic ecosystems to permafrost degradation. These findings provide the first long‐term perspective on the biological response to permafrost thaw, a stressor that will become increasingly important as northern landscapes respond to climate change.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".