Effects of prolonged sedimentation from permafrost degradation on macroinvertebrate drift in Arctic streams
Bibliographic record
Abstract
Abstract Retrogressive thaw slumps are areas of unstable degraded permafrost that often drain into nearby watersheds, leading to increased sediment loads and changes in water quality. Thaw slumps are prevalent across the Arctic, including western Canada, Alaska, and Russia, and high‐altitude areas of western China. Over the past several decades, increased temperatures and precipitation in the Arctic have led to increases in the size and frequency of thaw slumps. Our study explored the effects of prolonged sedimentation from thaw slumps in the Peel Plateau, NWT, Canada on benthic macroinvertebrate drift, an important biological function of stream ecosystems. Though sedimentation is known to initiate a catastrophic drift response, studies have generally not considered the drift response to ongoing, long‐term perturbation. Drift densities and sediment loads were measured using drift nets and sediment traps at paired sites upstream and downstream of thaw slumps. We compared drift densities and sediment loads between sites and examined how drift differed over a fine‐sediment gradient. The amount of suspended and settling fine sediments increased significantly at downstream sites. Drift densities decreased at downstream sites; however, when drift was corrected for benthic abundance at each site, there was an increase in proportional drift density associated with increased fine sediments. These results indicate that prolonged impacts from thaw slumps result in lower macroinvertebrate abundance and higher proportional drift relative to undisturbed sites. Ultimately, increased sediment loads from thaw slumps represent a chronic stressor that will continue to prevent recovery of macroinvertebrate communities at impacted sites until these features stabilize.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".