Factors influencing the structure of macroinvertebrate communities in subarctic lakes affected by wildfires
Bibliographic record
Abstract
Fires are a natural phenomenon in the boreal forest, but their frequency is expected to increase over the coming century. Fires may affect water quality and invertebrates in lakes, but there have been few studies in the northern boreal forest to describe these impacts. We collected data on water quality, macrophytes, and invertebrates from 20 lakes in the Sahtú Settlement Area of the Northwest Territories. Nine lakes were affected by fires in their catchments 4–5 years before data collection, while eleven were not. Our results showed that few water quality variables were associated with fires. However, remote sensing and field observations suggested that macrophyte biomass was higher in lakes affected by burns, and this variable was a significant predictor of invertebrate composition. Burn history was an important predictor of the richness and abundance of invertebrates, but natural variability in lake properties was more important for explaining differences among lakes. Our results suggest that a better understanding of the effects of wildfires might be gained by examining how postfire changes in macrophytes affect other trophic levels.
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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 | 0.001 | 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 | 0.000 |
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".