Long-term oxygen conditions assessed using chironomid assemblages in brook trout lakes from Nova Scotia, Canada
Bibliographic record
Abstract
We examined the larval remains of chironomids in 12 stocked brook trout lakes from Nova Scotia using 2 paleolimnological approaches (i.e., top–bottom approach and stratigraphic analyses). Limited monitoring data have indicated that almost all of the survey lakes contained poor coldwater-fish habitat; therefore, concerns have been raised that oxygen conditions have deteriorated and suitable habitat for brook trout may have declined. Our goal was to evaluate shifts in water quality, with a focus on understanding trends in hypolimnetic oxygen concentrations. No strong directional changes in the relative abundances of chironomids were recognized using top–bottom (12 lakes) and downcore stratigraphic (4 lakes) analyses. Chironomid assemblage compositions have not differed significantly between modern and preindustrial time periods (ANOSIM: R = −0.06, P = 0.94). Changes (if any) in oxygen conditions over the last ∼2 centuries likely were subtle and not of sufficient duration and (or) magnitude to strongly influence chironomid assemblage compositions through time. Detrended correspondence analysis of downcore assemblages indicated that taxa turnover was minimal (≤1 SD) at 3 of 4 lakes. We conclude that oxygen conditions (which our proxy data indicate were likely naturally low) have not deteriorated significantly since preindustrial times, and no overall directional trends are yet obvious in the paleolimnological record. Combining the often complimentary information gained from paleolimnological, monitoring, and modeling analyses, as we do here, can aid in the management of aquatic ecosystems and highlight the relative importance of regional trends in water quality and its influence on aquatic organisms such as recreationally significant salmonids.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".