Assessment of recent environmental changes in New Brunswick (Canada) lakes based on paleolimnological shifts in diatom species assemblages
Bibliographic record
Abstract
New Brunswick lakes are subjected to multiple environmental stressors, such as atmospheric acid deposition and climate change. In the absence of long-term environmental data, the impacts of these stressors are not well understood. Long-term effects of environmental change on diatom species assemblages were assessed in the sediments of 16 New Brunswick lakes using paleolimnological approaches. A regional trend of increasing Cyclotella stelligera Cleve & Gunrow and decreasing Aulacoseira species complex was recorded in most lakes. Detailed paleolimnological analyses of Wolfe, Cundy, and West Long lakes revealed varying degrees of species change, with assemblage shifts beginning ca. 1900 CE (common era). These species trends are not consistent with acidification. However, linear regression of mean July temperature with time for two New Brunswick historical instrumental temperature records revealed statistically significant warming over the past century. The shift from heavily silicified tychoplanktonic Aulacoseira species to small planktonic diatom species, such as C. stelligera, is consistent with paleolimnological inferences of warming trends recorded in several other lake regions of the Northern Hemisphere. These assemblage shifts are likely due to recent climate change and may be mediated by reduced ice cover and (or) increased thermal stability (decreased lake mixing) during the open water period.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".