An introduction to the Dorset special issue: transforming understanding of factors that regulate aquatic ecosystems on the southern Canadian Shield
Bibliographic record
Abstract
This special issue demonstrates that aquatic ecosystems on the south-central Canadian Shield have changed in many ways over the last three decades. El Niño cycles have synchronized multilake dynamics in lake-water chemistry and in several components of the aquatic biota. Overlain on this cyclic regional pattern, phosphorus, sulphate, and calcium levels have all declined, whereas alkalinity has not yet risen in the most acid-sensitive study lakes, despite large reductions in SO2 emissions. Further, novel and unanticipated stressors have appeared, including nonindigenous predator introductions, Ca decline, salinity increase, and autumn spikes in metals following El Niño induced droughts. The resident biota are clearly responding not only to the familiar historical phosphorus and acid stressors, but also to the interactive effects of changes in multiple stressors in a warming environment. Lakes are best managed with an understanding of dominant limnological trends, their causes, and their responses to past management interventions. The research conducted at the Dorset Environmental Science Centre indicates “progress but no cigar” on acid rain, proof of climate variability as a direct and indirect regulator of south-central Shield ecosystems, and the emergence of novel stressors, the effects of which we cannot yet fully predict.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.033 | 0.007 |
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".