Coherent response of lakes in Ontario, Canada to reductions in sulphur deposition: the effects of climate on sulphate concentrations
Bibliographic record
Abstract
Abstract. Sulphate deposition in south-central Ontario declined between 1976 and 2000 by more than 50%, whereas lake sulphate (SO42–) concentrations decreased by, on average, only half as much. To investigate the factors that controlled this slower than expected response, the temporal patterns in lake SO42– concentrations were compared with patterns in both deposition and climate, since climate has a major influence on the hydrological cycle in this part of the continent. To do this, the temporal coherence in SO42– concentrations between 9 lake basins was estimated using the intraclass correlation from a repeated-measures analysis of variance and two subsets of lakes were found (six in one group, four in the other), each with lakes having synchronous patterns. One subset (4 lakes) included the 3 with the longest water replenishment times (>3.4 yr) which are expected to respond to decreases in SO42– deposition more slowly. However, the average pattern reflecting the temporal changes of each of the two subsets was very similar. The response of both subsets of lakes to the decreasing SO42– deposition over two decades was independent of the degree of acidification or sensitivity to acidification of the lakes. In a determination of which factors best predicted each of those two subsets’ SO42– time series, good predictive models were produced by regional/global-scale climate indices, specifically the Southern Oscillation Index (SOI) describing the El Niño Southern Oscillation (ENSO) and the North Atlantic Oscillation Index (NAOI), as well as by SO42– deposition indices. When the predictor variables were combined, models which described the long-term changes in lake SO42– concentration best included the SOI, the NAOI and SO42– deposition. Thus, large-scale climate factors play a major role in determining the response of aquatic systems to changes in SO42– deposition, perhaps through their influence on lake and/or catchment processes that effectively delay recovery. Keywords: Atmospheric deposition, lake recovery, temporal trends, climate, temporal coherence
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".