Elevated metal concentrations inhibit biological recovery of <scp>C</scp>ladocera in previously acidified boreal lakes
Bibliographic record
Abstract
Summary Lakes near S udbury, C anada, have been exposed to intense acidification and metal contamination from nearby mining and smelting operations. Although lakewater p H improved substantially following the implementation of emission controls in the late 1960s, biological recovery continues to lag behind chemical recovery. We assessed the current state of biological recovery (relative to pre‐impact times) using multiproxy palaeolimnological records from two nearby lake districts ( S udbury and K illarney), both impacted by acidification but having experienced differences in metal contamination due to their respective distances from smelters. Twentieth century cladoceran shifts were most pronounced in the acidified and metal‐contaminated S udbury lakes, with assemblage changes tracking industrial activity. C hydorus brevilabris increased markedly in dominance, largely at the expense of B osmina spp. In contrast, the K illarney lakes, with similar changes in p H but lower C u and N i inputs than the S udbury lakes, experienced minimal changes within their sedimentary cladoceran assemblages. These regional differences in cladoceran impact and recovery patterns are best explained by varying levels of C u and N i contamination, with concentrations of these metals still exceeding provincial water quality guidelines in the S udbury lakes. Biological recovery in these systems appears to be inhibited by persistent high metal levels. Increased lake primary production and coincident shifts in cladoceran assemblages over the past approximately 40 years in all the study lakes suggest that climate impacts may be gaining prominence as drivers of ecological change, and therefore a return to the biotic structure of the pre‐smelter era is unlikely.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".