Cladoceran diversity dynamics in lakes from a northern mining region: responses to multiple stressors characterized by alpha and beta diversity
Bibliographic record
Abstract
The lakes surrounding the iron ore mining region of Schefferville, Quebec, Canada, sit within a landscape of historical disturbances, two of which have been relatively well documented over time: metal contamination and nutrient loading. Based on the analysis of sediment cores, we used cladoceran zooplankton subfossil assemblages from two lakes located in Schefferville to track both alpha and beta diversity over the last 100+ years. We showed that high metal concentrations were correlated with decreased cladoceran diversity, and that the site that experienced both direct wastewater input and atmospheric metal loading (Lake Dauriat) had the greatest declines in cladoceran richness. In both lakes, turnover in cladoceran assemblages was highest in the mining period. During the period of mine closures and improvement of wastewater treatment, some decreases in metal enrichment in the sediments and increases in cladoceran richness were observed in Lake Dauriat. Overall, a combined use of species richness and beta diversity metrics showed alpha and beta diversity are not always congruent, and that there are various ways to interpret scenarios of temporal beta diversity in northern freshwater systems.
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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 | 0.000 |
| 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 | 0.000 |
| 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".