Lake salinization drives consistent losses of zooplankton abundance and diversity across coordinated mesocosm experiments
Bibliographic record
Abstract
Abstract Human‐induced salinization increasingly threatens inland waters; yet we know little about the multifaceted response of lake communities to salt contamination. By conducting a coordinated mesocosm experiment of lake salinization across 16 sites in North America and Europe, we quantified the response of zooplankton abundance and (taxonomic and functional) community structure to a broad gradient of environmentally relevant chloride concentrations, ranging from 4 to ca. 1400 mg Cl − L −1 . We found that crustaceans were distinctly more sensitive to elevated chloride than rotifers; yet, rotifers did not show compensatory abundance increases in response to crustacean declines. For crustaceans, our among‐site comparisons indicate: (1) highly consistent decreases in abundance and taxon richness with salinity; (2) widespread chloride sensitivity across major taxonomic groups (Cladocera, Cyclopoida, and Calanoida); and (3) weaker loss of functional than taxonomic diversity. Overall, our study demonstrates that aggregate properties of zooplankton communities can be adversely affected at chloride concentrations relevant to anthropogenic salinization in lakes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".