The effects of salinity on plankton and benthic communities in the Great Salt Lake, Utah, USA: a microcosm experiment
Bibliographic record
Abstract
Saline lakes change in size and salinity because of natural climate variability and especially from inflow diversions, which threaten life in these waters. We conducted a microcosm experiment in 12 L containers using organisms from the Great Salt Lake to determine how salinities ranging from 10 to 275 g·L−1 influenced the ecosystem. After 30 days, brine shrimp (Artemia franciscana) were nearly absent in salinities of 10 g·L−1 (where fish survived) and >225 g·L−1. As salinities increased from 75 to 225 g·L−1, final masses decreased 60% and their total biomass decreased fourfold. Copepod and rotifer biomasses were negligible at salinities >50 g·L−1. Brine fly (Ephydra gracilis) final biomass decreased 45% as salinity increased from 50 to 250 g·L−1. When Artemia and other grazers were abundant, phytoplankton chlorophyll levels were near 4.0 μg·L−1, but when grazing rates declined at higher salinities, phytoplankton chlorophyll increased to 130 μg·L−1. Mean periphyton chlorophyll levels showed the reverse pattern. Denitrification decreased total N concentrations during the experiment, resulting in final N:P ratios indicative of algal nitrogen limitation. The microcosm experiment demonstrated the strong influence of salinity on the entire ecosystem and highlighted the need for careful management of salt lakes to maintain appropriate salinities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".