Potential marine benthic macro-invertebrates’ responses to flooding: in vitro responses to a combination of freshwater exposure, low pH and high turbidity on three intertidal mollusks
Bibliographic record
Abstract
In estuaries, flooding of natural or anthropogenic origin cause a sharp decrease in salinity and pH as well as an increase in turbidity that can be maintained for several days. Although salinity is the main biogeographical determinant in these ecosystems where it changes along a dynamic gradient, the responses of benthic intertidal communities to intense hypoosmotic stress may differ from those caused by daily and seasonal salinity variations that are typically studied. In addition, the response of these communities to several combined stressors encountered during floods (decreased salinity and pH, increased turbidity) has rarely been studied. Here, we aim to evaluate the relative sensitivity of three benthic macroinvertebrate species (Littorina saxatilis, Limecola balthica and Mytilus spp.) to conditions mimicking spring flooding. We measured the survival rate of organisms exposed to a gradient of periodic exposure (12 treatments, characterized by a period of exposure lasting 0 to 9 days interspersed with 24 hours of exposure to marine salt water, over a continuous six-weeks cycle) in acidic and turbid freshwater (pH 5.7, 60 NTU), and in untreated freshwater (pH 7.7, 0 NTU). For the three species, the mortality was higher in the treatments in the acidic and turbid water, and in the treatments with the longest period of exposure. L. saxatilis showed the highest mortality rate, followed by L. balthica. Mytilus spp. showed almost no mortality. Longer and more frequent flooding might have an impact on estuaries invertebrate communities. Our study also highlights the importance of considering combined factors that are more representative of natural conditions.
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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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".