Impacts of sequential salinity and heat stress are recovery time-specific in freshwater crustacean, Daphnia pulicaria
Bibliographic record
Abstract
Stressors can interact to affect animal fitness, but we have limited knowledge about how temporal variation in stressors may impact their combined effect. This limits our ability to predict the outcomes of pollutants and future dynamic environmental changes. Elevated salinity in freshwater ecosystems has been observed worldwide. Meanwhile, heatwaves have become more frequent and intensified as an outcome of climate change. These two stressors can jointly affect organisms; however, their interaction has rarely been explored in the context of freshwater ecosystems. We conducted lab experiments using Daphnia pulicaria, a key species in lakes, to investigate how elevated salinity and heatwave conditions collectively affect freshwater organisms. We also monitored the impacts of various recovery times between the two stressors. Daphnia physiological conditions (metabolic rate, Na+-K+-ATPase (NKA) activity, and lipid peroxidation level) and life history traits (survival, fecundity, and growth) in response to salt stress as well as mortality in heat treatment were examined. We found that Daphnia responded to elevated salinity by upregulating NKA activity and increasing metabolic rate, causing a high lipid peroxidation level. Survival, fecundity, and growth were all negatively affected by this stressor. These impacts on physiological conditions and life history traits persisted for a few days after the end of the exposure. Heat treatments caused mortality in Daphnia, which increased with rising temperature. Results also showed that individuals that experienced salt exposure were more susceptible to subsequent heat stress, but this effect decreased with increasing recovery time between stressors. Findings from this work suggest that the legacy effects from a previous stressor can reduce individual resistance to a subsequent stressor, adding great difficulties to the prediction of outcomes of multiple stressors. Our work also demonstrates that cross-tolerance/susceptibility and the associated mechanisms remain unclear, necessitating further investigation.
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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 | 0.000 |
| 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".