Tipping point arises earlier under a multiple-stressor scenario
Bibliographic record
Abstract
Anthropogenic impacts and global changes have profound implications for natural ecosystems and may lead to their modification, degradation or collapse. Increases in the intensity of single stressors may create abrupt shifts in biotic responses (i.e. thresholds). The effects of multiple interacting stressors may create non-additive responses, known as synergistic or antagonistic interactions. Here we combine both concepts-ecological thresholds and interactions between multiple stressors-to understand the effects of multiple interacting stressors along environmental gradients, and how this can affect the occurrence of thresholds. Using an experimental approach to investigate the effect of nutrient enrichment and saltwater intrusion on mortality in the zebra mussel, Dreissena polymorpha, we show that multiple stressors can create thresholds at lower levels of an environmental gradient. Our results reveal a major shortcoming in how we currently investigate these two ecological concepts, as considering them separately may be causing underestimation of thresholds and stressor-interaction impacts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.002 |
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; both teacher heads agree on what is shown here.
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".