Net effects of multiple stressors in freshwater ecosystems: a meta‐analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The accelerating rate of global change has focused attention on the cumulative impacts of novel and extreme environmental changes (i.e. stressors), especially in marine ecosystems. As integrators of local catchment and regional processes, freshwater ecosystems are also ranked highly sensitive to the net effects of multiple stressors, yet there has not been a large-scale quantitative synthesis. We analysed data from 88 papers including 286 responses of freshwater ecosystems to paired stressors and discovered that overall, their cumulative mean effect size was less than the sum of their single effects (i.e. an antagonistic interaction). Net effects of dual stressors on diversity and functional performance response metrics were additive and antagonistic, respectively. Across individual studies, a simple vote-counting method revealed that the net effects of stressor pairs were frequently more antagonistic (41%) than synergistic (28%), additive (16%) or reversed (15%). Here, we define a reversal as occurring when the net impact of two stressors is in the opposite direction (negative or positive) from that of the sum of their single effects. While warming paired with nutrification resulted in additive net effects, the overall mean net effect of warming combined with a second stressor was antagonistic. Most importantly, the mean net effects across all stressor pairs and response metrics were consistently antagonistic or additive, contrasting the greater prevalence of reported synergies in marine systems. Here, a possible explanation for more antagonistic responses by freshwater biota to stressors is that the inherent greater environmental variability of smaller aquatic ecosystems fosters greater potential for acclimation and co-adaptation to multiple stressors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it