Multiple anthropogenic stressors cause ecological surprises in boreal lakes
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
Abstract The number of combinations of anthropogenic stressors affecting global change is increasing; however, few studies have empirically tested for their interactive effects on ecosystems. Most importantly, interactions among ecological stressors generate nonadditive effects that cannot be easily predicted based on single‐stressor studies. Here, we corroborate findings from an in situ mesocosm experiment with evidence from a whole‐ecosystem manipulation to demonstrate for the first time that interactions between climate and acidification determine their cumulative impact on the food‐web structure of coldwater lakes. Interactions among warming, drought, and acidification, rather than the sum of their individual effects, best explained significant changes in planktonic consumer and producer biomass over a 23‐year period. Further, these stressors interactively exerted significant synergistic and antagonistic effects on consumers and producers, respectively. The observed prevalence of long‐ and short‐term ecological surprises involving the cumulative impacts of multiple anthropogenic stressors highlights the high degree of uncertainty surrounding current forecasts of the consequences of global change.
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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) | 0.000 | 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 it