Environmental fluctuations can stabilize food web dynamics by increasing synchrony
Bibliographic record
Abstract
Natural food webs are species-rich, but classical theory suggests that they should be unstable and extinction-prone. Asynchronous fluctuations in the densities of competing consumers can stabilize food web dynamics in constant environments. However, environmental fluctuations often synchronize dynamics in nature. Using the same 'diamond-shape' food web model first used to demonstrate the stabilizing effects of asynchrony in constant environments, we show that weak-to-moderate environmentally induced fluctuations in consumer mortality rates stabilize food webs while disrupting asynchrony. Synchrony actually promotes stability because: (i) synchronous declines in consumer density reduce the maximum abundance of top predators and (ii) resource competition quickly converts synchronous increases in consumer density into synchronous declines. These results are robust to details of food web topology and the implementation of environmental fluctuations. The fluctuation strengths that enhance stability are within the range experienced naturally by many species, suggesting that stabilization via environmental fluctuations is a realistic possibility.
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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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".