Fluctuations in density of an outbreak species drive diversity cascades in food webs
Bibliographic record
Abstract
Patterns in food-web structure have frequently been examined in static food webs, but few studies have attempted to delineate patterns that materialize in food webs under nonequilibrium conditions. Here, using one of nature's classical nonequilibrium systems as the food-web database, we test the major assumptions of recent advances in food-web theory. We show that a complex web of interactions between insect herbivores and their natural enemies displays significant architectural flexibility over a large fluctuation in the natural abundance of the major herbivore, the spruce budworm (Choristoneura fumiferana). Importantly, this flexibility operates precisely in the manner predicted by recent foraging-based food-web theories: higher-order mobile generalists respond rapidly in time and space by converging on areas of increasing prey abundance. This "birdfeeder effect" operates such that increasing budworm densities correspond to a cascade of increasing diversity and food-web complexity. Thus, by integrating foraging theory with food-web ecology and analyzing a long-term, natural data set coupled with manipulative field experiments, we are able to show that food-web structure varies in a predictable manner. Furthermore, both recent food-web theory and longstanding foraging theory suggest that this very same food-web flexibility ought to be a potent stabilizing mechanism. Interestingly, we find that this food-web flexibility tends to be greater in heterogeneous than in homogeneous forest plots. Because our results provide a plausible mechanism for boreal forest effects on populations of forest insect pests, they have implications for forest and pest management practices.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".