Dynamics of Compartmented and Reticulate Food Webs in Relation to Energetic Flows
Bibliographic record
Abstract
Using simple food webs, we address how the interactions of food web structure and energetic flows influence dynamics. We examine the effect of food web topologies with equivalent energetics (i.e., trophic interactions are equivalent at each trophic level), following which we vary energetic flows to include weak and strong interactions or nonequivalent energetics. In contrast to some work (Pimm 1979), we find that compartmented webs are more stable than reticulate webs. However, we find that nonequivalent energetics can stabilize previously unstable reticulate structures. It is not only weak flows that can be stabilizing but also the arrangement of the flows that emphasizes stabilizing mechanisms. We find that the main stabilizing mechanism is asynchrony, where structures and energetic arrangements that decrease synchrony such as internal segregation or competition will stabilize dynamics. Since compartments allow prey dynamics to behave somewhat independently, compartmentation readily promotes stability. In addition, these results can be scaled from simple food webs to more complex webs with many interacting subsystems so that linking weak subsystems to strong ones can stabilize dynamics. We show that food web dynamics are determined not only by topology but also the arrangement of weak and strong energetic flows.
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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".