Does altering patch number and connectivity change the predatory functional response type? Experiments and simulations in an acarine predator–prey system
Bibliographic record
Abstract
In multipatch landscapes, understanding the role of patch number and connectivity is key for the conservation of species under processes such as predation. The functional response is the most basic form of the predatorprey interaction. Two common response types exist: a decelerating curvilinear increase in prey consumption with prey density to a plateau (type II) and a sigmoidal-shaped curve (type III). Type II responses have been observed for a variety of predators, though only type III responses allow long-term persistence and are demographically stabilizing. We tested the hypothesis that the functional response type can change from a type II to a type III with increasing patch number and (or) decreasing connectivity. The predatory mite Amblyseius fallacis (Garman, 1948) has previously been shown to have a type II response when feeding on Panonychus ulmi (Koch, 1839). We examined this predatorprey interaction using experiments that varied in patch number, and simulations that varied in both patch number and connectivity. In no experimental or simulation trial did altering patch number or connectivity change the predator's functional response from type II to type III, even with an 80-fold decrease in patch connectivity. How do predators with this demographically destabilizing functional response persist? Hypotheses regarding metapopulations and alternative prey are discussed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".