The Effects of Switching Behavior on the Evolutionary Diversification of Generalist Consumers
Bibliographic record
Abstract
Mathematical models of consumer-resource systems explore the evolution of a morphological trait that determines two resource acquisition rates in a generalist consumer. The consumer also has the ability to adjust its relative consumption of the two resources via behavioral (or developmental) plasticity subject to a trade-off. The analysis examines both stable systems and those with sustained fluctuations in abundance. In both cases, it seeks to determine how the behavioral choice affects the evolution of the morphological characters. The presence of adaptive switching behavior transforms the shape of the relationship between the morphological character and fitness in a manner that usually leads to evolution of two or more morphological types. As in models without switching, the presence of sustained cycles in resource densities often allows the evolution of a generalist as well as two specialists. However, switching expands and shifts the parameter regions yielding this outcome and in some cases allows the evolution and coexistence of at least two generalists as well as the two specialists. This level of diversity supported by only two resources is not seen in the absence of behavioral choice and resource cycles. The results suggest major roles for both behavior and environmental variation in adaptive radiation.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".