No evidence for dominance–discovery trade-offs in <i>Pheidole</i> (Hymenoptera: Formicidae) assemblages
Bibliographic record
Abstract
Understanding the mechanisms that allow species coexistence across spatial scales is of great interest to ecologists. Many such proposed mechanisms involve trade-offs between species in different life-history traits, with distinct trade-offs being expected to be prevalent at varying temporal and spatial scales. The dominance–discovery trade-off posits that species differ in their ability to find and use resources quickly, in contrast to their ability to monopolize those resources, a mechanism analogous to the competition-colonization trade-off. We investigated the occurrence of this structuring mechanism in the genus Pheidole Westwood, 1839 (Hymenoptera: Formicidae) assemblages in Atlantic Forest remnants. According to the dominance–discovery trade-off, consistent interspecific variation should be observed along the axis of discovery and dominance. We established 55 sampling units across two sites, with each unit consisting of a sardine bait monitored for 3 h. There was no distinction among Pheidole species in their ability to find or dominate food sources, suggesting that the dominance–discovery trade-off does not explain their coexistence. The low levels of aggression between Pheidole species could prevent the establishment of dominance hierarchies, whereas the species order of arrival at food sources could allow for resource partitioning through priority effects.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".