Consequences of climate and body size on the foraging performance of seed‐eating ants
Bibliographic record
Abstract
1. Changes in climatic factors could have major effects on the foraging performance of animals. To date, however, no study has attempted to examine the concurrent effect of different climatic factors on foraging performance of individual organisms. 2. In the present study, this issue was addressed by studying changes in foraging performance of seed‐eating ant colonies of the genus Messor in response to variation in precipitation and ambient temperature along a macroecological gradient. In addition, we examined the way three colony‐level attributes, foraging distance, forager number, and variance in worker‐size, could affect foraging performance in those ants. Foraging performance was measured as size matching, i.e. the correlation between forager size and load size. The study was carried out for 2 years in six sites along a south‐north productivity gradient in a semi‐arid region of the E astern‐ M editerranean. 3. Size matching increased with increased precipitation as well as with an increase in worker‐size variability, but slightly decreased with increasing temperatures, as predicted by foraging‐decision models. In contrast, foraging distance had no effect on size matching. Interestingly, size matching showed a unimodal relationship with forager number. 4. These results indicate that interplay between climate and body size affects foraging performance either directly via physiological constraints, or indirectly through their effect on food availability. Moreover, this is one of the first evidences to support the assumption that ant colonies can differ in their ability to optimally allocate their workforce in natural environments. This emphasises the importance of studying the way foraging strategies vary across environmental gradients at macroecological scales.
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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 | 0.001 |
| 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) | 0.001 | 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".