Floral and Bird Excreta Semiochemicals Attract Western Carpenter Ants
Bibliographic record
Abstract
Ant colonies have vast and diverse nutritional needs but forager ants have limited mobility to meet these needs. Forager ants would accrue significant energy savings if they were able to sense and orient toward odor plumes of both carbohydrate and protein food sources. Moreover, if worker ants, like other flightless insects, had reduced olfactory acuity, they would not recognize the specific odor signatures of diverse carbohydrate and protein sources, but they may be able to orient toward those odorants that are shared between (macronutrient) food sources. Using the Western carpenter ant, Camponotus modoc , as a model species, we tested the hypotheses that (1) food sources rich in carbohydrates (aphid honeydew, floral nectar) and rich in proteins (bird excreta, house mouse carrion, cow liver infested or not with fly maggots) all prompt long-distance, anemotactic attraction of worker ants, and (2) attraction of ants to plant inflorescences (fireweed, Chamaenerion angustifolium ; thimbleberry, Rubus parviflorus ; and hardhack, Spiraea douglasii ) is mediated by shared floral odorants. In moving-air Y-tube olfactometer bioassays, ants were attracted to two of four carbohydrate sources (thimbleberry and fireweed), and one of four protein sources (bird excreta). Headspace volatiles of these three attractive sources were analyzed by gas chromatography-mass spectrometry, and synthetic odor blends of thimbleberry (7 components), fireweed (23 components), and bird excreta (38 components) were prepared. In Y-tube olfactometer bioassays, synthetic blends of thimbleberry and fireweed but not of bird excreta attracted ants, indicating that only the two floral blends contained all essential attractants. A blend of components shared between thimbleberry and fireweed was not attractive to ants. Our data support the conclusion that C. modoc worker ants can sense and orient toward both carbohydrate and protein food sources. As ants were selective in their responses to carbohydrate and protein resources, it seems that they can discern between specific food odor profiles and that they have good, rather than poor, olfactory acuity.
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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".