Effect of Formic Acid Formulations on Honey Bee (Hymenoptera: Apidae) Colonies and Influence of Colony and Ambient Conditions on Formic Acid Concentration in the Hive
Bibliographic record
Abstract
The interaction between the effects of varroa, Varroa destructor Anderson & Trueman, and formic acid treatments on colonies of honey bees, Apis mellifera L., were examined in two field experiments. In experiment 1, colonies with low varroa levels were exposed to two different slow-release formulations and compared with untreated colonies. In experiment 2, colonies inoculated with varroa and uninoculated colonies were exposed to a slow-release formulation, a pour-on formulation, or were left untreated. The effects of treatments, hive temperature, and hive relative humidity on formic acid concentration in hive air also were examined. Slow-release formic acid application improved colony development in colonies that had been inoculated with varroa. However, in uninoculated colonies where the mean abundance of varroa was low, slow-release formic acid application suppressed colony development. The pour-on application did not have a negative impact on worker population growth in uninoculated colonies, but also it was not as effective as the slow-release treatment in improving population growth in varroa-inoculated colonies. Equivalent volumes of acid applied in pour-on and slow-release formulations provided the same cumulative dose in hive air but differed in the daily pattern of formic acid release. Colonies that were not inoculated with varroa had higher concentrations of formic acid in hive air than colonies that were inoculated with varroa on three of the five pour-on application dates. The data suggest that reductions in worker population and/or activity caused by varroa can interact with ambient conditions to affect the volatilization or sorption of formic acid in the hive.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".