IMPACT OF WAR ON THE WINTER SURVIVAL OF BEE COLONIES IN UKRAINE: MONITORING RESULTS FOR 2023-2024
Bibliographic record
Abstract
Over the last 17 years, Northern Hemisphere countries, including the United States, European countries, Canada, and Mexico, have reported significant rates of annual losses of honey bee colonies, Apis mellifera L. These losses have significant economic consequences for the beekeeping and agricultural sectors, and, primarily, for ecosystems. This study aimed to analyze the honey bee colonies losses after wintering 2023-2024 in Ukraine in the context of international monitoring coordinated by the COLOSS organization, under the conditions of the third year of the war. Data collection was carried out using a questionnaire designed by the COLOSS working group, adapted to Ukrainian respondents and supplemented by national coordinators. The sample size was 684 protocols. All administrative regions and physiographic regions of Ukraine, except Crimea were covered by survey. It was found that the total rate of honey bee colony losses in Ukraine after the wintering of 2023-2024 is 9.52 %, which does not differ significantly from the corresponding indicators for the previous two winterings: after the wintering of 2022-2023 - 10.75 %, after the wintering of 2021-2022 - 8.8 7%. Colony mortality was 5.2% (after the wintering of 2022-2023 - 6.5 %). Negative natural phenomena caused losses of 2.3%, and unsolvable problems with queens – 1.99 % of colonies (after the wintering of 2022-2023 – 1.27 % and 3.27 %, respectively). The lowest rate of colony losses was found in the mixed forest zone (4.8 %), while in the broadleaf forest zone – 10.6 %, in the steppe zone – 10.5 %, in the Ukrainian Carpathians – 9.3 % and in the forest-steppe zone – 8.3 %. Like ech year, most often the dead bee colonies had many dead bees into or in front of the hive (37.4 %), and the least often they showed features of starvation (5.9 %). 90 respondents keep their apiaries in areas affected by military operations. The apiaries of about 5% of the beekeepers have suffered various types of damage, and more than 3% of beekeepers have lost contact with their apiaries due a number of reasons related to the war. An inverse relationship between loss rate and size of the apiary has been shown, and for the first time, significantly lower losses have been identified in stationary apiaries compared to migratory ones. 14.2 % of colonies in the spring turned out to be weak, but with a productive queen. However, no significant difference in wintering success between apiaries with such colonies and without them was found. Almost all respondents (98%) treated their colonies againts Varroa mites. Amitraz-based drugs remain the most popular, as before. However, no correlation was found between the use of such agents and low colony losses.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".