BACKGROUND: Pesticides are one of the most important anthropogenic‐related stressors. In times of global pollinator decline, the role of integrated farming and urban gardens in supporting wild pollinators is becoming increasingly important. We circulated an online questionnaire to survey plant protection practices among Hungarian farmers and garden owners with a particular emphasis on pollinator protection. RESULTS: We found that plant growers rely heavily on pesticide use, and pesticides are used widely in otherwise pollinator‐friendly gardens. Whether pesticide use practices were driven by expert opinion and respondent gender were the best predictors of pesticide use. Although most respondents supported pollinators, pesticides are also used widely among home garden owners, which can pose a non‐evident ecological trap for pollinator populations in the gardens. CONCLUSION: Special attention should be paid to implementing measures to reduce pesticide use not only in farmland, but also in home gardens. Environmental education and financial support through agroecological schemes could efficiently promote the transition away from pesticide use. However, whereas farmers can be encouraged to reduce pesticide use mostly by expert advice, garden owners are likely to rely on more conventional information channels. The attitudes of Hungarian plant growers can provide an insight into pesticide use practices of Central and Eastern European countries, but similar surveys are needed across Europe for a complete understanding of broad‐scale processes. This work lays the foundations for similar studies that can inform and facilitate the transformation to pesticide‐free farming and gardening. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Due to recent changes in regulation, acetamiprid has become the only neonicotinoid that can be applied without restrictions and in open field cultivations in the EU from 2021. We provide an overview of the current knowledge on the effects of this insecticide on bumblebees and assessed whether available empirical evidence supports the claim that acetamiprid poses negligible risk to these pollinators. We found that there is limited data on the lethal and sublethal effects of this pesticide on bumblebees. While risk assessment results suggest that field-realistic concentrations of acetamiprid have minor acute and chronic toxicity, detrimental sublethal effects, including reduced reproductive output, have been observed when bumblebees were exposed to high doses of this insecticide. We propose that further research on the topic is warranted as the more extensive application of acetamiprid may lead to such high concentrations in the field.

To understand the processes behind pollinator declines and for the conservation of pollination services, we need to understand fundamental drivers influencing pollinator behaviour. Here, we aimed to elucidate how wild bumblebees interact with three plant species and investigated their foraging behaviour with varying flower densities. We video-recorded Bombus terrestris in 60 × 60 cm quadrats of Lotus creticus, Persicaria capitata, and Trifolium pratense in urban areas of Terceira (Azores, Portugal). For the automated bumblebee detection and counting, we created deep learning-based computer vision models with custom datasets. We achieved high model accuracy of 0.88 for Lotus and Persicaria and 0.95 for Trifolium, indicating accurate bumblebee detection. In our study, flower cover was the only factor that influenced the attractiveness of flower patches, and plant species did not have an effect. We detected a significant positive effect of flower cover on the attractiveness of flower patches for flower-visiting bumblebees. The time spent per unit of inflorescence surface area was longer on the Trifolium than those on the Lotus and Persicaria. However, our result did not indicate significant differences in the time bumblebees spent on inflorescences among the three plant species. Here, we also justify computer vision-based analysis as a reliable tool for studying pollinator behavioural ecology.