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Environmental Science & Technology
Honeybees are essential pollinators for agriculture and natural ecosystems. Stressors like climate change, habitat loss and pesticide exposure threaten their ability to forage for pollen, a critical resource for colony survival. Researchers in ACS鈥� Environmental Science & Technology demonstrate that an artificial intelligence (AI)-based monitoring system combined with a computer model can link the exposure of neonicotinoid pesticides on individual honeybees to the health of the whole colony.

Neonicotinoid pesticides are widely used in agriculture. Plants absorb and distribute neonicotinoids throughout their tissues, making the plant鈥檚 pollen potentially harmful to honeybees. , neonicotinoid-exposed bees make fewer trips to collect pollen throughout the day. However, the connection between changes in individual honeybee pollen-foraging behavior and overall colony health hasn鈥檛 been widely researched. Now, a multidisciplinary team led by Ming Wang hopes to change this by combining field study data with computer modeling and AI-based monitoring.聽
The researchers repeated their 2019 pollen-foraging field experiments where they exposed honeybees to sublethal doses of neonicotinoids and then tracked the insects' activities with AI-based camera technology and traditional ecotoxicology methods. In this experiment, they analyzed the recently collected data using a computer simulation called BEEHAVE, which was designed to explore stress effects on honeybee colony dynamics.聽
Using their new approach, the team members found that even low neonicotinoid pesticide exposure led to less efficient pollen foraging on the individual and colony levels, which confirms their previous studies. 鈥淲e were surprised that we could replicate the findings of our first field experiment in 2019,鈥� says Silvio Knaebe, one of the researchers. 鈥淗oneybee colony behavior varies so much that statistically significant effects are difficult to detect.鈥澛�
Given these initial results, the researchers say their new model, with pollen-foraging behavior as a key parameter, could be a unique candidate for pesticide risk assessment in the field at both the individual honeybee and colony levels.聽
The authors acknowledge funding from the Federal Ministry of Food and Agriculture (Bundesministerium f眉r Ern盲hrung und Landwirtschaft) via the Federal Office for Agriculture and Food (Bundesanstalt f眉r Landwirtschaft und Ern盲hrung), Germany.
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