Reduced Honeybee Pollen Foraging under Neonicotinoid Exposure: Exploring Reproducible Individual and Colony Level Effects in the Field Using AI and Simulation

Environmental Science & Technology, Journal Year: 2025, Volume and Issue: unknown

Published: March 7, 2025

Honeybees (Apis mellifera) are important pollinators. Their foraging behaviors essential to colony sustainability. Sublethal exposure pesticides such as neonicotinoids can significantly disrupt these behaviors, in particular pollen foraging. We investigated the effects of sublethal doses neonicotinoid imidacloprid on honeybee foraging, at both individual and levels, by integrating field experiments with artificial intelligence (AI)-based monitoring technology mechanistic simulations using BEEHAVE model. Our results replicated previous findings, which showed that selectively reduces level, minimal impact nectar Individually marked exposed honeybees exhibited prolonged trips, reduced frequency, instances drifting likely due impaired cognitive functions altered metabolism. These behavioral changes level corroborated model predictions derived from BEEHAVE, highlights value combining experimental simulation approaches disentangle underlying mechanisms through foragers scale up dynamics. findings have implications for future pesticide risk assessment, we provide a robust feeding study design evaluating colonies real landscapes, could improve realism higher-tier ecological assessment.

Language: Английский

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Utilization of biochar as a carrier for the integrated controlled release of fertilizers and pesticides: Synergistically reducing application rates and enhancing efficiency

Industrial Crops and Products, Journal Year: 2025, Volume and Issue: 232, P. 121235 - 121235

Published: May 24, 2025

Language: Английский

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Expanding the Scope of the Bumblebee Model BEE‐STEWARD: A Simple Foraging Module Facilitates the Parameterization

Ecology and Evolution, Journal Year: 2025, Volume and Issue: 15(5)

Published: May 1, 2025

ABSTRACT The BEE‐STEWARD model simulates the population dynamics and behavior of bumblebees, including foraging, in remarkable detail, allowing impact various stressors on their populations to be assessed. To support underlying detailed mechanistic descriptions, requires extensive parameterization, corolla depth, which affects handling time foraging bees, for each flower species simulated landscape. However, this approach limits applicability due lack data depths, while also resulting unrealistic trip durations. Here we present a simplified module that uses constant thus eliminating need parameterize depth. This simplification allows us both apply large scales assume times reproduce observed Our new large‐scale projections with BEE‐STEWARD. increases its value policy contexts contributes understanding mitigating bumblebee declines.

Language: Английский

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Using honey bee flight activity data and a deep learning model as a toxicovigilance tool

Ecological Informatics, Journal Year: 2024, Volume and Issue: 81, P. 102653 - 102653

Published: May 24, 2024

Automatic monitoring devices placed at the entrances of honey bee hives have facilitated detection various sublethal effects related to pesticide exposure, such as homing failure and reduced flight activity. These further demonstrated that different neurotoxic molecules produce similar impacts on The these was conducted a posteriori, following recording activity data. This study introduces method using an artificial intelligence model, specifically recurrent neural network, detect pesticides in real-time based model trained dataset comprising 42,092 records from 1107 control 1689 pesticide-exposed bees. able classify bees healthy or number flights minutes spent foraging per day. least accurate (68.46%) when only five days were used for training. However, highest classification accuracy 99%, Cohen Kappa 0.9766, precision 0.99, recall F1-score 0.99 achieved with 25 data, signifying near-perfect ability. results underscore highly predictive performance AI models toxicovigilance highlight potential our approach cost-effective risks due exposure populations.

Language: Английский

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Buzzing with Intelligence: Current Issues in Apiculture and the Role of Artificial Intelligence (AI) to Tackle It

Insects, Journal Year: 2024, Volume and Issue: 15(6), P. 418 - 418

Published: June 4, 2024

Honeybees (

Language: Английский

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