Predicting soil neonicotinoid content in agricultural landscapes using indirect indicators.

Area of Science:

• Environmental Science
• Ecotoxicology
• Agricultural Science

Background:

• Neonicotinoid insecticides contribute to pollinator decline.
• Pesticide persistence and mobility lead to soil and non-target vegetation contamination.
• Predicting soil contamination is challenging, particularly with limited pesticide use data.

Purpose of the Study:

• To assess the potential of using proxies like cropping history and landscape structure to predict neonicotinoid soil contamination.
• To analyze neonicotinoid levels in agricultural soils and evaluate associated risks.
• To determine factors influencing soil contamination in the absence of recorded pesticide treatments.

Main Methods:

• Analysis of seven neonicotinoids in soil samples from 86 agricultural sites in Belgium.
• Assessment of contamination in relation to cropping history, landscape structure, and recorded treatment data.
• Calculation of hazard quotients to evaluate risk exposure through soil contact.

Main Results:

• Neonicotinoids detected in 78% of sites; imidacloprid and clothianidin were most frequent.
• Contamination occurred in 69% of sites without recent recorded treatment and 33% with no treatment history.
• Soil contact exposure risk was high for clothianidin (44%) and imidacloprid (19%).
• Treatment history, not landscape structure, better predicted contamination in treated sites.
• Predicting contamination was difficult without considering non-arable sites.

Conclusions:

• Soil contamination by neonicotinoids is widespread, even without recent recorded use.
• Treatment history is a useful, though imperfect, predictor of soil contamination.
• Landscape structure has limited predictive power for neonicotinoid soil contamination.
• Accurate contamination prediction requires considering non-arable land and informing agri-environmental policies.