Evidence for pollinator cost and farming benefits of neonicotinoid seed coatings on oilseed rape.

Chronic exposure to neonicotinoid insecticides has been linked to reduced survival of pollinating insects at both the individual and colony level, but so far only experimentally. Analyses of large-scale datasets to investigate the real-world links between the use of neonicotinoids and pollinator mortality are lacking. Moreover, the impacts of neonicotinoid seed coatings in reducing subsequent applications of foliar insecticide sprays and increasing crop yield are not known, despite the supposed benefits of this practice driving widespread use. Here, we combine large-scale pesticide usage and yield observations from oilseed rape with those detailing honey bee colony losses over an 11 year period, and reveal a correlation between honey bee colony losses and national-scale imidacloprid (a neonicotinoid) usage patterns across England and Wales. We also provide the first evidence that farmers who use neonicotinoid seed coatings reduce the number of subsequent applications of foliar insecticide sprays and may derive an economic return. Our results inform the societal discussion on the pollinator costs and farming benefits of prophylactic neonicotinoid usage on a mass flowering crop.

Using reports of bee mortality in the field to calibrate laboratory-derived pesticide risk indices.

Mounting evidence suggests that pollinators worldwide are experiencing dramatic population declines, and exposure to pesticides is one of the factors that can account for this. By making use of a database containing more than two decades of honey bee (Apis mellifera) hive poisoning incidents from the United Kingdom (Wildlife Incident Investigation Scheme [WIIS]) and corresponding pesticide use surveys, we attempted to explain honey bee poisoning incidents in the field using models derived from pesticide use information, laboratory-generated bee toxicity data (defined as a hazard ratio; application rate divided by LD(50)), and physico-chemical properties of the applied pesticides. Logistic regression analyses were used to assess the relationship between honey bee poisoning incidents in the field and these parameters. In analyzing models with multiple dimensions, we selected the best model by the best subset method, an iterative method based on maximum likelihood estimation, and Akaike's information criterion. Results suggested that the size of the area treated and hazard ratios calculated from application rates and oral or contact toxicity (but the latter especially) can be used to predict the likelihood that honey bee mortality will occur. Model predictions also suggest that some insecticides carry an extreme risk for bees, despite the lack of documented incidents.