And then there is the issue of models. Cresswell and Thompson wrote a detailed response to the use of modeling by Mickaël Henry, et al as reported in Science Magazine

Excerpts:

Henry et al. (Reports, 20 April, p. 348) used a model to predict that colony collapse in honey bees could be precipitated by pesticide-induced intoxication that disrupts navigation. Here, we show that collapse disappears when the model is recalculated with parameter values appropriate to the season when most pesticide-treated flowering crops bloom.

No published field experiment has yet had sufficient statistical power to detect effects on colonies of the magnitude observed on individual bees in the laboratory. When decisive experiments are unavailable, scientists may instead make forecasts with models and computer simulations. This approach has been used in the case of global climate change, and the results have the potential to be highly influential among policy-makers and regulators.

Henry et al. populated virtually all parameters in their model with empirically based values except one, namely w. Parameter w moderates the maximum daily rate of production of new workers, L, so that it has a density-dependent sigmoidal response: L × N / (N + w), where N is the number of adult bees in the colony.

 Thus, w represents the colony size at which new workers are produced at half the maximum rate. The originators of the model appear to have chosen a value of w to generate model outputs that fit observations of the average age of onset of foraging by adult bees and their overall life span.

 The model’s output is very sensitive to the value of w. Like the model’s originators, Henry et al. assumed that w = 27,000, but this is unrealistic because a colony of 18,000 adult bees then grows only by 11% in a month in the absence of pesticide.

 In spring or early summer, which is when bees in Europe are typically exposed to neonicotinoid treated mass-flowering crops such as oilseed rape (Brassica napus), a colony of this size can increase by >40% over 30 days, which is consistent with w ≈ 16,000. Indeed, using w = 16,000 in the model very accurately predicts observations of adult life span on similarly sized colonies in the absence of pesticide.

From this interpretation, the model predicts that a month of pesticide exposure leaves colony size virtually unchanged and
would not precipitate colony collapse.

There is no question that dietary thiamethoxam harms honey bee colonies by elevating the mortality of adult foragers through navigation failure, at least when the entire daily intake of a forager is consumed in a single dose. However, what is at issue is whether thiamethoxam is capable of causing colony collapse. 

Our results suggest that dietary thiamethoxam would not precipitate collapse in healthy colonies in spring, but this does not rule out the possibility that colonies will be more vulnerable later in the year when their capacity to replace lost workers has diminished. 

Based on our analysis, we argue that (i) the forecast impact of thiamethoxam on honey bees is nuanced, being highly contingent on colonies’ capacity for producing workers; (ii) pesticide regulators should be cautious in using this model’s outcomes when formulating a stance on controlling the future use of thiamethoxam; and (iii) colony-growth models may have a very important role in future risk assessments, but further research is required to ensure that they are fully validated and appropriately configured for the environmentally relevant context in which they are to be applied.

www.sciencemag.org SCIENCE VOL 337 21 SEPTEMBER 2012

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