We have reached an important landmark in our work on bee health at EFSA. Today we publish detailed information about the predictive model that will be required by EFSA to enable it to assess the impact of pesticides on honeybee colony health, in the context of multiple stressors relating to:
• the environment (landscape and weather) in which the colony is located;
• biological agents that might be adversely affecting the hive including Varroa mites and Nosema infection; and
• certain beekeeping practices.
Within the next few weeks we will be asking interested parties with relevant expertise to submit tenders for the task of developing the model itself – so please keep an eye on this blog and the EFSA Twitter account for an announcement.
As a next step, to be completed in the early part of 2017, the MUST-B working group will be designing a data collection protocol, to guide the collection of data from several sites in Europe. This will enable us to test how well the model performs under different environmental scenarios.
Why do we need a model?
It’s now well understood that a single honey bee colony is a complicated place. It’s often described as “a superorganism of individuals” (including a queen, eggs, larvae, pupae, workers, drones and foragers) with lots of very different processes (caring for the queen, eggs and larvae, foraging for pollen, nectar and water, processing and using in-hive food stores, regulating the temperature within the colony, and so on). As a further layer of complexity, each colony is placed within a landscape with distinct seasonal variations in the availability of flowers and other factors.
Experimental studies can help us to better understand specific processes, such as the impact of a particular pesticide on the behaviour of foraging bees. However, it can be difficult to extrapolate from such studies to the likely effect on the overall honey bee colony. This is where mathematical models are particularly helpful, as an important scientific tool to better understand complex systems, such as honey bee colonies.
In recent years, substantial progress has been made towards the development of mathematical models for honey bee colonies. A key advantage of this approach is the potential for models to help us answer “what-if” questions. In the above-mentioned experimental study, we might know, for example, that a particular pesticide adversely affects both the homing ability and mortality rate of forager bees. With this information, a model can then help us to better understand whether (and how) this effect on foragers might adversely affect the overall health of the colony in the longer- term.
Of particular importance, these questions can be asked under realistic circumstances, such as insights into the impact of this pesticide on the health of colonies that are already under stress from a range of other factors, such as the presence of Varroa mites (an important biological agent) and certain beekeeping practices.
Simon More is Professor of Veterinary Epidemiology and Risk Analysis at University College Dublin. He is also Chair of EFSA’s MUST-B Working Group.