This project is part of a larger workforce lead by the European Food Safety Authority (EFSA) with the goal to uncover the multiple stressors, which are thought to drive recent bee population declines.
The aim of the project is to contribute to the development of the ApisRAM model as a risk assessment tool on the unforeseen effects of pesticide. In conventional agriculture, a number of different pesticides are used to protect crops from pests. Unfortunately, some pesticides have adverse effects on beneficial insects, including bees. All pesticides are extensive testing before they are released for field use, but standard tests only measure mortality of test-bees within 48 hours in a laboratory. These lab tests do not account for the long-term effects (e.g. survival or long-term fecundity), or the effect of other stressors such as hunger or disease, which affect bees in the field. Nutritional stress and disease can negatively impact the immune system of the bees, and hence lower its tolerance to pesticides. Likewise, pesticides can affect the bee immune response and trigger diseases. Long-term experiments and studies involving bee colonies in the field are unfortunately time consuming and expensive. Hence, field tests are neither practically nor economically possible to conduct for all pesticides.
The project is part of the EFSA’s MUST-B (MUltiple STressors in Bees) project. MUST-B aims to develop a holistic approach on the risk assessment on multiple stressors in bees to be formalized through an Opinion of the Scientific Committee. The MUST-B project will culminate in an overarching Scientific Opinion that will bring together and synthesize the findings of the various activities including the development and testing of ApisRAM.
The project will supply the data, which will be used for validating the ApisRAM model. The experiments take place in four Danish agricultural landscapes, two sites in Western Denmark and two sites in Eastern Denmark in 2019 and 2020. At each of the four sites, the population development of five bee colonies was followed closely using advanced technologies, including automatic weight logging, videos of the flight activity, image analysis of combs (in order to quantify brood development and food provision) and decoding of bee dance, which depicts where the bees forage in the landscape.
The results of this project will provide the basis for the development of a more realistic risk assessment of pesticides on bees using computer simulations. Hence, we aim to develop a tool, which can better predict the influence of the negative factors affecting honeybee colonies in the field, and hence to reduce colony loss in the future.
1. EFSA: MUST-B project