Project description
The pollination strategy of bees
Understanding the foraging patterns and interactions of bees is important to both ecologists and economists. The EU-funded BEE-MOVE project will apply an interdisciplinary approach, combining pollinator behaviour and plant ecology, to link pollinator movements to pollination efficiency. A new radar system will record and analyse the individual movements of hundreds of bees foraging simultaneously. In addition, radar and robotic plants will be used to study how bees search and exploit food resources over several square kilometres. This information will be applied to computational agent-based models to investigate the influence of bee spatial strategies on pollination efficiency. The results will inform the design of practical interventions for conservation, sustainable agriculture, and green development to help stem pollinator decline.
Objective
How pollinators, such as bees, exploit plaHow pollinators, such as bees, exploit plant resources is a fundamental question in biology, with deep ecological, economical and societal consequences. When foraging on flowers, pollinators transfer pollen and mediate the reproduction of plants on which most animals (including us humans) rely on. Understanding the spatial foraging strategies and interactions of pollinators across the landscape is thus a critical scientific challenge to discover their influence on plant mating patterns and pollination efficiency. BEE-MOVE will use an interdisciplinary approach to mechanistically link pollinator movements to pollination efficiency at field scales, thereby crossing boundaries between research on pollinator behaviour and plant ecology. I will focus on two key pollinators worldwide: the buff-tailed bumblebee and the Western honey bee. 1) I will develop a new radar system to record and analyse the individual 3D movements of hundreds of bees foraging simultaneously. 2) I will use arrays of communicating radars and robotic plants to study how bees search and exploit food resources in field setups of several square kilometres, by manipulating key environmental factors such as the density of bees, the 3D distribution of plants, and the nutritional content of nectars and pollens. 3) From these observations, I will build computational agent-based models to investigate the influence of bee spatial strategies on pollination efficiency. Critical experiments will test model predictions in populations of natural plants. The dialogue between observations and simulations will create a positive feedback towards a robust, multi-level understanding of plant-pollinator interactions at the scale of landscapes. In addition to exploring entirely new grounds in pollination ecology, my results could be used to design practical interventions for conservation, sustainable agriculture and green development in the worrying context of pollinator declines.
Fields of science
- agricultural sciencesagriculture, forestry, and fisheriesagriculturesustainable agriculture
- natural sciencesbiological sciencesecology
- natural sciencesbiological scienceszoologyentomologyapidology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsradio technologyradar
Keywords
Programme(s)
Funding Scheme
ERC-COG - Consolidator GrantHost institution
75794 Paris
France