An integrated model for predicting bumblebee population success and pollination services in agro-ecosystems

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It is now widely recognized that both wild and managed pollinators provide a vital ecosystem service, essential for the maintenance of biodiversity in natural and semi-natural ecosystems, and necessary for crop production in ~75% of the world's crop species. Recent estimates suggest that crop pollination in the UK is worth £440 million. The main crop pollinators in the UK and throughout the temperate northern hemisphere are honeybees and bumblebees; honeybee populations are threatened by health issues, while many bumblebee species have undergone range declines, probably primarily due to habitat loss. There is thus an urgent need to develop farm management strategies which sustain both healthy populations of pollinators and crop yields. For bumblebees, we lack a detailed understanding of the relationships between the growth and survival of bumblebee nests, the spatial and temporal distribution of the floral resources on which they depend, and the spatial distribution of pollination services they provide. We cannot predict how many bumblebee nests a landscape can support, or how many crop plants they can pollinate. We do not know how many flowers are needed to support a single healthy nest, or how important predators and parasites are in removing bees and whole nests. This project proposes to use a systems approach to answer these questions, combining simulation models with a range of field and genetic studies to provide a new insight into factors governing bumblebee populations in agroecosystems. We will quantify the spatial and temporal distribution of pollen (protein) and nectar (sugar) provided by flowers in 10 representative landscapes (5 in England, 5 in Scotland) using GIS-based maps. In lab studies we will quantify the resources (protein and sugar) needed for healthy growth of a nest. Using novel camera systems developed by the applicants we will monitor wild bumblebee nests to establish rates of predation of nests and of individual bees. These data will feed in to models which will be developed to simulate the growth of realistic numbers of bumblebee nests seeded into our ten landscapes, with models also simulating the foraging of individual workers (agents) from each nest, estimating which food patches they are likely to exploit. Colonies will interact in the landscape through exploitation of resources, and be subject to realistic rates of predation and parasitism. The model will be validated by measuring actual colony growth rates of experimental nests placed into these landscapes, and by measuring the number of nests of different bumblebee species exploiting particular patches of forage within these landscapes (quantified using genetic techniques to identify sisters). Once validated, the models will then be used to predict the spatial distribution of crop pollination services for field beans, and these predictions tested by field measurements of bee visitation rates. The models will also be used to simulate the consequences of adding floral resources to the landscape in terms of pollen and nectar strips, enabling us to quantify how many extra bee nests, and how much extra crop pollination, can be supported. The project will build on and contrast with honeybee models currently being developed in a BBSRC-funded project at Rothamsted. Overall this project will, for the first time, provide us with mechanistic links and quantitative, validated predictions linking bumblebee populations, wildflowers, bee predators and crop pollination.