Foraging distances of pollinators have been extensively studied and have important implications for the spatial assessment of pollination services of important crops such as coffee, as well as for biodiversity conservation strategies. However, the main challenge is that foraging behaviors are context-dependent, resulting from the interactions between species characteristics and their environment. In particular, no general relationship exists between landscape structure and foraging distance. As a results, a fine scale understanding on how pollinators utilize space and resources in complex landscapes would lead to a more effective management of the pollination service.

In the coffee production region in the Western Ghats in South India, one of the main pollinators is the giant honeybee Apis dorsata. Despite an abundance of floral resources, a deficit of pollinators has been documented in coffee plantations. Our objective is to estimate the foraging range of Apis dorsata during coffee blossom. We are specifically interested in the occurrence of long flight events when the nests are isolated, since long flying bees may function as important pollinators in fragmented landscape.

One of the more recent and promising methods for direct estimates of foraging distance involves the use of genetic markers. The method is based on comparing the degree of relatedness between individual bees in the nests and worker bees foraging in the landscape. In 2015, we collected samples of Apis dorsata from isolated nests, as well as workers at different locations in the landscape. This work needs to be complemented with further sampling during the forthcoming coffee blossom season.
In this project, you will estimate the distances travelled by foraging workers, using genotyping methods and shibship reconstruction models. The project includes two months of field work in India in the Kodagu district for sampling bees (February – March 2016), laboratory work in India (for DNA extraction, one week) and in Zurich (for genotyping and visualization of DNA sequences, two months) and analysis of genetic data with dedicated software (genetic fullsib reconstruction (FSR) method, two months).

We are looking for an enthusiastic student, with sufficient background in population genetics. Laboratory experience would be an asset. The position would begin in late January or early February 2016. All field expenses would be covered.
Interested students may send a short CV and a letter of motivation in French or English to Charlotte Pavageau, PhD student in the Ecosystem Management group, Institute of Terrestrial Ecosystems: [email protected]
Supervision: Prof. Jaboury Ghazoul [email protected]

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