ArcticBuzz: bumblebee community responses to climate change in Lapland

Addressing these types of questions requires us to understand the mechanisms and processes by which insect pollinator populations are dynamically responding as well as how the structure of plant-pollinator networks respond under climatic variation. This project will study an Arctic bumblebee community and the host plants they visit in Lapland, Sweden. As ectotherms, bumblebee life-histories are mediated by temperature and thus by understanding intra- and interannual population and community turnover we can look to inform predictive models under warming scenarios and identify early warning signs of climate change impacts. Furthermore, this project will reveal the spatio-temporal variation (non-static) in the bumblebee-plant visitation network to reveal how resistant and resilient the mutualistic interaction network is to climate change. The project takes advantage of a unique phenology transect established over a century ago allowing us to compare past data on bumblebee/plant community composition and phenology with contemporary data spanning the major warming over the last four decades. The transect runs along an altitudinal gradient on Mount Nuolja, Abisko, providing a thermal cline with the study taking a space-for-time substitution approach. A number of important questions will be addressed by the student, which can include:
i) how preceding and current environmental variables determine population demography and queen turnover;
ii) what phenological variation is apparent across years, and how this relates to population and community-level responses;
iii) how climatic variation determines floral availability and floral acquisition by bumblebees and whether there is evidence of thermal tracking;
iv) how the topology and structure of the mutualistic network responds to climatic variation;
v) how population variability in the traits of individuals of a species aggregate determines network structure ; vi) whether we can predict non-random changes to the mutualistic networks by consideration of data on metabolic, phylogenetic and functional trait variation across species.