University of Exeter

There is great scientific and policy concern about threats to pollination, with the Parties to the Convention on Biological Diversity endorsing a report in 2016 that assessed pollination threats, trends and conservation. Pollination is important for many crops and fundamental to most ecosystems. In its absence, crop yields could decline and wild plants may be unable to reproduce, which could lead to cascading declines in dependent animal populations. At the same time, growth in international trade and transportation means that species are increasingly being transported outside their native ranges. Consequently, the ecological threat of invasive species is growing. The threat invasive species pose to pollination, however, is poorly understood.

This knowledge gap largely results from methodological shortcomings that prevent the impacts of invasive species from being detected. Ecologists study plant-pollinator communities as networks: that is, nodes, representing species, connected by links, representing pollination interactions. To date, these networks have been characterised by indices that summarise some aspect of network structure in a single number. My research has shown that this approach discards approximately 90% of the information about the network, making it highly insensitive to changes caused by invasive species. In this project, I will move beyond describing networks with simple indices and instead use ‘bipartite motifs’, a cutting-edge analytical technique that captures up to 1000% more information about network structure than traditional indices.

Motifs can be thought of as the ‘building blocks’ of networks; they capture network structure in incredible detail, from small local patterns to whole-network architectures. By harnessing the analytical strength of motifs to explore

(i) a unique dataset on invaded plant-pollinator communities over decadal timescales and

(ii) a global dataset of invaded plant-pollinator networks, I aim to uncover general rules about how invasive species integrate into plant-pollinator communities and how invasive species transform the networks they join.

These results will then allow me to predict the effects of invasion on the robustness of the pollination service around the world. My project will produce critical recommendations for invasive species management and therefore will be of great interest to ecologists, conservationists, practitioners and policymakers.