A severe drought is expected in the western Rockies in 2018, following the second-lowest snowpack on record the preceding winter. The drought will dramatically alter which species are present in the ecosystems of the Rockies and their relative abundances. The drought thus presents an unusual opportunity to study how pollination networks (the connections between interacting pollinator and plant species) are affected by disturbances. This is important given that extreme environmental events are expected to become increasingly common and that pollination is critically important for the maintenance of both wild plant populations and the productivity and security of many agricultural crops. Specifically, this project is focused on 1) how species in ecosystems can form new connections to other species after disturbances; 2) how new connections can be predicted even following major disturbance; and 3) the implications of new patterns of plant-pollinator relationships for understanding ecosystem-level responses to disturbance. This work will contribute to better understanding of how networks (including other ecological networks, and other network types such as economic, engineered, and social networks) respond to disturbances, particularly in terms of the formation of new connections.
This project will use existing plant-pollinator network field data from non-drought years (2016 and 2017) to build and test mechanism-focused models of network structure, based on plant and pollinator abundances, competition between pollinators for flowers, and data on plant and pollinator physical traits (such as body size). Model predictions will be compared with field data from the severe drought year (2018) in which it is anticipated that there will be a strong reduction in which species are present (for example, many long-lived plant species may not bloom when drought-stressed) as well as substantial changes in relative abundances of flowers and pollinators. In particular, the project will also assess how well this new network model performs relative to existing alternative models (none of which currently perform well in predicting interactions). The researchers will then use models to assess generally how substantial capacity for re-wiring will affect system-level responses to perturbations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
