Pollination: using the past and present to predict the future

Globally, nearly 90% of wild flowering plants and 35% of crop volume depend on animals for pollination. Pollinators are falling out of sync with their floral resources as each respond to slightly different cues, risking both biodiversity and food security. Given the intertwined threats of climate change and global biodiversity loss, to mitigate this, we need to understand how communities of plants and pollinators have changed in response to past perturbations, how they function in the present, and use this information to predict how they will function in the future. Effects cascade across habitats and among diverse species groups, and shift through time and in response to perturbations. Thus, to advance beyond a descriptive understanding of how communities have responded to change, and provide predictive models to inform restoration efforts, we need to investigate interactions across space and time. Working with museum curators, conservation practitioners and the general public, this project would investigate plant-pollinator interactions in the past using museum specimens that contain pollen from the day they were collected; in the present, creating empirically derived quantitative plant-pollinator interaction networks; and develop models to predict into the future and inform where restoration efforts now can protect against floral resource gaps in the future. Ultimately, gardens and urban green spaces will be central to maintaining resource provision, so engaging with the public now to protect pollination services in the future will be key to future-proofing long-term plant-pollinator communities.

1. What did plant-pollinator networks look like in the past? Using the extensive Smithsonian collections at the Natural History Museum in London we can determine historical pollinator activity timing and, by non-destructive DNA metabarcoding the pollen on the specimen or in the preserving ethanol, what flowers they visited on the day of collection. Herbarium specimens collected while in flower from the same locations will reveal historical flowering times and, through sequencing insect DNA on flowers, discover additional plant-insect association. This will inform historical plant-pollinator networks and past phenology.
2. What do modern day plant-pollinator networks look like? We will return to sites with good museum specimen coverage and re-sample modern day plants and pollinators to determine the structure of the communities now. Sampling across habitats will give a more accurate picture of how communities depend on floral resources at the landscape scale.
3. How have floral resources and pollinator interactions changed over time and how will they change into the future? Using the networks from 1. & 2., we will determine how the plant flowering times, pollinator activity times and plant-pollinator community structure have changed over time. This combined with climate predictions, predicted plant flowering time shifts and expected species’ responses to climate change will allow us to use adaptive network modelling to predict into the future and determine where there are likely to be plant-pollinator mismatches and limited floral resources.
4. Experimentally test the predictions of response to species loss and phenological mismatch modelling. In a UK system (Cairngorms),we will validate the predicted phenological response by encouraging plants to flower early in a heated greenhouse south of their natural range and then place them in the field before their natural equivalents would be available. Monitoring the pollinator visitations to both early flowering and naturally flowering plant communities will highlight future plant-pollinator temporal mismatches.
5. Inform action. Engaging with conservation practitioners, the general public and policy makers to protect and restore areas now will ensure that they will provide necessary floral resources in the future.

This project will involve field work, lab work and computer modelling as well as engaging with people and collaborators with a wide range of backgrounds.