Friday, August 6, 2010 - 9:00 AM

COS 108-4: Predicting the effects of phenological changes on plant-pollinator interactions

Laura A. Burkle and Tiffany M. Knight. Washington University in St. Louis

Background/Question/Methods

Direct and indirect effects of human actions, including climate change, species invasions, and land-use change, are having profound effects on ecological communities. One of our biggest challenges as ecologists is determining and predicting the individual and combined effects of these environmental forces on species interactions. By re-collecting historic plant-pollinator data from the 1880’s, we have the unique opportunity to disentangle some of these effects. One of the mechanisms by which climate change may alter plant-pollinator interactions is through differential changes in phenologies, leading to interaction mismatches. We used historical data on the phenological distributions (peak and duration) of plant blooming and pollinator activity and on the interaction network to create an individual-based model examining how the flexibility of pollinators in their foraging and how different magnitudes and directions of phenological changes in plants and pollinators affect the interaction network. We compare our model results to real data collected in 2009 and 2010, and evaluate how well this model – which includes potential effects of climate change, but not other forms of anthropogenic disturbance – explains changes in the interaction network.  

Results/Conclusions

Preliminary model results indicate that low flexibility in pollinator diet and/or strong phenological changes that separate plants and pollinators result in loss of network connections. Field results indicate that that pollinator phenology is more sensitive to climate change than is flowering phenology, with early season pollinators responding most strongly. Phenological changes have resulted in interaction mismatches, but the diets of some pollinators appear to be more flexible than previously assumed, allowing for new interactions to be formed when historic ones are no longer possible due to phenological mismatches. Our model, in combination with historic and current data on species interactions, provides a framework for understanding the degree to which phenological changes are altering the structure and function of ecological communities.