Tuesday, August 4, 2009 - 8:20 AM

SYMP 6-1: The dynamics of a butterfly-plant pollination network

Jens Olesen, University of Aarhus

Background/Question/Methods

Based on studies of pollination networks all over the world, research has made strong generalizations about the structure of pollination networks. We know how they vary in structure with size and under different environmental settings and methodologies. By far most constructed networks are static and based on pooling of observational data over researcher-defined space and timespan. However, a few, newer studies describe the change in structural properties during a single season or a few years. The consensus from these studies is that properties in general are stable but that a lot of internal dynamics takes place with respect to both species and links. Here, we make an extension to these studies by studying the temporal dynamics of a pollination network over a longer timespan. At four sites separated by 10-50 km in Northeastern Spain, we have in an ongoing study since 1996 made weekly census of flower–visitation links between all flowering plants and their flower–visiting butterflies. The overall goal of this study is to monitor the impact of climate change on “a piece of biological complexity”. This time series allows us to track the long-term behaviour of both species and their links.  

Results/Conclusions

We show that overall network structure, but also several characteristics of species with respect to their topological position and taxonomy are robust over this timespan. However, interesting exceptions are found. We also discovered that species going extinct or invading the habitats follow specific topological trajectories In addition, we find both synchrony and asynchrony between populations with respect to these variables. These findings make it possible for us to relate space and time and make some ergodic generalizations. Our ongoing study and growing database about the structure and dynamics of an ecological network offers a unique opportunity to track how external factors influence an ecological network.