SYMP 2-1 - Merging ecological networks across interaction types: Challenges and opportunities

Monday, August 7, 2017: 1:30 PM
Portland Blrm 252, Oregon Convention Center
Sonia Kéfi, Institut des Sciences de l'Evolution de Montpellier, CNRS, Montpellier cedex 05, France
Background/Question/Methods

In natural communities, species interact with each other in different ways, including predation, competition, and facilitation. This complex spectrum of interactions constitutes a network of links that mediates ecological communities’ response to perturbations, such as exploitation and climate change. In the last decades, there have been great advances in the study of intricate ecological networks. We have, nonetheless, lacked both the data and the tools to more rigorously understand the patterning of multiple interaction types between species, as well as their consequences for community dynamics. Improving our understanding of the dynamics and resilience of complex ecological systems may rely on how the joint effects of different interactions types explain variations not explained by feeding interactions alone.

Results/Conclusions

Data and models of ecological networks including different interaction types simultaneously are recently starting to become available, and some of the results challenge the idea that a full understanding of the dynamics and stability of ecological communities can be achieved by knowledge of trophic interactions alone. For example, theoretical studies suggest that the incorporation of non-trophic interactions in food webs can have important consequences for species diversity, overall productivity, frequency of functional extinctions, stability, and the complexity–stability relationship.

In this talk, I’ll present recent efforts in analyzing and understanding ecological networks including different types of species interactions. I will argue that moving beyond unidimensional analyses of ecological networks may contribute to improving our understanding and predictive capacity of the way ecological systems respond to disturbances.