Disentangling an entangled bank: using network theory to understand interactions in plant communities

Abstract

Network analysis can map interactions between entities to reveal complex associations between objects, people or even financial decisions. Recently network theory has been applied to ecological networks, including interactions between plants that live in the canopy of other trees (e.g. mistletoes or vines). In this thesis, I explore plant-plant interactions in greater detail and I test for the first time, a predictive approach that maps unique biological traits across species interactions. In chapter two I used a novel predictive approach to investigate the topology of a mistletoe-host network and evaluate leaf trait similarities between Lauranthaceaous mistletoes and host trees. Results showed support for negative co-occurrence patterns, web specialisation and strong links between species pairs. However, the deterministic model showed that the observed network topology could not predict network interactions when they were considered to be unique associations in the community. Network analysis has revealed similarities between mistletoe- and vine-host interactions. In this thesis I investigated the role of chance in structuring these interactions. Results showed that mistletoes and vines use host trees in very different ways even though network topology suggest similarities. In chapter three I show that the dispersion of individual mistletoes (i.e., clumping of mistletoe on certain trees) was not dependent on tree availability; however and perhaps more importantly, I show in chapter five that coincidental associations between vines and trees are sufficient to generate similar network patterns to that found in mistletoes. Each of these studies explored untested hypotheses regarding the architecture of plant-plant interactions. In chapter six I turned to plant-animal interactions to test whether temporal changes influenced network topology. That is, I quantified variability among species interactions and I tested the role of species turnover in structuring a frugivore network spanning six sequential years. Results showed that frugivore interactions (i) changed from year-to-year, (ii) showed inconsistent patterns of nestedness, and (iii) novel interactions occurred even after six years of data collection. In conclusion, a modified approach to the traditional randomisation procedure has allowed me to test explicit factors that determine interactions in plant communities. Network analysis is a useful measure of structure that can depict structural differences among arboreal plant communities in Australian ecosystems.