PS 50-35 - Network structure is linked to the community stability of canopy arthropods associated with Populus angustifolia

Wednesday, August 4, 2010
Exhibit Hall A, David L Lawrence Convention Center
Matthew K. Lau1, Arthur R. Keith1 and Thomas G. Whitham2, (1)Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, (2)Department of Biological Sciences and Merriam Powell Center for Environmental Research, Northern Arizona University, Flagstaff, AZ
Background/Question/Methods   Interspecific interactions have long been considered important to community stability. However, interspecific interactions remain difficult to quantify despite an abundance of community data. Here we take a network perspective to analyze community data from a multi-year study of canopy arthropods associated with Populus angustifolia, a foundation, riparian tree species. We then relate the network structure to the community stability, measured as similarity over time. Arthropod abundance data was observed on individual trees of known genotype in a common garden setting, controlling for the effects of environment and tree genetics. Species interactions were quantified as species correlations using an equivalence testing approach, which adjusted for power issues with multiple pairwise comparisons.

Results/Conclusions   Three major findings emerged. 1) Genotypes varied in network structure in all years sampled. 2) Network structure was consistent across all years. 3) There was a significant, positive correlation between community stability and network structure. Studies of species interaction networks, such as food-webs and mutualisms, have provided the foundations of a network perspective in ecology. Our results suggest that the genetics of a foundation tree species can affect the interaction network structure of associated species and that communities with higher network centrality (i.e., a more even distribution of links among species) are less stabile. Furthermore, our findings indicate the importance of network analytical methods in understanding community dynamics.

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