@article{just_norton_traud_antonelli_poteate_backus_snyder-beattie_sanders_dunn_2014, title={Global biogeographic regions in a human-dominated world: the case of human diseases}, volume={5}, ISSN={["2150-8925"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84919788790&partnerID=MN8TOARS}, DOI={10.1890/es14-00201.1}, abstractNote={Since the work of Alfred Russel Wallace, biologists have sought to divide the world into biogeographic regions that reflect the history of continents and evolution. These divisions not only guide conservation efforts, but are also the fundamental reference point for understanding the distribution of life. However, the biogeography of human‐associated species—such as pathogens, crops, or even house guests—has been largely ignored or discounted. As pathogens have the potential for direct consequences on the lives of humans, domestic animals, and wildlife it is prudent to examine their potential biogeographic history. Furthermore, if distinct regions exist for human‐associated pathogens, it would provide possible connections between human wellbeing and pathogen distributions, and, more generally, humans and the deep evolutionary history of the natural world. We tested for the presence of biogeographic regions for diseases of humans due to pathogens using country‐level disease composition data and compared the regions for vectored and non‐vectored diseases. We found discrete biogeographic regions for diseases, with a stronger influence of biogeography on vectored than non‐vectored diseases. We also found significant correlations between these biogeographic regions and environmental or socio‐political factors. While some biogeographic regions reflected those already documented for birds or mammals, others reflected colonial history. From the perspective of diseases caused by pathogens, humans have altered but not evaded the influence of ancient biogeography. This work is the necessary first step in examining the biogeographic relationship between humans and their associates.}, number={11}, journal={ECOSPHERE}, author={Just, Michael G. and Norton, Jacob F. and Traud, Amanda L. and Antonelli, Tim and Poteate, Aaron S. and Backus, Gregory A. and Snyder-Beattie, Andrew and Sanders, R. Wyatt and Dunn, Robert R.}, year={2014}, month={Nov} }
 @article{verdolin_traud_dunn_2014, title={Key players and hierarchical organization of prairie dog social networks}, volume={19}, ISSN={["1476-9840"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84903905547&partnerID=MN8TOARS}, DOI={10.1016/j.ecocom.2014.06.003}, abstractNote={The use of social network theory in evaluating animal social groups has gained traction in recent years. Despite the utility of social network analysis in describing attributes of social groups, it remains unclear how comparable this approach is to traditional behavioral observational studies. Using data on Gunnison's prairie dog (Cynomys gunnisoni) social interactions we describe social networks from three populations. We then compare those social networks to groups identified by traditional behavioral approaches and explore whether individuals group together based on similarities. The social groups identified by social network analysis were consistent with those identified by more traditional behavioral approaches. However, fine-grained social sub-structuring was revealed only with social network analysis. We found variation in the patterns of interactions among prairie dog social groups that was largely independent of the behavioral attributes or genetics of the individuals within those groups. We detected that some social groups include disproportionately well-connected individuals acting as hubs or bridges. This study contributes to a growing body of evidence that social networks analysis is a robust and efficient tool for examining social dynamics.}, journal={ECOLOGICAL COMPLEXITY}, author={Verdolin, Jennifer L. and Traud, Amanda L. and Dunn, Robert R.}, year={2014}, month={Sep}, pages={140–147} }
 @article{traud_mucha_porter_2012, title={Social structure of Facebook networks}, volume={391}, number={16}, journal={Physica (Hague, Netherlands). A}, author={Traud, A. L. and Mucha, P. J. and Porter, M. A.}, year={2012}, pages={4165–4180} }