With limited conservation resources, it is becoming much more important to target conservation efforts on the locations and features that provide the greatest impact on a species or group of species. One underused method to do so is applying the mathematical framework of social network analysis (SNA) to generate networks of interaction between a species and its habitats. To test the applicability of this method, I used SNA to generate an interactive network of chimney swift (Chaetura pelagica) roost sites. Using SNA and a Wilcoxon-Pratt signed-rank test, I quantified the importance of each roost site to the structure and stability of the network. I also tested for the influence of weather variables on the structure of the roost network using logistic regression. My results identified a large-scale roost network throughout southern Nova Scotia, with three roosts that had significant influence over the connectivity of the network. I also identified atmospheric pressure as having influence over degree and closeness centrality, two measures of the connectivity of the roost network, and wind speed over closeness centrality. These results show that SNA is a valuable tool that can identify key sites for targeted conservation efforts. I also show that changing weather patterns could result in modifications of the roost network as movement between roost sites is influenced by pressure and wind speed.
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