Behavioral Ecology and Sociobiology

, Volume 64, Issue 7, pp 1199–1208 | Cite as

Using home range estimates to construct social networks for species with indirect behavioral interactions

  • Vincent A. FormicaEmail author
  • Malcolm E. Augat
  • Mollie E. Barnard
  • R. Eileen Butterfield
  • Corlett W. Wood
  • Edmund D. BrodieIII


Social network analysis has become a vital tool for studying patterns of individual interactions that influence a variety of processes in behavior, ecology, and evolution. Taxa in which interactions are indirect or whose social behaviors are difficult to observe directly are being excluded from this rapidly expanding field. Here, we introduce a method that uses a probabilistic and spatially implicit technique for delineating social interactions. Kernel density estimators (KDE) are nonparametric techniques that are often used in home range analyses and allow researchers studying social networks to generate interaction matrices based on shared space use. We explored the use of KDE analysis and the effects of altering KDE input parameters on social network metrics using data from a natural population of the spatially persistent forked fungus beetle, Bolitotherus cornutus.


Social networks Kernel density estimation Home range Bolitotherus cornutus Indirect behavioral interactions 



We would like to thank Mountain Lake Biological Station faculty and staff, especially M. Larsen, for logistical support throughout the field season. We would also like to thank A. Wilkinson, J. McGlothlin, E. Liebgold, L. Avila, M. Formica, P. Fields, J. Krause, and two anonymous reviewers for helpful discussions on earlier versions of this manuscript. Many field assistants, graduate students, and REU students at MLBS assisted in the nocturnal data collection, and we are very grateful for their help. We are especially indebted to D.L. Gaggia for his tireless assistance in the field. A. Snedden and Wet-A-Hook technologies provided materials and advice for beetle labeling. Funding was provided by the University of Virginia, Mountain Lake Biological Station, the Norman A. Meinkoth Field Biology Award from the Department of Biology at Swarthmore College, Swarthmore College chapter of Sigma Xi, the Howard Hughes Medical Institute grant to Swarthmore College Biology Department, and the National Science Foundation REU grant to MLBS (DBI-0453380).


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Vincent A. Formica
    • 1
    • 2
    Email author
  • Malcolm E. Augat
    • 2
  • Mollie E. Barnard
    • 2
  • R. Eileen Butterfield
    • 3
  • Corlett W. Wood
    • 1
    • 2
  • Edmund D. BrodieIII
    • 1
  1. 1.Mountain Lake Biological Station, Department of BiologyUniversity of VirginiaCharlottesvilleUSA
  2. 2.Department of BiologySwarthmore CollegeSwarthmoreUSA
  3. 3.School of Biological SciencesUniversity of Texas at AustinAustinUSA

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