Abstract
Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system(RTLS) to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density), subgroup clustering (modularity), triadic property (transitivity), and dyadic interactions (correlation coefficient from a quadratic assignment procedure) at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level) or temporal (aggregated at daily level) resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc.) also changed substantially at different time and locations. There were certain time (feeding) and location (hay) that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect) disease transmission pathways.
Original language | English |
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Article number | e0129253 |
Journal | PLoS ONE |
Volume | 10 |
Issue number | 6 |
DOIs | |
State | Published - 24 Jun 2015 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2015 Chen et al.
Funding
We thank the comments and suggestions from Dr. Louis Gross, National Institute for Biological and Mathematical Synthesis (NIMBioS), for improvements of this manuscript. This work was conducted with partial funding provided at NIMBioS, an institute sponsored by the U.S. National Science Foundation, the U.S. Department of Homeland Security, and the U.S. Department of Agriculture through NSF Award # EF-0832858, with additional support from the University of Tennessee, Knoxville.
Funders | Funder number |
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U.S. Department of Agriculture | |
U.S. Department of Homeland Security | |
National Science Foundation | EF-0832858 |
Directorate for Biological Sciences | 0832858 |
U.S. Department of Homeland Security | |
U.S. Department of Agriculture | |
University of Tennessee | |
National Institute for Mathematical and Biological Synthesis |