Supporting data: Spatial network clustering reveals elk population structure and local variation in prevalence of chronic wasting disease at Wind Cave National Park, 2005--18
November 12, 2021
These data were used for preparation of Sargeant et al. (2021), "Spatial network clustering reveals elk population structure and local variation in the prevalence of chronic wasting disease." They include locations of elk that were monitored with global positioning system collars at Wind Cave National Park, South Dakota (WICA) during 2005--08 and 2011--13; coordinates of a polygon describing the boundary of WICA; and results of tests for chronic wasting disease for elk culled at WICA during 2016--18.
Citation Information
| Publication Year | 2021 |
|---|---|
| Title | Supporting data: Spatial network clustering reveals elk population structure and local variation in prevalence of chronic wasting disease at Wind Cave National Park, 2005--18 |
| DOI | 10.5066/P9VPV6FO |
| Authors | Glen A Sargeant |
| Product Type | Data Release |
| Record Source | USGS Asset Identifier Service (AIS) |
| USGS Organization | Northern Prairie Wildlife Research Center |
| Rights | This work is marked with CC0 1.0 Universal |
Related
Spatial network clustering reveals elk population structure and local variation in prevalence of chronic wasting disease
Spatial organization plays prominent roles in disease transmission, genetics, and demography of wildlife populations and is therefore an important consideration not only for wildlife management, but also for inference about populations and processes. We used hierarchical agglomerative clustering of a spatial graph network to partition Wind Cave National Park (WICA) into five regions used by 163 fe
Authors
Glen A. Sargeant, Margaret A. Wild, Gregory M. Schroeder, Jenny G. Powers, Nathan L. Galloway
Related
Spatial network clustering reveals elk population structure and local variation in prevalence of chronic wasting disease
Spatial organization plays prominent roles in disease transmission, genetics, and demography of wildlife populations and is therefore an important consideration not only for wildlife management, but also for inference about populations and processes. We used hierarchical agglomerative clustering of a spatial graph network to partition Wind Cave National Park (WICA) into five regions used by 163 fe
Authors
Glen A. Sargeant, Margaret A. Wild, Gregory M. Schroeder, Jenny G. Powers, Nathan L. Galloway