DOI: 10.5061/dryad.37pvmcvrp
title: Chronic wasting disease alters the movement behavior and habitat use of mule deer during clinical stages of infection

description: Integrating host movement and pathogen data is a central issue in wildlife
 disease ecology that will allow for a better understanding of disease
 transmission. We examined how adult female mule deer (Odocoileus hemionus)
 responded behaviorally to infection with chronic wasting disease (CWD). We
 compared movement and habitat use of CWD-infected deer (n = 18) to those
 that succumbed to starvation (and were CWD-negative by ELISA and IHC; n =
 8) and others in which CWD was not detected (n = 111, including animals
 that survived the duration of the study) using GPS collar data from two
 distinct populations collared in central Wyoming, USA during 2018–2022.
 CWD and predation were the leading causes of mortality during our study
 (32 of 91 deaths attributed to CWD and 27 of 91 deaths attributed to
 predation). Deer infected with CWD moved slower and used lower elevation
 areas closer to rivers in the months preceding death compared with
 uninfected deer that did not succumb to starvation. Although CWD-infected
 deer and those that died of starvation moved at similar speeds during the
 final months of life, CWD-infected deer used areas closer to streams with
 less herbaceous biomass than deer that died of starvation. These
 behavioral differences may allow for the development of predictive models
 of disease status from movement data, which will be useful to supplement
 field and laboratory diagnostics or when mortalities cannot be quickly
 retrieved to assess cause-specific mortality. Furthermore, identifying
 individuals that are sick before predation events could help to assess the
 extent to which disease mortality is compensatory with predation. Finally,
 infected animals began to slow down around four months prior to death from
 CWD. Our approach for detecting the timing of infection-induced shifts in
 movement behavior may be useful in application to other disease systems to
 better understand the response of wildlife to infectious disease.
description: # Chronic wasting disease alters the movement behavior and habitat use of
 mule deer during clinical stages of infection ## GENERAL INFORMATION Title
 of Dataset: CWD-HostBehavior-EcolEvol Author Information A. Principal
 Investigator Contact Information Name: Gabriel Barrile Institution:
 University of Wyoming Address: 1000 E University Ave, Laramie, WY 82071
 Email: [gbarrile15@gmail.com](mailto:gbarrile15@gmail.com) B. Associate or
 Co-investigator Contact Information Name: Jerod Merkle Institution:
 University of Wyoming Address: 1000 E University Ave, Laramie, WY 82071
 Email: [jmerkle@uwyo.edu](mailto:jmerkle@uwyo.edu) C. Alternate Contact
 Information Name: Gabriel Barrile Email:
 [gbarrile@uwyo.edu](mailto:gbarrile@uwyo.edu) Date of data collection:
 December 2018 - October 2022 Geographic location of data collection:
 Central Wyoming, USA. Data were collected on mule deer in the Bates
 Hole/Hat Six herd south of Casper, Wyoming and the Upper Powder River herd
 south of Buffalo, Wyoming. Funding sources that supported the collection
 of the data: Clear Creek Foundation, Knobloch Family Foundation,
 University of Wyoming School of Computing, the Institutional Development
 Award (IDeA) from the National Institute of General Medical Sciences of
 the National Institutes of Health (2P20GM103432), the Buffalo BLM Field
 Office, Wyoming Sportsmen’s Group, US Geological Survey NOROCK, Bow
 Hunters of Wyoming, Wyoming Governor’s Big Game License Coalition, and
 Wyoming Game and Fish Department’s Mule Deer Initiative ## SHARING/ACCESS
 INFORMATION Recommended citation for this dataset: Barrile, G. M., Cross,
 P. C., Stewart, C., Malmberg, J., Jakopak, R. P., Binfet, J., Monteith, K.
 L., Werner, B., Jennings-Gaines, J., and Merkle, J. A. (2023). Data from:
 Chronic wasting disease alters the movement behavior and habitat use of
 mule deer during clinical stages of infection. Dryad Digital Repository.
 ## METHODOLOGICAL INFORMATION Description of methods used for
 collection/generation of data: Captured mule deer were fit with GPS
 store-on-board collars, which obtained a fix every hour for deer in Bates
 Hole and every two hours for deer in Upper Powder River. We collated GPS
 data for adult (&gt; 1.5 year old) females collared during 2021–2022 in
 Bates Hole (n = 64) and 2018–2021 in Upper Powder River (n = 115). GPS
 units were equipped with a mortality signal that activated after 10 hours
 of inactivity. Methods for determining cause of death (including from CWD
 and emaciation) are described in great detail in the manuscript. We
 calculated movement speed, turning angle, and displacement between
 consecutive relocations for each deer. To reduce spatiotemporal
 autocorrelation among telemetry locations, we summarized movement
 parameters as daily metrics (i.e., one value per day for each deer). We
 also intersected GPS relocations with land cover, topographic,
 hydrographic, and anthropogenic variables relevant to mule deer ecology.
 All environmental variables were derived from remotely sensed geospatial
 data layers at 30-m resolution. Methods for processing the data: Data are
 in the format described above. Data are GPS locations from collared mule
 deer (adult females) and their associated movement and habitat metrics.
 The exact coordinates of GPS fixes constitute sensitive information and
 were not needed to conduct analyses. GPS coordinates were thus removed
 from the dataset. Instrument- or software-specific information needed to
 interpret the data: We used Program R to format and analyze data. All R
 packages and functions needed to interpret the data are cited in the
 manuscript. ## DATA-SPECIFIC INFORMATION: Number of variables: 13 Number
 of cases/rows: 88,032 (including the top row of column names) **Variable
 Information:** id = the identification number for each individual mule
 deer. This column is used to uniquely identify each individual animal.
 date = the date/time of the GPS fix in the format year-month-day
 hour:minute:second. For example, 2018-12-16 21:00:07 is December 16, 2018
 in the seventh second of the first minute of hour 21 (9:00 PM). group =
 grouping variable for analysis. Animals were grouped into "cwd",
 "emaciated", and "negative_control" for analysis.
 Please see main text for details. population = whether a deer was in the
 Upper Powder River population (UPR) or the Bates Hole population (BH).
 speed = mean speed between successive relocation in meters per second
 dist2stream = distance to the nearest stream in meters dist2road =
 distance to the nearest road in meters Cover_Trees = percent tree cover
 Cover_Trees = percent shrub cover tri = terrain ruggedness index; higher
 values signify greater topographic heterogeneity elevation = elevation in
 meters herb_biomass = biomass of grasses and forbs in kilograms per
 hectare radangle = relative turning angle in radians *There should be no
 "NA" in the dataset