@article {JRN55342,
	title = {Can cattle geolocation data yield behavior-based criteria to inform precision grazing systems on rangeland?},
	journal = {Livestock Science},
	volume = {255},
	year = {2021},
	month = {12/5/2021},
	pages = {104801},
	abstract = {A key challenge of precision grazing systems is identifying behavior anomalies associated with situations of reduced animal production and wellbeing. We determined typical ranges of diel variation of movement and activity patterns of steers on rangeland to identify metrics that could serve as sensitive indicators of behavior anomalies. Seventeen Raramuri Criollo or Criollo crossbred yearling steers weighing 318 {\textpm} 9.3 kg (winter; W) or 358 {\textpm} 8.4 kg (late summer; LS) were fitted with GPS collars that recorded animal location at 5-min intervals. Steers grazed a 3,215-ha rangeland pasture for approximately 67 d in W or LS of 2016 and 2017. GPS data were used to derive 22 commonly monitored behavior variables. Means and day-to-day variation (CV\%) of all behavior metrics were calculated for each animal as well as linear correlations between the CV of each behavior and ADG. Daily time spent resting or grazing exhibited the least day-to-day variation in both W and LS (CV resting =10.8 and 9.9\%, respectively; CV grazing =13.8 and 14.8\%, respectively); predawn area explored (CV =240.8\%) and time spent at drinkers (CV =336.6\%) exhibited the most daily variation in W and LS, respectively. During W, increasing day-to-day variation in daytime distance traveled and area explored, as well as daily time spent traveling were associated with increasing ADG (r = 0.56 to 0.58; P < 0.05). In LS, steers with greater CV for 24-h area explored, time spent traveling, or daytime distance traveled tended to gain less weight (r =-0.77 to -0.84; P < 0.01), while steers with more flexible 24 hour path sinuosity tended to gain more weight (r = 0.93; P < 0.01). Behavior metrics more closely associated with forage intake processes, such as daily time spent grazing or resting, exhibited lowest diel variation levels and could be used to diagnose non-normal behavior of cattle on rangeland.},
	keywords = {Average daily weight gain, beef cattle, GPS monitoring, Precision grazing, Precision livestock ranching},
	doi = {10.1016/j.livsci.2021.104801},
	url = {files/bibliography/21-053.pdf},
	author = {Matthew M. McIntosh and Andr{\'e}s F. Cibils and Richard E. Estell and Qixu Gong and Huiping Cao and Amy L. Gonzalez and S. Nyamuryekung{\textquoteright}e and S. Spiegal}
}
