Do Movement Patterns of GPS-Tracked Cattle on Extensive Rangelands Suggest Independence among Individuals?

Abstract

Abstract:In behavioral studies, cattle within the same pasture are not considered as independent experimental units because of the potential confounding effects of the herd's social interactions. However, evaluating cattle behavior on extensive rangelands is logistically challenging for researchers, and treating individual animals as independent experimental units may be beneficial for answering specific research questions. The objective of this study was to evaluate the association patterns among global positioning system (GPS)-tracked cattle at six different study sites in the western United States. A Half-Weight Index (HWI) association value was calculated for each pair of GPS-tracked cows (i.e., dyad) to determine the proportion of time that cattle were within 75 m and 500 m of each other. Cattle at two study sites exhibited relatively low mean HWI-association values (i.e., less than 0.23 HWI); whereas, cattle at other study sites tended to have greater mean HWI associations (i.e., greater than 0.35 HWI). Distinguishing features between study sites with low and high association values were the management of cattle prior to the study, herd size, pasture size, and the number of watering points. However, at all ranches except one, at least 75% of all dyadic associations had HWI values of less than 0.5 at 500 m, indicating that most of the GPS-tracked cows were greater than 500 m from each other for over 50% of tracking period. While interactions among cattle in the same pasture are often inevitable, our data suggests that under some situations, movement patterns of a sub-set of individual GPS-tracked cows may have levels of independence that are sufficient for analysis as individual experimental units. Understanding the level of independence among GPS-tracked cattle may provide options for analysis of grazing behavior for individual cattle within the same pasture.

Association patterns reveal dispersal-aggregation dynamics among cattle in a South Texas Rangeland, USA

“…These hypotheses will require further research that integrates animal location, physiological information at the individual level, and environmental variables to develop herd emergent properties (Swain and Friend 2013). Furthermore, breed and herd and pasture size can greatly affect the spacing behavior and social association patterns in cattle herds (Bøe and Faerevik 2003;Stephenson et al 2016;Stephenson and Bailey 2017). Our findings show the importance of studying herds at multiple scales to better detect spatial and temporal patterns.…”

“…Previous studies have addressed questions regarding the relationship between spatial interactions and social dominance in a cattle herd (Stricklin 1983;Grant and Albright 2001;Šárová et al 2010;Stephenson et al 2016) as well as independence among individuals (Stephenson and Bailey 2017) in herds of various sizes. Stephenson et al (2016) reported that in herds of 40 or less cows no strong or weak association pattern was detected using visual observations suggesting that these animals had equal association with all other cows in the pasture.…”

“…However, there is a need to determine if current tracking technology such as global positioning systems (GPS) and association analysis tools such as ASSOC1 can detect more subtle dispersal-aggregation dynamics in a small cattle herd and whether any effects of social dominance can be observed. The use of GPS collars to track animal movements during 24 h day cycles and longer time frames (e.g., year-round, seasonal), and the development of validated animal association tools has improved our understanding of livestock behavior and distribution dynamics (Weber et al 2001;Stephenson and Bailey 2017). The aim of this work was to examine the seasonal dispersal-aggregation patterns in a small cattle herd in a South Texas Rangeland using GPS technology and the spatial association software ASSOC1 (Weber et al 2001).…”

Lameness Detection as a Service: Application of Machine Learning to an Internet of Cattle

“…This is one of the features of a normal distribution and therefore it would not matter whether the mean or median is used. Authors [19] Fig. 4.…”

SmartHerd management: A microservices‐based fog computing–assisted IoT platform towards data‐driven smart dairy farming

“…Although behavioral studies indicate that cattle in the same pasture are not considered independent experimental units because of the potential confounding effects of the herd's social interactions, 66 the same authors concluded that under some situations such as larger herds (of around 53-240 cows), movement patterns of subsets of individual cows may have a level of independence that is sufficient for analysis as individual experimental units. Therefore, there can be no one-size-fits-all solution for determining the behavior of an individual cow, considering the difference in the behavior of subsets within the same herd.…”