Spatially enabled livestock management: increasing biomass utilisation in rotational systems

Abstract

Increasing pasture utilisation is one of the primary means of increasing the productivity of livestock systems. The precise control of grazing pressure across a paddock can increase pasture utilisation above 50%, much higher than the current industry average of 30-40% (MLA 2009). In a recent review of new approaches to grazing management, Laca (2009) highlights the importance of understanding the spatial variability of pastures, grazing activity and the potential for information technology and spatial monitoring in livestock systems to inform management decisions and lift pasture use efficiency. Indeed, there are several real-time spatial monitoring systems currently in development for deployment in commercial situations (Stassen 2009). Considerable effort has been put into developing systems that can determine animal behaviour from 'on-animal' motion sensors (Reed and Solie 2007) and recent research has combined motion sensors with spatial information to predict behaviour (Ungar et al. 2005). However, limited research has been undertaken into the potential for spatial data alone to predict the behaviour of livestock (Schwager et al. 2007). This is an important deficiency in the current knowledge as many commercial systems in development are limited to position sensors only and their application in grazing systems will be limited unless further research is undertaken. This project combines GPS tracking with visual observations of animal behaviour in order to determine whether spatial livestock data alone can be used to predict the biomass characteristics (quantity and quality) of the pasture. Moreover we aim to see whether such information can be used to as a trigger to moving stock in rotational systems.