Abstract
Rangeland livestock provide a great opportunity to capture resilience traits due to the significant amount of the year spent grazing a resource-limited environment where they are exposed to extreme weather, predators, and varied terrain. Capturing the ability of an individual to cope with these stressors has the potential to improve animal welfare and productivity in the face of climate change. These measurements need to occur over the course of time of an animal in such an environment or capture the sum of the ability of the animal to cope with the environment. To do this, measurements of resilience and efficiency will be a useful tool to make continued improvement in rangeland livestock through genetic selection. However, the high-throughput phenotyping typically required to capture resilience traits is challenged by the remote location, limited or no access to power and internet, and limited manpower for data collection. Therefore, such tools need to be self-sustaining, automated, and cost-effective to be able to capture data on a large number of individuals in a rangeland setting. To this end, we have been exploring the use of precision livestock tools to capture sheep performance in a rangeland environment. We are currently working on developing a portable walk-over-weighing system to automatically capture an individual’s weight that uses a combination of solar powered portable batteries and an RFID system with the aim to make a compact weighing system that can easily be transported in rough mountainous terrain. This system can be used to capture longitudinal weights in challenging environments, which can be used to develop indicators of resilience, such as the variability in weight over time or changes in weight due to chronic environmental stressors such as a heat wave. Because it is RFID-based, the data can also be used to take stock inventory to track possible predation events or other stock losses. We are also using low-cost commercial-off-the-shelf GPS units to capture animal behavior in these environments. These data can be used to derive a multitude of traits relating to land-use behavior, including water usage and daily distance traveled. The data can also be used to capture social interactions, such as ewe-lamb relationships. While the information content is high for these datatypes, there are also challenges associated with missing or unreliable data. We are currently exploring methods to combat these challenges to provide robust measurements of performance. Through these data, we aim to develop traits that integrate animal performance and behavior to identify animals that are better suited to a rangeland environment. We expect that breeding of such animals will result in a positive impact on productivity, a reduced impact on the ecosystem, and lower mortality rates, thereby improving the sustainability of livestock production systems.