Emerging Near-Real Time Forage Monitoring Technology with Application to Large Herbivore Management in Mongolia

Large herbivore livestock and wildlife in Mongolia depend almost entirely for substance on forage standing crop produced each year on natural pastureland. Consequently, both livestock and wildlife are continuously subject to environmental risk, especially drought and severe winter storms, while livestock are also subject to financial risk. As consumption-based livestock production changes to commercialized livestock production, steps taken by the livestock herder to avert both environmental and financial risk to livestock can increase environmental risk to large wild herbivores. A realistic and workable pastureland and risk management system will be critical for conservation of large herbivore habitat. New technologies are becoming available to facilitate understanding of risk and resource allocation. Texas A&M University has developed a suite of innovative technologies that facilitate resolving risk and resource allocation issues. A pre-parameterized rangeland model (i.e., PHYGROW) provides daily estimates of forage available to a mixed population of herbivores. Near Infra-Red Spectroscopy (NIRS) allows prediction of diet quality of free-ranging large herbivores via fecal scans which, when coupled with advanced nutritional management software (i.e., NUTBAL), can predict performance of animals. Oregon State University has developed a computerized multi-criteria decision-making tool (i.e., KRESS) that can take landscape parameters and determine the suitability of each cell or unit of the landscape for use by large herbivores. Emerging near real-time technologies can help clarify habitat needs, identify habitat improvements, and enable better management of large herbivore wildlife and livestock