Perhaps the greatest limitation to sustaining livestock production on our State’s grazinglands is timely decision making by livestock owners concerning destocking and restocking of livestock. Conservation stewardship and resulting improvement in land’s productivity and ecological status can be much more effective if land holders have access to information that warns of impending forage shortages and provides guidance for potential crisis mitigation actions they can take to reduce risk from weather extremes.

Recent breakthroughs in computer modeling technology, weather monitoring data distribution, climate trend modeling, and assessment of animal nutritional status have created a technological environment conducive to assessing the impact of emerging weather events on forage supply for livestock and wildlife and their ability to acquire nutrients to sustain themselves. When coupled with pervasive communication infrastructures, we are poised to offer the livestock industry and the people of Texas an advanced monitoring system capable of providing early warning of emerging conditions that can be predicted well in advance of human perception of detrimental environmental effects on forage supply for livestock and wildlife.

To establish this component of the Statewide program, a monitoring framework will have to be established and foundation vegetation and livestock information packaged in a manner for complex computer models to access the information and in-coming near real-time weather data to project emerging forage conditions. Arrangements will be made with NOAA to acquire 4 x 4 km (2.6 x 2.6 mile) rainfall estimates from NEXRAD radar data and reporting weather stations throughout Texas. These weather sources provides maximum/minimum temperature and rainfall while weather generators estimate solar radiation. Each county will have representative points (9 -12) selected to match the variation in soil associations derived from the USDA-NRCS-STATSGO soils database with a "master drought observer" participating from a near by ranch. One of these ranches will actively pick up fecal samples from livestock to allow monthly analysis of livestock nutritional well being and predicted performance. The soils database provides spatially explicit information on acreage (composition) and physical properties that are critical in models of forage production. The soils are further aggregated into ecological sites and a modal soil assigned to the ecological site called a range site or pasture suitability group.

To represent forage supply conditions, a series of expert derived modal plant communities will be assigned to the range sites. The PHYGROW model is used to "grow and consume" complex plant communities with plants competing for resources under grazed conditions that are controlled by stock/destock rules. One of the first major tasks will require human resources to upgrade our current vegetation maps of the State. We are not proposing to conduct detailed vegetation maps. Instead we will use a protocol to assign "virtual landscapes" to each STATSGO monitoring point in each county. A virtual landscape is a bounded landform (STATSGO polygon) in which we assign a composition of modal plant communities on grazinglands. For each STATSGO polygon, a vegetation survey team comprised of a combination of TAEX specialists and agents, TAES scientists, other University scientists and cooperating USDA-NRCS personnel will develop the modal plant community and the peak canopy expression (percent cover) of the primary species comprising the plant community. They will also assign the modal soil type to the community. Recent experience by TAES scientists in setting up a large-scale monitoring system in East Africa has emerged several robust, rapid appraisal methods to geo-reference virtual landscapes that will be used in this project as well.

An adequate historical record of weather near the NEXRAD monitoring points will allow long-term runs of forage production (~ 25 years) for each unique combination of weather point, modal soil, modal plant community and modal livestock/wildlife population density. This will create a baseline or foundation "grazed" standing crop value for each combination. This same historical weather data will then be statistically analyzed to create weather generator coefficients that have been synchronized with stages of the ENSO/SOI predictions coming from NOAA’s Climate Prediction Center.

Every 15 days, a computing system in the Center for Natural Resource Information Technology in TAES will acquire the NEXRAD precipitationr data from a server at the TAES Blackland Research Center and National Weather Service torun the PHYGROW model and output the projected forage supply relative to the long-term forage supply, expressed as a percent deviation from the baseline forage. (see attached figure from south Texas). A geo-referenced map of forage supply deviations for each major kind of livestock and major ungulates (mostly white-tailed deer) will be created and provided on the internet and distributed to key communication sources via the Center for Grazingland and Ranch Management in cooperation with the Texas Department of Agricultural and Agricultural Communications at Texas A&M University. A similar set of output will be generated for crops statewide as part of the Crop Early Warning System as a major component of the Statewide Drought Mangement Program.

Another key element of the system is use of the animal to tell us how the emerging conditions are affecting the animal’s ability to garner nutrients from grazinglands to meet their needs. A statewide laboratory established by TAES in the Ranching Systems Group called the Grazingland Animal Nutrition Lab at Texas A&M University has developed a rapid monitoring system for assessing the protein and energy status of free-ranging livestock via fecal scans with a near infrared reflectance spectrophotometer. Ranchers currently use the system by sending fresh fecal sample in an insulated mailer via 2-day priority mail. The lab returns predictions of diet protein and energy content in 48 hours and can use the NUTBAL Nutritional Balance Analyzer to predict weight/condition change as well. The lab currently maps diet quality from samples over the entire USA using advanced spatial analysis tools. However, the system is subject to spatial discontinuity of samples being sent to the lab.

To ensure a spatially robust map of diet quality and kind/class performance trends in the State, a fecal sampling source will be identified in each county where the land holder will agree to provide fecal samples to the lab every 30 days. These samples will then be used to predict how a virtual herd of animals in that region would be performing without supplement inputs. Deficits and surplus of protein and net energy will be mapped relative to the deviations in forage supply to emerge a sequence of emerging conditions (watch, warning, rapid response assessment, alert, critical) that are sent out via radio, television, internet, and print media.

TAES scientists and TAEX specialists/agents will work together with rancher focus groups to develop on-ranch decision aids to effectively use the forage deficit information and nutrient status reports. These tools will be designed to be easy to use and provide valued information to livestock producers. This will create a strong link between advanced computing technology, state of the art monitoring systems and practical on-ranch decision aids. Within this framework, a matrix of specialists will be identified across multiple agencies and institutions to form rapid response teams to evaluate predicted problem areas. This feedback coupled with our "Master Drought Observers" network will be critical to the success of the system, allowing tuning of the system and improvement of its functionality.

For the first time, the people of Texas will be provided information on emerging weather conditions as they impact the States natural resources while ranchers will be able to make timely, rational decisions concerning feeding and destocking or restocking. The Texas Livestock Early Warning System provides an information infrastructure that helps bond rural and urban populations concerns for the conservation of their natural resources and strong ranching heritage across the State.

Send mail to  ganlab@cnrit.tamu.edu with questions or comments about this web site.
Last modified: July 05, 2001