Improvements in Simulation Modeling for Estimating Patch and Landscape Forage Biomass on Rangelands
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The ability to characterize the productivity of vegetation over large landscapes can be an important component in the assessment of drought impacts, natural resource management options, environmental degradation, wildfire potential, and economic impacts of changing technologies. At the ranch or firm level, assessment of forage productivity for carrying capacity or stocking rate determination is one of the most critical factors for both economic and ecological sustainability. However, the time and resources required to conduct assessments of vegetation productivity over large landscapes are prohibitive, and are not always recoverable. Another complicating factor is that decisions regarding stocking rate may require near real-time information, especially in the face of drought. Vegetation productivity assessment is almost impossible to conduct on a near real-time basis, thus the information needed for stocking rate decisions is not always available when needed. The inability to make stocking rate decisions at critical times could lead to vegetation overuse and lead to degradation. Improvements in computing, along with near real-time production of climate data and remote sensing imagery, offer the opportunity to develop near-real time systems for monitoring vegetation on rangelands. The emergence of technology for estimating precipitation using techniques such as cold cloud, radar, and other remote sensing technology have made spatially explicit climate data, thus increasing their potential for use in near real-time systems. Improved computing has also increased the use of simulation modeling for rangelands. The application of these models includes simulations for hydrology, soil erosion, plant growth, or combinations of these. Many of these models could be modified or adapted for use in real-time monitoring systems. However, more work is needed to improve their ability to predict biomass at the landscape level. Another limitation of simulation models for estimating forage biomass is the ability to simulate animal movement. Elevation, slope, distance to water, and the species composition of the vegetation at the site can influence how different kinds and classes of animals use the landscape. Recent studies, using Global Positioning System (GPS) technology, are offering new insights into how grazing animals use the landscape with regard to specific soil types, rock cover, location of supplements, and location of water. For simulation modeling to be effective, additional study is needed to incorporate the differential use of the landscape by livestock. Lastly, the ability to dynamically model vegetation state and transition changes on rangelands using simulation models is a limiting factor. The capability to model state and transition change within the simulation modeling environment will be extremely important for assessing impacts of climate change, shifts in composition between C3 and C4 plants, carbon sequestration, and assessing impacts to ecosystem services. This capability will also be needed for developing adaptive management strategies and for building next generation early warning systems.