Coastal Bermudagrass, Bahiagrass, and Native Range Simulation at Diverse Sites in Texas

Effective comparisons of natural grasslands and improved pasture require a robust model for plant growth, soil water balance, runoff, soil erosion, and climatic impacts. Our first objective was to develop plant parameters in the field that enabled the ALMANAC model to simulate growth of coastal bermudagrass [Cynodon dactylon (L.) Pers.]. Pensacola bahiagrass (Paspalum notatum Flügge var saurae Parodi), and some common native, warm-season grasses. Parameters included leaf area, light interception, biomass growth, and nitrogen concentration. The maximum leaf area index values of coastal bermudagrass and bahiagrass were near 2.2. Those for native grasses other than switchgrass (Panicum virgatum L.) were much less. Mean values for light extinction coefficient ranged from 0.7 to 2.1. Radiation use efficiency values for four of the five measured grass species were between 1.0 and 2.0 g MJ. Grass [N] values showed similar patterns of seasonal change among species. Our second objective was to use these grass parameters to simulate biomass production of coastal bermudagrass, bahiagrass, and some native grasses on representative soils in several counties in a number of regions of Texas. Counties and soils that were simulated represented a diversity of sites in Texas where improved grasses and native grasses are grown. The ALMANAC model reasonably simulated biomass means and SDs for native grasses, coastal bermudagrass, and bahiagrass. The model is a realistic tool to simulate effects of soil type and weather on native and improved grass productivity on such diverse sites. AS NATURAL GRASSLANDS are converted to or from improved pasture or croplands, the change in ground cover can have large effects on the soil nutrient balance, soil erosion, and water quality in adjacent waterways. Effective, efficient evaluation of the impact of such changes in vegetative cover requires a robust model for plant growth, the soil water balance, runoff, soil erosion, and climatic impacts. There are many possible applications of such a model. It could be used to compare mean productivity and stability of productivity across years for native grass range sites and for improved pastures. It also could simulate environmental impacts of changing plant cover. These impacts include changes in soil erosion and water quality. Model simulations could help optimize livestock stocking rates and applied nutrients for native and improved grasses on different soils with varying rainfall amounts. Likewise, the responses of soil erosion and forage productivity to different grazing intensities could be simulated. Ideally, such a model would have sufficient detail to simulate several plant species, soils, and climatic conditions without excessive input requirements. The model should be able to simulate improved grasses and common native grasses. The required plant parameters should be simple enough to be readily derived from published studies in conjunction with measurements that can be obtained without an inordinate amount of time and effort in field experiments. Themodel should have processbased components to simulate leaf area growth, biomass production, and nutrient uptake. In addition, the required soils data should be readily available, and there should be data sets with sufficient detail available for validating grass production simulations. There has been a diversity of simulation models developed for grasses. These models include the SPUR (Simulation of Production and Utilization on Rangelands) model (Wight and Skiles, 1987; MacNeil et al., 1985; Stout, 1994) and the ELM (Ecosystem Level Model) (Innis, 1978). In addition, Overman et al. (1988, 1989) described two simple models to simulate coastal bermudagrass production with only three or four parameters that are fitted for each new location. More recently, Rymph et al. (2004) adapted the CROPGRO model (Boote et al., 1998) to simulate bahiagrass. A more general model, called ALMANAC (Agricultural Land Management Alternative with Numerical Assessment Criteria), simulates a diversity of grass species as well as crops and interspecies competition (Kiniry et al., 1992). This model meets all the above-mentioned criteria and has great potential for the listed applications. It is process based and can simulate one or several competing species. It simulates plant growth using independently derived parameters, with no recalibration among sites. The model includes components for the water balance, nutrient balance, and interception of solar radiation by competing plant species. Although some subroutines and functions from the EPIC (Erosion Productivity Impact Calculator) model (Williams et al., 1984) are included, the plant growth simulation is more detailed (Kiniry, 2006). Daily values for maximum and minimum temperatures, precipitation, and incident solar radiation are required. Soil inputs are readily available from published USDA-ARS soil surveys. The ALMANAC model is a valuable tool to simulate diverse cropping systems and diverse rangelands in the J.R. Kiniry, USDA-ARS, Grassland, Soil and Water Res. Lab., 808 East Blackland Rd., Temple, TX 76513; B.L. Burson, USDA-ARS, 430 Heep Center, Texas A&M Univ. College Station, TX 77843-2474; G.W. Evers, Texas A&M Univ. Agric. Res. and Ext. Center, P.O. Box E, Overton, TX 75684; J.R. Williams, Texas Agric. Exp. Stn., 808 E. Blackland Rd., Temple, TX 76513; H. Sanchez, USDA-NRCS, P.O. Box 6567, Fort Worth, TX 76115; C. Wade, USDA-NRCS, 2301 N. Travis Ave., P.O. Box 1027, Cameron, TX 76520-1027; and J. Featherston and J. Greenwade, USDA-NRCS, 101 S. Main, Temple, TX 76501-7682. Received 13 Apr. 2006. *Corresponding author ([email protected]). Published in Agron. J. 99:450–461 (2007).