Woody plant encroachment restricts forage production and capacity to produce grazing livestock. Biophysical plant growth simulation and economic simulation were used to evaluate a prescribed burning range management technique. Modeling systems incorporated management practices and costs, historical climate data, vegetation and soil inventories, livestock production data, and historical regional livestock prices. The process compared baseline non-treatment return estimates to expected change in livestock returns resulting from prescribed burning. Stochastic analyses of production and price variability produced estimates of greater net returns resulting from use of prescribed burning relative to the baseline.

The purpose of this study was to determine the economic risk efficiency of implementing a boll weevil (Anthonomus grandis [Boheman]) eradication (BWE) program in cotton (Gossypium hirsutum L.) producing regions of the Mississippi Delta. Alternative producer pest management practices and program cost sharing were incorporated into a biophysical cotton simulation model. Participation in a BWE program along with strict adherence to Cooperative Extension Service pest management guidelines proved to be the risk efficient practice.

Linear programming and regional input-output models were applied to estimate the impacts of increased pumping costs for irrigated agriculture due to groundwater depletion principally caused by the expanding urban area of San Antonio, Texas. A biophysical simulator was used to estimate linear programming coefficients of crop yield by irrigation level and timing. The results indicate significant local (county) economic impacts from groundwater mining but insignificant regional impacts. A major improvement in irrigation efficiency would be required to offset the increased pumping costs and reduced water availability associated with increased lifts due to urban expansion.

Economic feasibility of Texas Blacklands corn production in relation to sorghum, wheat, and cotton is studied. Biophysical simulation generated yield data are integrated with an economic decision model using quadratic programming. Given the various scenarios analyzed, corn is economically feasible for the Blacklands. A crop mix of half corn and half cotton production is selected under risk neutrality with wheat entering if risk aversion is present. Corn and grain sorghum production are highly substitutable. Profit effects attributed to changing corn planting dates are more pronounced than profit changes resulting from altering corn population or maturity class.

Given an equipment complement, a specific crop mix has a probability distribution for whole-farm net returns. Increasing crop acreage while holding the set of equipment constant will reduce fixed costs per acre, but it will also increase the length of time required to complete crucial field operations such as planting and harvesting. Thus, the probability of encountering weather-related delays in fieldwork will increase. This increase in delays may cause a decline in yields and changes in the distribution of net returns. This paper develops a Target MOTAD model capable of capturing intra-year impacts on profit that arise from the timing of planting and harvesting operations as well as inter-year impacts on profits that are due to variations in economic and weather-related factors. The model relies on estimates of available fieldwork time and a crop's harvestable yield in different time periods throughout the harvest season.

The value of an innovative seed technology is estimated in a discrete stochastic programming framework for a representative farm in the northern Corn Belt. Temperature-activated polymer-coated seed has the potential to increase net returns by increasing yields due to early planting and use of longer season varieties, as well as reducing yield loss due to delayed planting. A biophysical simulation model was used to estimate die impact of polymer-coated seed on corn and soybean yields and on field day availability for five planting periods, three crop varieties, and two tillage systems on two different soils under varying weather conditions.

Production timing is an essential element in fresh vegetable growers'efforts to maximize profitability and reduce income risks. The present studyuses biophysical simulation modeling coupled with a dual crop (tomatoes,sweet corn) whole-farm economic formulation to analyze the effects ofgrowers' risk aversion levels and price consideration (seasonal or annualprice consideration) in expected net returns and production practices. Thefindings indicate that consideration of seasonal price trends results inhigher expected net returns and greater opportunities to mitigate risk.Furthermore, risk aversion levels substantially influence production timingwhen seasonal price trends are considered.