Optimization of rangelands management strategies under rainfall and price risks.
Abstract
Dynamic programming was used to obtain optimal management and marketing policies for stocker operations in Southeastern Colorado under different stocking rates, rainfall, and price scenarios. Simulated steer liveweights at low, moderate, and high stocking rates were incorporated with simulated steer prices to maximize the present value of net returns from the sale of 0, 50, and 100% of the steer inventory in July, August, September, or October. Two low-risk, 1 moderate-risk, and 2 high-risk scenarios were considered. The 2 low-risk scenarios were favorable rainfall-optimistic price and favorable rainfall-pessimistic price. The moderate-risk scenario was average rainfall average price. The 2 high-risk scenarios were unfavorable rainfall-optimistic price and unfavorable rainfall-pessimistic price. The highest net returns from the low-risk and moderate-risk scenarios were obtained at the high stocking rate with sales in September and October. The highest net returns from the highrisk scenarios were obtained at the moderate stocking rate with sales in September and October. Risk-averse operators who are not prepared to handle sales before October will be better off using a low stocking rate. Risk-taker operators will obtain higher net returns than risk-averse operators using a high stocking rate providing they are prepared to sell half of the herd in July if cumulative rainfall up to June is below 149 mm. If this high stocking rate is maintained beyond July, operators should sell in September independently of the amount of rainfall or the level of prices in August.
Keywords
dynamic programming;risk;marginal returns;market prices;rain;stocking rate;pastures;range management