Utility of Seasonal Climate Forecasts in Management of Winter-Wheat Grazing

Abstract

In the southern Great Plains of the United States, winter wheat is a dual purpose crop that produces forage for livestock grazing in the fall and winter, and a grain crop in the spring. Seasonal and interannual climate variations are pronounced and make it difficult to anticipate forage production and number of cattle for grazing. Seasonal climate forecasts could improve projections of forage availability and thereby help with stocking rate decisions that are often made in September or October before actual forage production is known. A case study was conducted to determine if seasonal climate forecasts contained enough decision-relevant information to attract producer attention and justify development of an operational decision support system for projecting forage availability and selecting stocking rate. This question was addressed by investigating three strong seasonal climate forecasts issued in August and September by the NOAA Climate Prediction Center (CPC) for central Oklahoma. Forecast of daily weather, forage availability, and stocker performance were simulated by computer models for physiographic and climatic conditions in the region. Simulation results revealed that strong seasonal forecasts issued in August and September for central Oklahoma had enough impact on forage production and stocker weight gain to attract producers' attention, yet the small increase in odds of realizing a forecast-based outcome dampened producers' enthusiasm for making decisions based on seasonal climate forecasts. Furthermore, the low frequency of strong seasonal forecasts issued between 1997 and 2008 (on average 1 in every 4 years) do not favor, at this time, development of an operational decision tool that specifically uses the CPC seasonal climate forecasts as a basis for projecting forage availability and selecting stocking rate in central Oklahoma. It was suggested that initial soil moisture and climate risk may present a potentially more promising approach for developing decision support information for stocking rate decisions.