Using a Model and Forecasted Weather to Predict Forage and Livestock Production for Making Stocking Decisions In the Coming Growing Season.

Forecasting peak standing crop (PSC, kg/ha) for the coming grazing season can help ranchers make appropriate stocking decisions to reduce enterprise risks. Previously developed PSC predictors based on short-term experimental data (< 15 years) and limited (1-3) stocking rates (SR) not including the effect of SR on PSC explicitly, may limit the utility across different weather or SR conditions. Here, we used longer-term (30 years) measured data of PSC and steer weight gain (SWG), extended with the help of a model for SR effect, to develop multiple-variable regression functions for predicting PSC and SWG across a wide range of SR (0.2 to 1.32 steers/ha for a 4.5 month summer grazing season, June to mid-October) on a loam soil in Northern Mixed-Grass Prairie. The April-June rainfall was the primary weather variable influencing PSC (R² = 0.45); inclusion of SR and soil water content on April 1 improved the accuracy in predicting PSC (R² =0.64). Combining the response of PSC to SR and the response of SWG to both PSC and SR enables ranchers to explore tradeoffs between economic net return and environmental impact (land conservation) as influenced by SR and weather variations (April-June rainfall). The result was further extended to other two soil types (loam sandy and clay loam soils) using a simple soil influence factor estimated from the long-term simulations. A simple spreadsheet-based decision support tool has been developed to use forecasted April-June rainfall to predict forage and livestock production for making SR decisions in the coming grazing season.