Optimal Rangeland Stocking Decisions Under Stochastic and Climate‐Impacted Weather

Abstract

A Stochastic Dynamic Programming (SDP) model is developed to analyze optimal stocking rates in the face of weather uncertainty and potential climate change projections. The model extends previous work modeling grazing as a predator‐prey relationship. Attention is given to profit maximizing decisions when growing season precipitation is unknown. Comparisons are made across results from a model that utilizes constant growing season precipitation in all years. Results suggest that optimal stocking rates and profitability decrease in climate change scenarios with increased precipitation variability as compared to the historical stochastic weather scenario.

Keywords: climate change, optimal stocking rate, precipitation, rangeland, stochastic dynamic programming (SDP)