Opportunities for Increasing Utility of Models for Rangeland Management

A large number of empirical and mechanistic simulation models and decision support tools have been produced for rangelands. Collectively, these models have considerably increased our fundamental knowledge and understanding of the dynamics of ecosystem functions, processes, and structure. We explore three areas where models for rangeland management are often challenging for land managers and enterprise-level decision making: 1) coping with spatiotemporal and climatic variability in implementing scenario forecasting, risk assessments, and adaptive management; 2) addressing outputs of multiple ecosystem goods and services and determining whether they are synergistic or competitive; and 3) integrating experimental and experiential knowledge and observations into decision making. Increasing the utility of models for rangeland management remains a key frontier and a major research need for the modeling community and will be achieved less by further technical advances and model complexity and more by the use of existing topoedaphic databases, the capacity to readily incorporate new experimental and experiential knowledge, and the use of frameworks that facilitate outcome-based, adaptive decision making at the enterprise level with associated economic considerations. Opportunities exist for increasing the utility of models for decision making and adaptive rangeland management through better matching of model complexity with enterprise-level, decision-making goals. This could be accomplished by incorporating a fundamental understanding of herbivory, fire, and spatiotemporal interactions with weather patterns that affect multiple ecosystem functions. Most important, effective models would allow land managers in a changing and variable climate to 1) evaluate trade offs in producing multiple goods and services, 2) optimize the application of conservation practices spatially (comparing costs and benefits accrued across different timescales), and 3) incorporate manager capacity, including experience, skills, and labor input.