Big landscapes meet big data: Informing grazing management in a variable and changing world

Abstract

Rangeland-based livestock raising is the only agricultural production system that maintains native plant communities, providing ecosystem services in the same space as food and fiber production. Annual aboveground net primary productivity (ANPP) underlies forage production and multiple ecosystem services. ANPP is highly variable in rangelands in the western United States, across the landscape, from year to year, and within a growing season. Variability is also increasing as the climate changes. Grazing management decisions that determine when, where, and how much of ANPP is consumed by livestock, including stocking rate decisions, can ultimately determine rangeland health and the future sustainability of livestock production and provision of ecosystem services. Yet managers' access to data on available forage and its variability is limited, and existing field methods to quantify forage production accurately require extensive sampling and are prone to errors or bias. A variety of remotely sensed data sources exist to help characterize forage availability and how it has varied spatially and temporally over the last 30 or more years, as well as other datasets that can estimate available forage and inaccessible terrain for livestock. We discuss the need for a state-of-the-art decision support tool that integrates available remote-sensing data on forage availability with land managers’ knowledge of local needs and information for managers to access to the depth and breadth of information they need to sustainably manage grazing under variable and changing conditions. Such a decision support tool could help land managers better manage rangeland ecosystems with flexible stocking rates and adaptive grazing management opportunities that adjust to variations in ANPP, leading to increased regional and site-specific rangeland resilience.