Modeling Herbaceous Biomass for Grazing and Fire Risk Management

Abstract

Both grazing and fine fuels management are dependent on the temporal and spatial distribution of herbaceous biomass production. Rangeland and wildland fire managers can both benefit from knowing when and where there is excessive herbaceous biomass buildup. In this study, we compared modeled herbaceous biomass outputs from the Phytomass Growth Simulator (Phygrow) to observe and predict herbaceous production on desert, juniper, and pine sites on the Coconino National Forest in Arizona. Models were validated with: (a) 2 years of quarterly data, and (b) fire season-only data. The Phygrow model showed strong agreement between observed and predicted values year-round on the desert (r2 = 0.73) and pine sites (r2 = 0.69), and a lower, but positive agreement in the juniper sites (r2 = 0.54). Fire season predictions were strong for all ecosystem types (desert r2 = 0.89; juniper r2 = 0.62; pine r2 = 0.94), suggesting that the Phygrow model is well suited to provide valuable decision support information with which to address both rangeland and fire management objectives.

Keywords

• Coconino National Forest
• decision support system
• fine fuel
• herbivory
• Phygrow
• understory