Abstract
Abstract. Wildfires in sagebrush (Artemisia spp.)-dominated semi-arid ecosystems in the western United States have increased dramatically in frequency and severity in the last few decades. Severe wildfires often lead to the loss of native sagebrush communities and change the biogeochemical conditions which make it difficult for sagebrush to regenerate. Invasion of cheatgrass (Bromus tectorum) accentuates the problem by making the ecosystem more susceptible to frequent burns. Managers have implemented several techniques to cope with the cheatgrass–fire cycle, ranging from controlling undesirable fire effects by removing fuel loads either mechanically or via prescribed burns to seeding the fire-affected areas with shrubs and native perennial forbs. There have been a number of studies at local scales to understand the direct impacts of wildfire on vegetation; however there is a larger gap in understanding these impacts at broad spatial and temporal scales. This need highlights the importance of dynamic global vegetation models (DGVMs) and remote sensing. In this study, we explored the influence of fire on vegetation composition and gross primary production (GPP) in the sagebrush ecosystem using the Ecosystem Demography (EDv2.2) model, a dynamic global vegetation model. We selected the Reynolds Creek Experimental Watershed (RCEW) to run our simulation study, an intensively monitored sagebrush-dominated ecosystem in the northern Great Basin. We ran point-based simulations at four existing flux tower sites in the study area for a total of 150 years after turning on the fire module in the 25th year. Results suggest dominance of shrubs in a non-fire scenario; however under the fire scenario we observed contrasting phases of high and low shrub density and C3 grass growth. Regional model simulations showed a gradual decline in GPP for fire-introduced areas through the initial couple of years instead of killing all the vegetation in the affected area in the first year itself. We also compared the results from EDv2.2 with satellite-derived GPP estimates for the areas in the RCEW burned by a wildfire in 2015 (Soda Fire). We observed moderate pixel-level correlations between maps of post-fire recovery EDv2.2 GPP and MODIS-derived GPP. This study contributes to understanding the application of ecosystem models to investigate temporal dynamics of vegetation under alternative fire regimes and post-fire ecosystem restoration.
Highlights
The number and intensity of wildfires in the sagebrush steppe of the semi-arid Great Basin, western USA, have increased dramatically (Keane et al, 2008)
Temporal dynamics of the gross primary production (GPP) for shrub and C3 grass plant functional type (PFT) were similar for the Lower Sheep (LS), Wyoming Big Sagebrush (WBS), and Upper Sheep (US) sites, while they were slightly different for the Reynolds Mountain Sagebrush (RMS) site (Fig. 2), which is located at a higher elevation (Fig. 1a)
We explored fire-induced alterations to GPP in a dryland shrub ecosystem, in terms of shrub and C3 grass PFTs
Summary
The number and intensity of wildfires in the sagebrush steppe of the semi-arid Great Basin, western USA, have increased dramatically (Keane et al, 2008). Even though fire is often recognized as a natural ecosystem process, it reduces woody shrub biomass while increasing herbaceous biomass (Ellsworth et al, 2016). Invasion of nonnative cheatgrass (Bromus tectorum) alters the competitive balance between woody and herbaceous plants and makes the ecosystem more susceptible to frequent and larger fires (Baker, 2006; Building et al, 2013; Whisenant, 1990). A recent study has shown that this cheatgrass–fire cycle has resulted in more than one-third of the Great Basin being invaded by cheatgrass (Bradley et al, 2018), which represents an enormous community shift with potentially large yet unknown effects on ecosystem function at a regional scale (Bradley et al, 2006; Bradley, 2010; Fusco et al, 2019)
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