There is a gap in understanding the impacts of wildfire on vegetation at broad spatial and temporal scales, highlighting the need for accurate global dynamic vegetation models.
Researchers tested the Ecosystem Demography (EDv2.2) model for predicting how fire affects vegetation composition and gross primary production (GPP) in the Reynolds Creek Experimental Watershed, representative of sagebrush-dominated ecosystems in the northern Great Basin. Modeling simulations showed that with a sustained absence of fire, shrub cover and biomass can dominate over herbaceous species; however, under the fire scenario there were contrasting phases of high and low shrub and grass growth. Regional simulations revealed a gradual decline in GPP through the initial couple of post-fire years instead of simply killing all vegetation in the first year after fire. Researchers observed a good spatial agreement between modeled GPP and a Landsat image-derived index. The EDv2.2 model captured the prevailing trend in ecosystem response to fire, highlighting its potential utility as a planning tool.
Pandit, K., Dashti, H., Hudak, A.T., Glenn, N.F., Flores, A.N., Shinneman, D.J., 2021, Understanding the effect of fire on vegetation composition and gross primary production in a semi-arid shrubland ecosystem using the Ecosystem Demography (EDv2.2) model: Biogeosciences Discussions, p. 1-20, https://doi.org/10.5194/bg-2019-510
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