Developing and optimizing shrub parameters representing sagebrush (<i>Artemisia</i> spp.) ecosystems in the northern Great Basin using the Ecosystem Demography (EDv2.2) model

Abstract

Abstract. Ecosystem dynamic models are useful for understanding ecosystem characteristics over time and space because of their efficiency over direct field measurements and applicability to broad spatial extents. Their application, however, is challenging due to internal model uncertainties and complexities arising from distinct qualities of the ecosystems being analyzed. The sagebrush-steppe ecosystem in western North America, for example, has substantial spatial and temporal heterogeneity as well as variability due to anthropogenic disturbance, invasive species, climate change, and altered fire regimes, which collectively make modeling dynamic ecosystem processes difficult. Ecosystem Demography (EDv2.2) is a robust ecosystem dynamic model, initially developed for tropical forests, that simulates energy, water, and carbon fluxes at fine scales. Although EDv2.2 has since been tested on different ecosystems via development of different plant functional types (PFT), it still lacks a shrub PFT. In this study, we developed and parameterized a shrub PFT representative of sagebrush (Artemisia spp.) ecosystems in order to initialize and test it within EDv2.2, and to promote future broad-scale analysis of restoration activities, climate change, and fire regimes in the sagebrush-steppe ecosystem. Specifically, we parameterized the sagebrush PFT within EDv2.2 to estimate gross primary production (GPP) using data from two sagebrush study sites in the northern Great Basin. To accomplish this, we employed a three-tier approach. (1) To initially parameterize the sagebrush PFT, we fitted allometric relationships for sagebrush using field-collected data, information from existing sagebrush literature, and parameters from other land models. (2) To determine influential parameters in GPP prediction, we used a sensitivity analysis to identify the five most sensitive parameters. (3) To improve model performance and validate results, we optimized these five parameters using an exhaustive search method to estimate GPP, and compared results with observations from two eddy covariance (EC) sites in the study area. Our modeled results were encouraging, with reasonable fidelity to observed values, although some negative biases (i.e., seasonal underestimates of GPP) were apparent. Our finding on preliminary parameterization of the sagebrush shrub PFT is an important step towards subsequent studies on shrubland ecosystems using EDv2.2 or any other process-based ecosystem model.

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

“…Despite the interannual variability evident in the observed flux tower data, the poor comparisons for the higher elevation sites US and RMS than the lower elevation sites could be explained by the fact that the shrub parameters we used were mainly developed and calibrated for the lower sites (Pandit et al, 2019), and thus may not have accounted for local variability. Higher ecosystem productivity and quick post-fire recovery at the RMS site compared to the other three sites can be associated with higher productivity, higher precipitation and lower temperature, as suggested by previous studies (Keane et al, 2008;Nelson et al, 2014;Shriver et al, 2018).…”

“…In this study, we used the version of EDv2.2 with shrub PFT (Pandit et al, 2019) to understand the effect of fire on a shrubland ecosystem in the Reynolds Creek Experimental Watershed (RCEW), Great Basin, USA. We explored the dynamics of shrub and C3 grass gross primary production (GPP) under alternative fire scenarios for four different sites (point-based analysis) in the study area, and also investigated model generated post-fire shrubland recovery patterns against observed Landsat imagederived Normalized Difference Vegetation Index (NDVI) (Wylie et al, 2003;Running et al, 2004) covering the entire RCEW area (regional-based analysis).…”

“…For the shrubs, we used a PFT especially developed for sagebrush in the study area based on our previous work (Pandit et al, 2019) whereas for the grasses, we used the temperate C3 grass PFT which is the closest match from among available PFTs in EDv2.2. We assumed that this existing temperate grass PFT in the model would represent common perennial grass species in the study area.…”

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

“…icantly across the Great Basin due to fire and other disturbances (Knick et al, 2003;Pilliod et al, 2017;Rigge et al, 2019;Schroeder et al, 2004). The low stature of sagebrush makes it less adapted in morphological terms to survive fires as most of the flammable fuels are close to the ground (Hood and Miller, 2007;McArthur and Stevens, 2004;Welch and Criddle, 2003).…”