Evaluating Performance of the Ecosystem Demography Model in Simulating Dryland GPP

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Dynamic global vegetation models can reveal much about carbon cycling in different ecosystems, yet the performance of these models in drylands is complicated partly by the heterogeneity of the vegetation and hydrometeorological conditions. 

Researchers evaluated the performance of the Ecosystem Demography model (EDv2.2) for drylands to facilitate improved understanding of gross primary production (GPP) as one of the important components of the carbon cycle. GPP was estimated from model simulations using eddy covariance data and compared to estimates using remote sensing in a dryland watershed in Idaho, 2000-2017. Results showed good model performance between simulated and measured GPP in lower elevations of the watershed, in which precipitation clearly drives GPP, yet performance degraded in more productive and heterogeneous sites at higher elevations. To improve model performance, future studies could introduce additional plant functional types for drylands and modify simulated plant processes such as plant hydraulics and phenology. 

Dashti, H., Pandit, K., Glenn, N.F., Shinneman, D.J., Flerchinger, G.N., Hudak, A.T., de Graaff, M., Flores, A.N., Ustin, S., Ilangakoon, N., Fellows, A.W., 2021, Performance of the ecosystem demography model (EDv2.2) in simulating gross primary production capacity and activity in a dryland study area: Agricultural and Forest Meteorology, v. 297, p. 108270, https://doi.org/10.1016/j.agrformet.2020.108270 

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Date published: November 20, 2017
Status: Active

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