Performance of the ecosystem demography model (EDv2.2) in simulating gross primary production capacity and activity in a dryland study area
Links
- More information: Publisher Index Page (via DOI)
- Open Access Version: Publisher Index Page
- Download citation as: RIS | Dublin Core
Abstract
Dryland ecosystems play an important role in the global carbon cycle, including regulating the inter-annual global carbon sink. Dynamic global vegetation models (DGVMs) are essential tools that can help us better understand carbon cycling in different ecosystems. Currently, there is limited knowledge of the performance of these models in drylands partly due to characterizing the heterogeneity of the vegetation and hydrometeorological conditions. The aim of this study is to evaluate the performance of a DGVM for drylands to facilitate improved understanding of gross primary production (GPP) as one of the important components of the carbon cycle. We performed a sensitivity analysis and calibrated the Ecosystem Demography (EDv2.2) DGVM to simulate GPP in a dryland watershed (Reynolds Creek Experimental Watershed, Idaho) in the western US for the years 2000-2017. GPP capacity and activity were investigated by comparing model simulations with GPP estimated from eddy covariance data (available from 2015-2017) and remote sensing products (2000-2017). Our results show good performance of EDv2.2 at daily timesteps (RMSE≈0.38[kgC/m2/year])
Study Area
Publication type | Article |
---|---|
Publication Subtype | Journal Article |
Title | Performance of the ecosystem demography model (EDv2.2) in simulating gross primary production capacity and activity in a dryland study area |
Series title | Agricultural and Forest Meteorology |
DOI | 10.1016/j.agrformet.2020.108270 |
Volume | 297 |
Year Published | 2021 |
Language | English |
Publisher | Elsevier |
Contributing office(s) | Forest and Rangeland Ecosystem Science Center |
Description | 108270, 10 p. |
Country | United States |
State | Idaho |
Other Geospatial | Reynolds Creek Experimental Watershed |
Google Analytic Metrics | Metrics page |