Global Evaluation of the Ecosystem Demography Model (ED v3.0)
- 1Department of Geographical Sciences, University of Maryland, College Park, MD 20770, USA
- 2Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
- 3Regrow Agriculture Inc., Durham, NH 03824, USA
- 4Wildland Fire Science, Tall Timbers Research Station and Land Conservancy, Tallahassee, FL 32312, USA
- 5Universities Space Research Association, Columbia, MD 21046, USA
- 6Department of Plant Science & Landscape Architecture, University of Maryland, College Park, MD 20770, USA
- 7Department of Geography, National University of Singapore, 117570, Singapore
Abstract. Terrestrial ecosystems play a critical role in the global carbon cycle but have highly uncertain future dynamics. Ecosystem modelling that includes the scaling-up of underlying mechanistic ecological processes has the potential to improve the accuracy of future projections, while retaining key process-level detail. Over the past two decades, multiple modelling advances have been made to meet this challenge, including the Ecosystem Demography (ED) model and its derivatives including ED2 and FATES. Here, we present the global evaluation of the Ecosystem Demography model (ED v3.0), which likes its predecessors features the formal scaling of physiological processes of individual-based vegetation dynamics to ecosystem scales, together with integrated submodules of soil biogeochemistry and soil hydrology, while retaining explicit tracking of vegetation 3-D structure. This new version builds on previous versions and provides the first global calibration and evaluation, global tracking of the effects of climate and land-use change on vegetation 3-D structure, new spin-up process and input datasets, as well as numerous other advances. Model evaluation was performed with respect to a set of important benchmarking datasets, and model estimates were within observational constraints for multiple key variables including: (i) global patterns of dominant plant functional types (broadleaf vs evergreen); (ii) spatial distribution, seasonal cycle, and interannual trends of global Gross Primary Production (GPP); (iii) global interannual variability of Net Biome Production (NBP); and (iv) global patterns of vertical structure including leaf area and canopy height. With this global model version, it is now possible to simulate vegetation dynamics from local to global scales and from seconds to centuries, with a consistent mechanistic modelling framework amendable to data from multiple traditional and new remote sensing sources, including lidar.
Lei Ma et al.
Lei Ma et al.
Model code and software
Global Evaluation of the Ecosystem Demography Model (ED v3.0) https://doi.org/10.5281/zenodo.5236771
Lei Ma et al.
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