Global evaluation of the Ecosystem Demography model (ED v3.0)

Abstract

Abstract. Terrestrial ecosystems play a critical role in the global carbon cycle but have highly uncertain future dynamics. Ecosystem modeling 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 modeling advances have been made to meet this challenge, such as 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, like its predecessors, features the formal scaling of physiological processes for 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 model 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, 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) the spatial distribution, seasonal cycle, and interannual trends for global gross primary production (GPP), (iii) the 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 modeling framework amendable to data from multiple traditional and new remote sensing sources, including lidar.

Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling

“…This study used a global version of ED (v3.0) which has been developed and calibrated at global scale (Ma et al, 2022). This version has also been benchmarked by a series of datasets including spatial distribution of plant function types, carbon stocks in vegetation and soil, carbon and water fluxes, and vegetation structures across a range of spatial and temporal scales.…”

“…The most comparable reference data were from carbon cycle models driven by land-use history. To isolate the impact of the initialization approach itself, ED-LUH2 was used as a reference (Ma et al, 2022). ED-LUH2 used the same ED model…”

“…ecosystem demography, forest aboveground carbon stocks and fluxes, GEDI ICESat-2, lidar canopy height, process-based model, spatial heterogeneity respect to modeling carbon dynamics, using comprehensive benchmarking datasets (Ma et al, 2022). The goal of this study was to combine these advances to quantify the spatial heterogeneity of forest structure and its impacts on global forest carbon stocks and fluxes.…”

“…First, lidar observations of 3D vegetation structure have been shown to provide direct and accurate measurement of forest vertical structure and serve as a proxy for measurement of aboveground carbon stocks (Drake et al, 2002; Dubayah et al, 2010; Dubayah & Drake, 2000; Huang et al, 2019; Los et al, 2012; Tang et al, 2012, 2021). Second, height‐structured ecosystem models have advanced with an emphasis on explicit characterization of individual‐based dynamics and forest vertical structure (Fisher et al, 2018; Hurtt et al, 1998; Longo et al, 2019; Ma et al, 2022; Medvigy et al, 2009; Moorcroft et al, 2001). Used together, these tools have provided powerful constraints on both aboveground carbon stocks and net carbon fluxes, and facilitated projections of forest carbon sequestration potential over heterogeneous landscapes (Antonarakis et al, 2011; Hurtt et al, 2004, 2019; Ma et al, 2021; Rödig et al, 2017).…”

“…The recent emergence of spaceborne lidar missions, such as GEDI (Global Ecosystem Dynamics Investigation) and ICESat‐2 (ICE, Cloud, and Land Elevation Satellite 2), provide unprecedented global observations of forest structure (Dubayah et al, 2020; Markus et al, 2017). In parallel, a global version of the ED model (ED v3) has recently been developed and evaluated for its performance with respect to modeling carbon dynamics, using comprehensive benchmarking datasets (Ma et al, 2022). The goal of this study was to combine these advances to quantify the spatial heterogeneity of forest structure and its impacts on global forest carbon stocks and fluxes.…”