Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)

作者：Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin R. Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, Benjamin I. Cook · 发表于：Geoscientific model development · 年份：2022 · DOI：10.5194/gmd-15-8153-2022 · 被引用次数：15 · 研究领域：Plant Water Relations and Carbon Dynamics、Ecology and Vegetation Dynamics Studies、Soil Carbon and Nitrogen Dynamics

Abstract. We developed a demographic vegetation model, BiomeE, to improve the modeling of vegetation dynamics and ecosystem biogeochemical cycles in the NASA Goddard Institute of Space Studies' ModelE Earth system model. This model includes the processes of plant growth, mortality, reproduction, vegetation structural dynamics, and soil carbon and nitrogen storage and transformations. The model combines the plant physiological processes of ModelE's original vegetation model, Ent, with the plant demographic and ecosystem nitrogen processes that have been represented in the Geophysical Fluid Dynamics Laboratory's LM3-PPA. We used nine plant functional types to represent global natural vegetation functional diversity, including trees, shrubs, and grasses, and a new phenology model to simulate vegetation seasonal changes with temperature and precipitation fluctuations. Competition for light and soil resources is individual based, which makes the modeling of transient compositional dynamics and vegetation succession possible. Overall, the BiomeE model simulates, with fidelity comparable to other models, the dynamics of vegetation and soil biogeochemistry, including leaf area index, vegetation structure (e.g., height, tree density, size distribution, and crown organization), and ecosystem carbon and nitrogen storage and fluxes. This model allows ModelE to simulate transient and long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems. Furt...