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The Ecosystem Demography Model version 2.2 (ED-2.2) is a terrestrial biosphere model that simulates the biophysical and biogeochemical cycles of dynamic ecosystems while considering the role of vertical structure of plant communities and the heterogeneity of such structures across the landscape. In a companion paper, we described in detail how the model solves the energy, water, and carbon cycles, and verified the excellent conservation of such properties in long-term simulation. Here, we present a thorough assessment of the model's ability to represent multiple processes associated with the biophysical and biogeochemical cycles, with focus on the Amazon forest. We used multiple measurements from eddy covariance towers, forest inventory plots and regional remote-sensing products to assess the model's ability to represent biophysical, physiological, and ecological processes at multiple time scales ranging from sub-daily to century-long. The ED-2.2 model accurately describes the vertical distribution of light, water fluxes and the storage of water, energy and carbon in the canopy air space, the regional distribution of biomass in tropical South America, and the variability of biomass as a function of environmental drivers. In addition, ED-2.2 also simulates emerging properties of the ecosystem found in observations, such as the relationship between biomass and mortality rates and wood density, although the relationships predicted by the model were biased. We also identified some of the model limitations, such as the model's tendency to overestimate the magnitude and seasonality of heterotrophic respiration, and to overestimate growth rates in a nutrient-poor tropical site. The evaluation presented here highlights the potential of incorporating structural and functional heterogeneity within biomes in ESMs, to realistically represent the role of forest structure and composition on energy, water, and carbon cycles, as well as the priority areas for further model development. [ABSTRACT FROM AUTHOR]

Earth System Models (ESMs) have been developed to represent the role of terrestrial ecosystems on the energy, water, and carbon cycles. However, many ESMs still lack representation of within-ecosystem heterogeneity and diversity. In this manuscript, we present the Ecosystem Demography Model version 2.2 (ED-2.2). In ED-2.2, the biophysical and physiological cycles account for the horizontal and vertical heterogeneity of the ecosystem: the energy, water, and carbon cycles are solved separately for each group of individual trees of similar size and functional group (cohorts) living in a micro-environment with similar disturbance history (patches). We define the equations that describe the energy, water, and carbon cycles in terms of total energy, water, and carbon, which simplifies the ordinary differential equations and guarantees excellent conservation of these quantities in long-term simulation (< 0.1% error over 50 years). We also show examples of ED-2.2 simulation results at single sites and across tropical South America. These results demonstrate the model's ability to characterize the variability of ecosystem structure, composition and functioning both at stand- and continental-scales. In addition, a detailed model evaluation was carried out and presented in a companion paper. Finally, we highlight some of the ongoing developments in ED-2.2 that aim at reducing the uncertainties identified in this study and the inclusion of processes hitherto not represented in the model. [ABSTRACT FROM AUTHOR]

Amazon forests, which store ~50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale dieback of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem's resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest's response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions. [ABSTRACT FROM AUTHOR]