||Increases in atmospheric carbon dioxide concentrations (ca) will lead to changes in the climate that alter mean air temperature (Ta) and precipitation (P) patterns. The ability of terrestrial ecosystems to absorb ca is sensitive to these climatic conditions, as well as to ca, thereby creating a feedback that has the potential to accelerate warming. To describe the feedback, the primary pathways by which elevated ca, Ta, and changing P patterns simultaneously impact ecosystem photosynthesis and respiration must be quantified. This work will produce a synthesis that capitalizes on the strengths of different models and incorporates the important feedbacks of the soil-plant-atmosphere system at pertinent spatial and time scales. An optimization modeling approach will be used to capture stomatal responses to simultaneous elevated ca, changes in Ta, vapor pressure deficit and leaf water potential. Scaling-up from leaves to the canopy to provide a mathematically usable form for coarse-scale models will be completed at two time scales: at short time scales (<1 h), where leaf area density and autotrophic biomass can be assumed constant, and at longer time scales (e.g., seasonal or longer), where changes in these quantities are large. Autotrophic respiratory processes reflect changes in biomass in pools determined using standard biomass budget equations, which will be modified to include carbon allocation rules derived from resource optimization theories that explicitly consider soil and foliage nutrition. For heterotrophic processes, at minimum, three interacting soil carbon pools must be considered: litter, more stabilized SOM, and microbial biomass. Rates of decomposition, nitrogen mineralization, nitrification, and de-nitrification will be modeled together with soil moisture and temperature. Lastly, we will use a novel dimension reduction approach to simplify the multi-dimensional phase-space of this detailed model to a system of a few ordinary differential equations and prepare this simplified model for incorporation into existing climate-carbon models.