Scaling from individual plants to the globe in an Earth System Model: height structured competition and carbon cycling

Monday, 15 December 2014: 5:15 PM
Ensheng Weng1, Sergey Malyshev2, Jeremy W Lichstein3, Caroline E Farrior1, Ray Dybzinski1, Tao Zhang3, Elena Shevliakova4 and Stephen W Pacala5, (1)Princeton University, Princeton, NJ, United States, (2)GFDL, Princeton, NJ, United States, (3)University of Florida, Gainesville, FL, United States, (4)Princeton Environmental Institute, Princeton, NJ, United States, (5)Princeton University, Ecology and Evolutionary Biology, Princeton, NJ, United States
The long-term and large scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water and nutrients. Woody biomass, a pool of carbon (C) larger than that in the atmosphere, exists because of height-structured competition for light. However, none of the current Earth System Models that predict climate change and C cycle feedbacks includes a mechanistic formulation for height-structured competition for light, or an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition and explicit scaling from individuals to ecosystems into the land model (LM3) currently used in the Earth System Models developed by the Geophysical Fluid Dynamics Laboratory based on the Perfect Plasticity Approximation model (PPA), which has been shown to scale accurately from individual plants to stands in individual-based simulation models of plant competition for light, water and nutrients. Because of the tractability of the PPA, the coupled LM3-PPA model is able to include a large number of phenomena across a range of spatial and temporal scales, and still retain computational and mathematical tractability. We test a range of predictions against data from the temperate forests in northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy shifts at different atmospheric CO2 concentrations due to competition with alternative strategies in the model. The results show that the competitively optimal allocation of carbon to leaves, wood, and fine roots depends on the atmospheric CO2 concentration, and that C sinks caused by CO2 fertilization in forests limited by light and water are down-regulated if allocation tracks changes in the competitive optimum, indicating the critical roles of competition played in predicting forest ecosystems responses to climate change.