Tuesday, August 3, 2010 - 10:10 AM

OOS 13-7: CANCELLED - An integrated modeling framework for the assessment of multiple global changes on terrestrial productivity

Atul Jain1, Xiaojuan Yang2, Miaoling Liang2, and Rahul Barman1. (1) University of Illinois at Urbana-Champaign, (2) University of Illinois

Background/Question/Methods and Results/Conclusions

Terrestrial productivity is directly impacted by independent changes in atmospheric carbon dioxide, land cover and land use changes and increased nitrogen deposition. Less well understood are the interactive effects of these globally changing factors on terrestrial productivity and the resultant impact on rising atmospheric carbon dioxide concentrations. This study uses the Integrated Science Assessment Model (ISAM) to quantify the impacts of these multiple global changes on terrestrial productivity. The ISAM is modified to include a mechanistic model of leaf photosynthesis including the sensitivity of leaf photosynthesis to nitrogen availability. Leaf-level photosynthetic carbon gain is scaled to the canopy with a sun-shade microclimate model to estimate the gross primary productivity of 18 biomes comprised of representative plant functional types. The modified carbon-nitrogen cycling in the ISAM is coupled to a detailed model of biogeophysical processes and therefore providing the integrated modeling framework required to assess the interactive effects of rising carbon dioxide, climate and land cover and land use changes and nitrogen deposition on terrestrial productivity. The expanded ISAM modeling framework is evaluated with data from the Duke University and Oak Ridge National Laboratory free-air CO2 enrichment (FACE) experiments. These data comprises measurements of fluxes of carbon, nitrogen, water in an hourly time step for a long time period.  ISAM also has been evaluated against remote sensing data on vegetation productivity. The ISAM is able to reproduce the seasonality and magnitude of carbon, nitrogen, and water fluxes at DUKE and ORNL FACE sites. The distribution of net primary productivity on the global scale estimated by ISAM is also consistent with remote sensing data.