Browsing by Author "Zhang, Shuxia"

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    Parallel Computing of Forest Biotic Dynamics
    (2012-06-13) Wythers, Kirk; Zhang, Shuxia; Reich, Peter; Peters, Emily
    This poster presents a parallel-computing framework developed recently through the collaborative efforts between the College of Food, Agricultural, and Natural Resource Sciences, the Institute of the Environment, and the Supercomputing Institute at the University of Minnesota. The goal of this project is to address the challenges encountered in the modeling of biotic dynamics in a forest region across different time and spatial scales. By implementing the parallel computing framework on Itasca, we have been able to reduce the computing time from 46 days (if the simulation runs on a single desktop) to half a day by using 8 nodes for a study of northern Minnesota, Wisconsin, and Michigan with 1 km grid resolution. This will allow us to attack computationally challenging problems, such as assessing the impact of critical events like the 1999 BWCA blowdown and finer resolution events such as controlled burns on future forest productivity and stability.
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    Potential climate change impacts on temperate forest ecosystem processes
    (NRC Research Press, 2013) Peters, Emily B; Wythers, Kirk R; Zhang, Shuxia; Bradford, John B; Reich, Peter B
    Large changes in atmospheric CO2, temperature, and precipitation are predicted by 2100, yet the long-term consequences for carbon (C), water, and nitrogen (N) cycling in forests are poorly understood. We applied the PnET-CN ecosystem model to compare the long-term effects of changing climate and atmospheric CO2 on productivity, evapotranspiration, runoff, and net nitrogen mineralization in current Great Lakes forest types. We used two statistically downscaled climate projections, PCM B1 (warmer and wetter) and GFDL A1FI (hotter and drier), to represent two potential future climate and atmospheric CO2 scenarios. To separate the effects of climate and CO2, we ran PnET-CN including and excluding the CO2 routine. Our results suggest that, with rising CO2 and without changes in forest type, average regional productivity could increase from 67% to 142%, changes in evapotranspiration could range from –3% to +6%, runoff could increase from 2% to 22%, and net N mineralization could increase 10% to 12%. Ecosystem responses varied geographically and by forest type. Increased productivity was almost entirely driven by CO2 fertilization effects, rather than by temperature or precipitation (model runs holding CO2 constant showed stable or declining productivity). The relative importance of edaphic and climatic spatial drivers of productivity varied over time, suggesting that productivity in Great Lakes forests may switch from being temperature- to water-limited by the end of the century.