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IBIS model and its use to simulate trends for the Qinghai-Tibetan Plateau
The Integrated Biosphere Simulator (IBIS) is designed to integrate a variety of
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terrestrial ecosystem processes within a single, physically consistent modeling framework
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(Coe et al., 2002). It represents land surface processes, canopy physiology, vegetation
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phenology, long-term vegetation dynamics, and carbon cycling (Coe et al., 2002, Foley et
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al., 1996, Kucharik et al., 2000). The hydrological module of IBIS is based on a land-
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surface-transfer scheme (Thompson & Pollard, 1995a, Thompson & Pollard, 1995b).
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Two canopy layers, three snow layers, and six soil layers are considered in each cell of
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the landscape grid. IBIS represents natural vegetation using plant functional types (PFTs),
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each of which is characterized in terms of its biomass and leaf area index. For each PFT,
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IBIS adopts a mechanistic treatment of canopy photosynthesis based on the methods of
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Farquhar et al. (1980) and Farquhar and Sharkey (1982), and uses a semi-mechanistic
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model of stomatal conductance (Ball et al., 1986, Foley et al., 1996, Kucharik et al., 2000)
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to quantify the gross primary productivity. A dynamic vegetation mechanism is adopted
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to simulate changes in the vegetation structure on an annual time step as a result of
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competition among PFTs for light and water from common resource pools (Kucharik et
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al., 2006). The competition between PFTs depends on differences in resource availability,
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carbon allocation, vegetation phenology, leaf form, and photosynthetic pathway (Foley et
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al., 1996, Kucharik et al., 2000).
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The variations of net primary production, soil respiration, and net ecosystem
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production on the Qinghai-Tibetan Plateau that were simulated in this study were
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extracted from a country-scale simulation of China created using IBIS (Zhu et al., 2012).
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A 0.085°resolution land mask map of China was used in the IBIS simulations. The map
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excluded bodies of water and some areas for which soil information was unavailable. A
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hole-filled version of the Shuttle Radar Topography Mission digital elevation model
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dataset (Jarvis et al., 2006) for China was re-sampled to 0.085° resolution and used as the
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input topographic data. A 1:1 000 000 China soil map provided the fractions of sand, clay,
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and silt particles for each soil layer and each cell (Shi et al., 2004). The 1:4 000 000
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China vegetation map was reclassified into IBIS-specific vegetation types to initialize the
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simulation (Hou et al., 1979). A 1-km-resolution land cover map of China from 2000
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(Data Center for Resources and Environmental Sciences Chinese Academy of Sciences
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(RESDC), 2001) was used to construct a vegetation cover layer for each cell in the grid,
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allowing a detailed representation of the current land use and land cover conditions in the
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simulation. These data are resampled to the resolution of 0.085°.
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Two projected future climate datasets under the IPCC SRES scenarios (A2 and B1)
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(IPCC, 2007) were selected from the third version of the Canadian Centre for Climate
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Modeling and Analysis Coupled Global Climate Model (CGCM3.1). Emission scenarios
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SRES A2 and SRES B1 represent high and low greenhouse gas emission levels,
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respectively, in this study. Averaged observed meteorological data based on more than
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650 stations obtained from Meteorological Bureau of China (precipitation, air
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temperature, relative humidity, and cloudiness fraction) from 1950 to 2006 were used as
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the baseline climate conditions. The relative climate forcing data were resampled to
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resolution of 0.085° using thin spline interpolation methods. The CO2 concentration was
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defined for each year of the simulation using the values in the SRES A2 and SRES B1
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scenarios. In 2100, the CO2 concentration is projected to increase to 836 ppmv under
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scenario SRES A2 and to 540 ppmv under scenario SRES B1 (IPCC, 2001). Simulations
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were performed using the abovementioned soil texture data, initial vegetation conditions,
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and projected climate data. The simulation results from 1960 to 2100 were then selected
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for analysis.
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Validation of IBIS in China and on the Qinghai-Tibetan Plateau
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From our previous studies using IBIS in China, simulated runoff captured the
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quantity pattern quite well; the simulated ET matched reasonably with estimated ET that
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is calculated as the residual of observed precipitation and runoff (Zhu et al., 2010b).
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Comparison between the observed and simulated soil moisture showed that mean errors
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are within 10% for all the months and root mean squared errors are within 10% for most
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of the seasons (Zhu et al., 2009). Validation for soil temperature simulation based on 650
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stations observed data (from 1955 to 2000) shows that IBIS model performs well in
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capturing spatial and temporal patterns of soil temperature (Zhu et al., 2010a). Validation
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and comparison showed reasonable agreement for variables related to carbon exchange
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processes using forestry inventory data (for net primary productivity and biomass
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validation), flux site data (for gross primary productivity validation), and literature
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reported data (for net primary productivity and biomass validation) at regional (Zhu et al.,
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2011a) and national (Zhu et al., 2011b) scales.
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The simulated annual NPP of QTP was compared with the MODIS NPP product,
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based on the multi-year average from 2000 to 2010. The 1 km MODIS NPP (MOD17A3;
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collection 5) was obtained from the Numerical Terradynamic Simulation Group
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(www.ntsg.umt.edu) (Zhao & Running, 2010, Zhao et al., 2005). Nearly 2000 random
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points were generated on QTP to extract the corresponding values from the NPP layers of
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simulated and MODIS product. The compared scatter plot is shown as Appendix Figure 1,
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which indicates quite reasonable modeled NPP using IBIS on QTP. The points marked by
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dashed circle, with the percentage of 7.5% of all the points, showed the NPP was
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underestimated by the model. However, most of the comparing scattered points (92.5%,
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marked by solid circle) were close to the 1:1 line, which indicted the model performed
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well.
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