scholarly journals A global soil data set for earth system modeling

2014 ◽  
Vol 6 (1) ◽  
pp. 249-263 ◽  
Author(s):  
Wei Shangguan ◽  
Yongjiu Dai ◽  
Qingyun Duan ◽  
Baoyuan Liu ◽  
Hua Yuan
2017 ◽  
Vol 9 (2) ◽  
pp. 545-556 ◽  
Author(s):  
Guangsheng Chen ◽  
Shufen Pan ◽  
Daniel J. Hayes ◽  
Hanqin Tian

Abstract. Plantation forest area in the conterminous United States (CONUS) ranked second among the world's nations in the land area apportioned to forest plantation. As compared to the naturally regenerated forests, plantation forests demonstrate significant differences in biophysical characteristics, and biogeochemical and hydrological cycles as a result of more intensive management practices. Inventory data have been reported for multiple time periods on plot, state, and regional scales across the CONUS, but the requisite annual and spatially explicit plantation data set over a long-term period for analysis of the role of plantation management on regional or national scales is lacking. Through synthesis of multiple inventory data sources, this study developed methods to spatialize the time series plantation forest and tree species distribution data for the CONUS over the 1928–2012 time period. According to this new data set, plantation forest area increased from near zero in the 1930s to 268.27 thousand km2 in 2012, accounting for 8.65 % of the total forestland area in the CONUS. Regionally, the South contained the highest proportion of plantation forests, accounting for about 19.34 % of total forestland area in 2012. This time series and gridded data set developed here can be readily applied in regional Earth system modeling frameworks for assessing the impacts of plantation management practices on forest productivity, carbon and nitrogen stocks, and greenhouse gases (e.g., CO2, CH4, and N2O) and water fluxes on regional or national scales. The gridded plantation distribution and tree species maps, and the interpolated state-level annual tree planting area and plantation area during 1928–2012, are available from https://doi.org/10.1594/PANGAEA.873558.


2018 ◽  
Author(s):  
Yongjiu Dai ◽  
Wei Shangguan ◽  
Dagang Wang ◽  
Nan Wei ◽  
Qinchuan Xin ◽  
...  

Abstract. Global soil dataset is a pillar to the challenge of earth system modeling. But it is one of the most important uncertainty sources for Earth System Models (ESMs). Soil datasets function as model parameters, initial variables and benchmark datasets for model calibration, validation and comparison. For modeling use, the dataset should be geographically continuous, scalable and with uncertainty estimates. The popular soil datasets used in ESMs are often based on limited soil profiles and coarse resolution soil maps. Updated and comprehensive soil information needs to be incorporated in ESMs. New generation soil datasets derived by digital soil mapping with abundant soil observations and environmental covariates are preferred to those by the linkage method for ESMs. Because there is no universal pedotransfer function, an ensemble of them may be more suitable to provide secondary soil parameters to ESMs. Aggregation and upscaling of soil data are needed for model use but can be avoid by taking a subgrid method in ESMs at the cost of increases in model complexity. Uncertainty of soil data needs to be incorporated in ESMs.


Eos ◽  
2007 ◽  
Vol 88 (12) ◽  
pp. 143 ◽  
Author(s):  
Sophie Valcke ◽  
Reinhard Budich ◽  
Mick Carter ◽  
Eric Guilyardi ◽  
Marie-Alice Foujols ◽  
...  

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