Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning.

Annual gross primary productivity (AGPP) is the basis for grain production and terrestrial carbon sequestration. Mapping regional AGPP from site measurements provides methodological support for analysing AGPP spatiotemporal variations thereby ensures regional food security and mitigates climate change. Based on 641 site-year eddy covariance measuring AGPP from China, we built an AGPP mapping scheme based on its formation and selected the optimal mapping way, which was conducted through analysing the predicting performances of divergent mapping tools, variable combinations, and mapping approaches in predicting observed AGPP variations.

[Profile distribution and storage of soil organic carbon in a black soil as affected by land use types].

Taking soils in a long-term experimental field over 29 years with different land uses types, including arable land, bare land, grassland and larch forest land as test materials, the distribution and storage of soil organic carbon (SOC) in the profile (0-200 cm) in typical black soil (Mollisol) region of China were investigated. The results showed that the most significant differences in SOC content occurred in the 0-10 cm surface soil layer among all soils with the order of grassland > arable land > larch forest land > bare land. SOC contents at 10-120 cm depth were lower in arable land as compared with the other land use types.

Change in soil organic carbon between 1981 and 2011 in croplands of Heilongjiang Province, northeast China.

Background: Soil organic carbon (SOC) is fundamental for mitigating climate change as well as improving soil fertility. Databases of SOC obtained from soil surveys in 1981 and 2011 were used to assess SOC change (0-20 cm) in croplands of Heilongjiang Province in northeast China. Three counties (Lindian, Hailun and Baoqing) were selected as typical croplands representing major soil types and land use types in the region.