Predicting and delineating soil temperature regimes of China using pedotransfer function

Soil temperature regime(STR)is important for soil classification and land use.Generally,STR is delineated by estimating the mean annual soil temperature at a depth of 50 cm(MAST50)according to the Chinese Soil Taxonomy(CST).However,delineating the STR of China remains a challenge due to the difficulties in accurately estimating MAST50.The objectives of this study were to explore environmental factors that influence the spatial variation of MAST50 and generate an STR map for China.Soil temperature measurements at 40 and 80 cm depth were collected from 386 National Meteorological Stations in China during 1971–2000.The MAST50 was calculated as the average mean annual soil temperature(MAST)from 1971–2000 between 40 and 80 cm depths.In addition,2048 mean annual air temperature(MAAT)measurements from 1971 to 2000 were collected from the National Meteorological Stations across China.A zonal pedotransfer function(PTF)was developed based on the ensemble linear regression kriging model to predict the MAST50 in three topographic steps of China.The results showed that MAAT was the most important variable related to the variation of MAST50.The zonal PTF was evaluated with a 10%validation dataset with a mean absolute error(MAE)of 0.66°C and root mean square error(RMSE)of 0.78°C,which were smaller than the unified model with MAE of 0.83°C and RMSE of 0.96°C,respectively.This study demonstrated that the zonal PTF helped improve the accuracy of the predicted MAST50 map.Based on the prediction results,an STR map across China was generated to provide a consistent scientific base for the improvement and application of CST and land use support.

Response of soil CO_2 efflux to precipitation manipulation in a semiarid grassland

Soil CO_2efflux（SCE） is an important component of ecosystem CO_2 exchange and is largely temperature and moisture dependent, providing feedback between C cycling and the climate system. We used a precipitation manipulation experiment to examine the effects of precipitation treatment on SCE and its dependences on soil temperature and moisture in a semiarid grassland. Precipitation manipulation included ambient precipitation, decreased precipitation（- 43%）, or increased precipitation（＋ 17%）. The SCE was measured from July2013 to December 2014, and CO_2 emission during the experimental period was assessed.The response curves of SCE to soil temperature and moisture were analyzed to determine whether the dependence of SCE on soil temperature or moisture varied with precipitation manipulation. The SCE significantly varied seasonally but was not affected by precipitation treatments regardless of season. Increasing precipitation resulted in an upward shift of SCE–temperature response curves and rightward shift of SCE–moisture response curves,while decreasing precipitation resulted in opposite shifts of such response curves. These shifts in the SCE response curves suggested that increasing precipitation strengthened the dependence of SCE on temperature or moisture, and decreasing precipitation weakened such dependences. Such shifts affected the predictions in soil CO_2 emissions for different precipitation treatments. When considering such shifts, decreasing or increasing precipitation resulted in 43 or 75% less change, respectively, in CO_2 emission compared with changes in emissions predicted without considering such shifts. Furthermore, the effects of shifts in SCE response curves on CO_2 emission prediction were greater during the growing than the non-growing season.