Based on research progress on economic value of ecosystem services, taking the plain afforestation data in Beijing as the study area, this paper explores the ecosystem service value evaluation of the 6.67×104 hm2 plain afforestation area. Shadow engineering method, opportunity cost method and opportunity cost method are used. The results show that, the total plain afforestation ecosystem service value is about 325.89×108Yuan. The importance of each ecological service function, in descending order: climate regulation function, air purification function, function of fixing carbon and releasing oxygen, solid soil fertilizer function, reduce the noise function, the function of water conservation. The results provide reference for further promoting the Beijing plain afforestation project construction and the ecological compensation policy and determine the ecological compensation standard.

Based on logarithmic mean weigh division index method (LMDI), empirical mode decomposition method (EMD) and variance decomposition model (VDM), the evolutive trend and fluctuation characteristics of corn production in China during 1978–2012 was analyzed. The contribution difference to corn output fluctuation during eight grain production regions was revealed. The following results were obtained. Corn output increased by 1.50×10⁸ ton from 1978 to 2012, and the corn production advantage in Huang-Huai-Hai region and Northeast Region in China was further highlighted. It was estimated that the accumulated contribution values of corn sowing area and corn yield per hectare at national scale were 0.79×10⁸ ton and 0.71×10⁸ ton respectively, and corn sowing area was the major contributor to the increment of corn output. The residual trend of corn output showed a trend of gradual increase and the grain output has 3-year periodic oscillation. During the eight grain production regions in China, Huang-Huai-Hai Region played the prominent role in the total fluctuation, following by the Northeast Region and Loess Plateau Region. The self-fluctuations in the three regions and their positively mutual affect were the main factors of China’s corn output fluctuation, including Huang-Huai-Hai Region, Northeast Region and Loess Plateau Region in China. For the high contribution ratio and drastic change, more attention should be paid to Huang-Huai-Hai Region and Northeast Region in China.

Based on the statistical data of 126 counties in Henan, using mathematical statistics method and spatial autocorrelation analysis, spatial changes and variation character of grain yield per hectare at county level in Henan Province during 1980?2012 are discussed by SPSS, ArcGIS and GeoDa software, and the increase potential of grain yield per hectare and total yield at regional scale are calculated. The results show that:1) During 1980?2012, grain yield per hectare and its absolute difference at county level take on increasing trend by and large, while the relative difference increases first and then decreases. The distributional pattern of grain yield per hectare changes from positive skewness to negative skewness, and the agglomeration degree of grain yield per hectare increases first and then decreases. 2) Grain yield per hectare at county level in Henan has a strong spatial autocorrelation with evident pattern “high in the eastern while low in the western”. The increment of grain yield per hectare descends from East to West at county level, and counties with higher increment of grain yield per hectare gather in the eastern plain area of Henan. 3) The changes of grain yield per hectare at county level show a positive spatial autocorrelation and the characteristic of spatial clustering of regional high value and low value is significant. The counties with “High-High” and “Low-Low” correlation are the majority. The counties with significant “High-High” correlation are mostly located in the eastern of Huang-Huai plain area and northwestern of the Hebei-Shandong-Henan low-lying plain area, while the counties with significant “Low-Low” correlation are mainly distributed in western Henan mountainous-hilly area and western of Huang-Huai plain area. 4) Henan Province is divided into 5 first-grade regions and 11 second-grade regions according to the coupled conditions of farming system regionalization and LISA cluster map. The potential output per hectare of the 5 first-grade regions could be sorted in descending order as hilly-mountainous region of Hubei-Henan-Anhui, piedmont region of Taihang mountain and Yanshan mountain, western Henan mountainous-hilly region, Huang-Huai plain region, and Hebei-Shandong-Henan low-lying plain region. The total potential output of Henan Province is 1.27×10⁷ tons, and the 5 regions could be sorted as Huang-Huai plain area, hilly-mountainous region of Hubei-Henan-Anhui, piedmont region of Taihang mountain and Yanshan mountain, western Henan mountainous-hilly region, and Hebei-Shandong-Henan low-lying plain region.