The impacts of climate change on rice yield in China from 1961 to 2010 were studied in this paper, based on the provincial data, in order to develop scientiifc countermeasures. The results indicated that increase of average temperature improved single cropping rice production on national level by up to 11%relative to the average over the study period, however, it resulted in an overall loss of double cropping rice by up to 1.9%. The decrease of diurnal temperature range （DTR） in the major producing regions caused the decrease by up to 3.0%for single cropping rice production and 2.0%for double cropping rice production. Moreover, the contribution of precipitation change reached about 6.2%for single cropping rice production, but no signiifcant effect for double cropping rice production in recent 50 years.
Accurate evaluation of dark respiration of plants is important for estimation of the plant carbon budget.The response of leaf dark respiration of winter wheat to changes in CO 2 concentration and temperature was studied,using an open top chamber during 2011-2012,to understand how leaf dark respiration of winter wheat will respond to climate change.The results indicated that leaf dark respiration decreased linearly with increased CO2 concentration.Dark respiration decreased by about 11% under 560 μmol mol-1 CO2 compared with that under 390 μmol mol-1 CO2.Leaf dark respiration showed an exponential relationship with temperature,and the temperature constant(Q10) was close to 2.Moreover,the responses of leaf dark respiration to CO concentration and temperature were independent.A leaf dark respiration model based on CO2 concentration and temperature responses was developed.This model provides a method for estimation of the leaf dark respiration rate of winter wheat under future climate change and guidance for establishment of crop carbon countermeasures.
Accurate estimation of non-photosynthetic biomass is critical for modeling carbon dynamics within grassland ecosystems.We evaluated the cellulose absorption index(CAI),widely used for monitoring non-photosynthetic vegetation coverage,for non-photosynthetic biomass estimation.Our analysis was based on in situ hyperspectral measurements,during the growing seasons of 2009 and 2010,in the desert steppe of Inner Mongolia.ASD(Analytical Spectral Device)-derived and Hyperion-derived CAI were found to be effective for non-photosynthetic biomass estimation,yielding relative error(RE) values of 26.4% and 26.6%,respectively.The combination of MODIS(Moderate Resolution Imaging Spectroradiometer)-derived(MODIS2 MODIS5)/(MODIS2 +MODIS5) and(MODIS6 MODIS7)/(MODIS6 +MODIS7) showed a high multiple correlation(multiple correlation coefficient,r=0.884) with ASD-derived CAI.A predictive model involving the two MODIS indices gave greater accuracy(RE=28.9%) than the TM(Landsat Thematic Mapper)-derived indices.The latter were the normalized difference index(NDI),the soil adjusted corn residue index(SACRI),and the modified soil adjusted crop residue index(MSACRI).These indices yielded RE values of more than 42%.Our conclusions have great significance for the estimation of regional non-photosynthetic biomass in grasslands,based on remotely sensed data.
