关键词: 非期望产出DEA模型, 节能减碳效率, CO₂, 辽宁省

Abstract: Drought can substantially alter composition, structure and function of terrestrial ecosystems, and thus significantly affects terrestrial carbon cycle. Gross primary production (GPP), reflecting the productivity level of terrestrial ecosystems, is the largest component of the global terrestrial carbon fluxes. Here, we investigated the spatiotemporal patterns of GPP and drought in China during 1980-2013 and quantitatively analyzed the responses of GPP to drought at different temporal scales. Processbased model (DLM GPP) and eddy-covariance flux tower measurements (FLUXCOM GPP) were used to simulate GPP, while a drought index (standardized precipitation evapotranspiration index, SPEI) was employed to reflect the intensity of drought. The results showed that the two GPP estimates had similar spatio temporal patterns, characterized by increasing trends in southwest China but decreasing trends in most of areas in northeast China. Overall, there was a slight decrease in droughtimpacted areas in China, with most significant decrease in northwest inland. However, the south of Qinling Mountains-Huaihe River was becoming drier. The temporal variation of the two GPP estimates were generally consistent with SPEI, and displayed significant decreases in 1986, 1997, 2001 and 2011 due to severe drought events in these years. At the spatial scale, GPP estimates were correlated positively with SPEI in most regions of northern China, but they were negatively correlated in many areas of southern China. The effects of drought on GPP were more obvious in the semiarid regions. The responses of GPP to drought were closely related to temporal scales of drought index. There were differences in the drought response and sensitivity of GPP estimated by the two models. Therefore, to get a more accurate estimation of GPP, there is an urgent need to improve the current GPP models and establish more flux observation sites.

Key words: Liaoning Province., CO₂, undesirable output DEA model, energy saving and carbon emission reduction efficiency