Yang Z.,BeijingNormal University
Journal of Industrial Ecology | Year: 2016
Along with globalization, countries consume a large amount of goods and services from both domestic and international markets. As one of the world's largest agricultural countries, China is faced with serious water scarcity and has to reduce the water consumption from both domestic and global aspects, of which the crop planting structure optimization (CPSO) between regions based on the virtual water perspective could be a solution for efficient agricultural water consumption. In this article, three scenarios of Chinese agriculture, including agricultural water consumption restrictions relaxed scenario, agricultural water consumption limited scenario, and net utilization ratio of water resources limited scenario, were designed to minimize the national agricultural water consumption under various water, land, and crop planting constraints in individual provinces and analyze the impacts of the CPSO. The results showed that compared with the historical situation of crop planting in 2007, 53.3%, 51.4%, and 47.3% of the agricultural water consumption and more than 10% of the sown area of China was saved under the three scenarios, respectively. Because of the reduction of agricultural water consumption and land use, it brought about the expansion of crops production in China. CPSO is found to have notable effects on water saving and food security considering the dependence of the crops by international trade. © 2016, Yale University.
Wu S.,Harbin Normal University |
Yan X.,BeijingNormal University |
Zhang L.,Harbin Normal University
Acta Geographica Sinica | Year: 2014
In this study, with the help of emergy value theory and ecosystem service value theory, we established the function relationship between forest emergy value and ecosystem service value in China using the global temperature and precipitation data during 1901-2009 and 1266 sample forest data of major vegetation types in China. Results indicate that: there was a high consistency of the spatial distribution of the Chinese forest ecosystem service value in 1994 between the simulated results by the established function relationship and the evaluation results from Costanza. In particular, the raster number of forest areas in China increased by about 14.02% from 1990 to 2009, and the mean forest ecosystem service value density increased by about 54.46 USD/hm2. In addition, the mean forest ecosystem service value density for Beijing, Shanghai, Jiangsu, Tianjin, Hebei decreased by about 86.87%, 85.45%, 81.99%, 46.48% and 23.07%, respectively, and the mean ecosystem service value density for Henan, Hunan, Jilin, Jiangxi, Heilongjiang and Zhejiang decreased by about 71.35%, 58.65%, 52.70%, 34.56%, 23.36% and 22.03%, respectively. There was also a severe forest destruction in Guangxi, Tibet, Gansu, Inner Mongolia, Sichuan, Yunnan, and Ningxia, and the mean forest ecosystem service value density of those provinces decreased by about 2.89%-22.36%. According to the fourth and seventh National forest survey reports, the forest areas have continually increased in recent years. However, the reports show that the forest ecosystem service value density in several provinces have decreased, and indicate that the forest ecosystem has not been fully recovered. Generally speaking, the forest ecosystem service value is lower than the global average level, suggesting that the forest eco-environment is not good enough in China, and human activities have a tremendous negative impact on the ecosystem.
Hu X.,University of Electronic Science and Technology of China |
Zeng A.,BeijingNormal University |
Shang M.-S.,Chinese Academy of Sciences
European Physical Journal B | Year: 2016
Recommender system is an effective tool to find the most relevant information for onlineusers. By analyzing the historical selection records of users, recommender system predictsthe most likely future links in the user-item network and accordingly constructs apersonalized recommendation list for each user. So far, the recommendation process ismostly investigated in static user-item networks. In this paper, we propose a model whichallows us to examine the performance of the state-of-the-art recommendation algorithms inevolving networks. We find that the recommendation accuracy in general decreases with timeif the evolution of the online network fully depends on the recommendation. Interestingly,some randomness in users’ choice can significantly improve the long-term accuracy of therecommendation algorithm. When a hybrid recommendation algorithm is applied, we find thatthe optimal parameter gradually shifts towards the diversity-favoring recommendationalgorithm, indicating that recommendation diversity is essential to keep a high long-termrecommendation accuracy. Finally, we confirm our conclusions by studying therecommendation on networks with the real evolution data. © 2016, EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg.
Zhao N.N.,China Agricultural University |
Zhou L.,China Agricultural University |
Liu Z.L.,China Agricultural University |
Du S.S.,BeijingNormal University |
Deng Z.W.,BeijingNormal University
Food Control | Year: 2012
Fourteen essential oils of common spices in China were evaluated for insecticidal activities against the booklouse, Liposcelis bostrychophila. Five essential oils (Allium sativum, Cinnamomum cassia, Foeniculum vulgare, Illicium verum, and Perilla frutescens) exhibited strong contact toxicity against the booklice at a concentration of 0.16μL/cm 2 while only C. cassia, F. vulgare and P. frutescens essential oils possessed fumigant toxicity at a concentration of 0.04μL/L. Based on bioactivity-directed fractionation, estragole, trans-anethole and fenchone were isolated from the essential oil of F. vulgare. Estragole and trans-anethole exhibited contact toxicity against the booklouse with LD 50 values of 49.95μg/cm 2 and 57.98μg/cm 2, respectively while F. vulgare essential oil had an LD 50 value of 90.36μg/cm 2. trans-Anethole (LC 50=15.96μg/L) possessed stronger fumigant toxicity against the booklouse than fenchone (LC 50=73.23μg/L), estragole (LC 50=160.33μg/L) and the essential oil of F. vulgare (LC 50=34.07μg/L). © 2012 Elsevier Ltd.