The impact of climate change on agriculture has received wide attention by the scientific community. This paper studies how to assess the grain yield impact of climate change, according to the climate change over a lo...The impact of climate change on agriculture has received wide attention by the scientific community. This paper studies how to assess the grain yield impact of climate change, according to the climate change over a long time period in the future as predicted by a climate system model. The application of the concept of a traditional ＂yield impact of meteorological factor （YIMF）＂ or ＂yield impact of weather factor＂ to the grain yield assessment of a decadal or even a longer timescale would be suffocated at the outset because the YIMF is for studying the phenomenon on an interannual timescale, and it is difficult to distinguish between the trend caused by climate change and the one resulting from changes in non-climatic factors. Therefore, the concept of the yield impact of climatic change （YICC）, which is defined as the difference in the per unit area yields （PUAY） of a grain crop under a changing and an envisaged invariant climate conditions, is presented in this paper to assess the impact of global climate change on grain yields. The climatic factor has been introduced into the renowned economic Cobb-Douglas model, yielding a quantitative assessment method of YICC using real data. The method has been tested using the historical data of Northeast China, and the results show that it has an encouraging application outlook.展开更多
Objective:This study aimed to analyze the spatiotemporal characteristics of dengue fever in Yunnan Province and its relationship with meteorological factors.Methods:Circular and spatiotemporal scan analyses were perfo...Objective:This study aimed to analyze the spatiotemporal characteristics of dengue fever in Yunnan Province and its relationship with meteorological factors.Methods:Circular and spatiotemporal scan analyses were performed to investigate dengue fever,and a negative binomial regression model was used to estimate the impact of meteorological factors on the incidence of dengue fever.Results:The peak period of dengue fever cases in Yunnan Province was from August to October,with clustering observed in border prefectures.Conclusion:Dengue fever in Yunnan Province exhibited distinct spatiotemporal clustering and was significantly influenced by meteorological factors,particularly temperature and precipitation.These findings highlight the importance of multidimensional surveillance and early warning systems.展开更多
基金This work was supported by the National Natural Science Foundation of China under Grant No. 40231006 the National Key Program for Developing Basic Sciences under Grant No. 2006CB400503the Knowledge Innovation Project of the Chinese Academy of Science under Grant No. KZCX- SW-218.
文摘The impact of climate change on agriculture has received wide attention by the scientific community. This paper studies how to assess the grain yield impact of climate change, according to the climate change over a long time period in the future as predicted by a climate system model. The application of the concept of a traditional ＂yield impact of meteorological factor （YIMF）＂ or ＂yield impact of weather factor＂ to the grain yield assessment of a decadal or even a longer timescale would be suffocated at the outset because the YIMF is for studying the phenomenon on an interannual timescale, and it is difficult to distinguish between the trend caused by climate change and the one resulting from changes in non-climatic factors. Therefore, the concept of the yield impact of climatic change （YICC）, which is defined as the difference in the per unit area yields （PUAY） of a grain crop under a changing and an envisaged invariant climate conditions, is presented in this paper to assess the impact of global climate change on grain yields. The climatic factor has been introduced into the renowned economic Cobb-Douglas model, yielding a quantitative assessment method of YICC using real data. The method has been tested using the historical data of Northeast China, and the results show that it has an encouraging application outlook.
文摘Objective:This study aimed to analyze the spatiotemporal characteristics of dengue fever in Yunnan Province and its relationship with meteorological factors.Methods:Circular and spatiotemporal scan analyses were performed to investigate dengue fever,and a negative binomial regression model was used to estimate the impact of meteorological factors on the incidence of dengue fever.Results:The peak period of dengue fever cases in Yunnan Province was from August to October,with clustering observed in border prefectures.Conclusion:Dengue fever in Yunnan Province exhibited distinct spatiotemporal clustering and was significantly influenced by meteorological factors,particularly temperature and precipitation.These findings highlight the importance of multidimensional surveillance and early warning systems.
