基于统计模型识别气候变化对农业产量贡献的研究进展(英文)

编号 zgly0001585255

文献类型 期刊论文

文献题名 基于统计模型识别气候变化对农业产量贡献的研究进展(英文)

作者 史文娇  陶福禄  张朝 

作者单位 StateKeyLaboratoryofEarthSurfaceProcessesandResourceEcology  BeijingNormalUniversity  InstituteofGeographicSciencesandNaturalResourcesResearch  CAS 

母体文献 Journal of Geographical Sciences 

年卷期 2013年03期

年份 2013 

分类号 S162 

关键词 climatechange  cropyield  influence  adaptation  statisticalmodel 

文摘内容 Statistical models using historical data on crop yields and weather to calibrate relatively simple regression equations have been widely and extensively applied in previous studies, and have provided a common alternative to process-based models, which require extensive input data on cultivar, management, and soil conditions. However, very few studies had been conducted to review systematically the previous statistical models for indentifying climate contributions to crop yields. This paper introduces three main statistical methods, i.e., time-series model, cross-section model and panel model, which have been used to identify such issues in the field of agrometeorology. Generally, research spatial scale could be categorized into two types using statistical models, including site scale and regional scale (e.g. global scale, national scale, provincial scale and county scale). Four issues exist in identifying response sensitivity of crop yields to climate change by statistical models. The issues include the extent of spatial and temporal scale, non-climatic trend removal, colinearity existing in climate variables and non-consideration of adaptations. Respective resolutions for the above four issues have been put forward in the section of perspective on the future of statistical models finally.