【目的】马铃薯作为中国第四大主粮作物,其适宜性评价对保障国家粮食安全具有重要意义。本研究基于气候数据,构建集成物种分布模型预测中国未来时期马铃薯气候适宜区,为优化中国马铃薯种植提供重要科学参考。【方法】利用6种全球气候模...【目的】马铃薯作为中国第四大主粮作物,其适宜性评价对保障国家粮食安全具有重要意义。本研究基于气候数据,构建集成物种分布模型预测中国未来时期马铃薯气候适宜区,为优化中国马铃薯种植提供重要科学参考。【方法】利用6种全球气候模式(global climate models,GCMs)未来气候数据驱动5种物种分布模型(species distribution models,SDMs),集成模拟预测未来4种温室气体排放情景(ssp126、ssp245、ssp370、ssp585)下,中国历史上(1970—2000年)和4个未来时期(2021—2040、2041—2060、2061—2080、2081—2100年)的马铃薯气候适宜区时空分布特征。【结果】(1)最湿月份的降水量、最暖月份的最高温度,以及最冷季度的平均温度是影响中国马铃薯气候适宜度的主要气象因子,对模拟结果的贡献率分别为54.7%、21.4%和18.1%。(2)4种温室气体排放情景下对于各适宜等级区域的预测结果变化基本一致,都呈现适宜区、低适宜区面积变大而高适宜区面积变小的趋势,仅在海南、西藏、新疆等地局部存在种植气候不适宜区。马铃薯适宜种植区(适宜区和高适宜区)的面积在各种情况下均超过50%。(3)在未来各时期马铃薯种植低适宜区和适宜区面积将大幅增加,而高适宜区面积则呈下降趋势,各适宜等级区域面积总体依旧保持:适宜区>低适宜区>高适宜区。(4)随着温室气体排放等级的提高,中国马铃薯高适宜区将大幅减小。从空间分布上看,中国马铃薯种植高适宜区主要以东北地区、甘肃地区、新疆西部,以及西南部分区域为主;从时间顺序上看,陕西北部、长江中下游区域、内蒙古中西部等区域受未来气候变化影响较大,马铃薯气候适宜度减小趋势明显。【结论】利用构建的集成物种分布模型预测了未来时期中国马铃薯气候适宜区时空分布特征。根据模型模拟结果,建议东北、甘肃、西南等地区可以作为未来马铃薯的主要种植区域,新疆等地区可以作为主要发展区域,其他地区应按照当地情况优先发展其他粮食和经济作物。展开更多
Data assimilation is extensively applied in agricultural remote sensing application.However,integration of multi-temporal and high spatial resolution images with crop growth model to evaluate the effect of cold damage...Data assimilation is extensively applied in agricultural remote sensing application.However,integration of multi-temporal and high spatial resolution images with crop growth model to evaluate the effect of cold damage on paddy rice was still lacking.In this paper,authors applied data assimilation combining LANDSAT/TM,a series of terra MODIS images with SIMRIW model to detect how cold damage affected paddy rice yield per unit in the Wuchang county,Heilongjiang province for the year 2006.In the study,MODIS images selected corresponding to a series of the key rice growth phases were utilized to retrieve daily LAI values that were needed in the SIMRIW model.Meanwhile,TM was applied to accurately extract paddy rice sown areas.The study results showed that the yield per unit was 10,628.5840 kg/ha under cold damage condition,which was little less than 10,768.3210 kg/ha under optimal condition.Moreover,the ratio of the calculated yield per value under cold damage condition to the actual value of paddy rice yield per unit was 0.56.The result was better than that acquired in USA and Japan.The results of this study expected to provide suggestions to policy-makers and reference to related research.展开更多
文摘【目的】马铃薯作为中国第四大主粮作物,其适宜性评价对保障国家粮食安全具有重要意义。本研究基于气候数据,构建集成物种分布模型预测中国未来时期马铃薯气候适宜区,为优化中国马铃薯种植提供重要科学参考。【方法】利用6种全球气候模式(global climate models,GCMs)未来气候数据驱动5种物种分布模型(species distribution models,SDMs),集成模拟预测未来4种温室气体排放情景(ssp126、ssp245、ssp370、ssp585)下,中国历史上(1970—2000年)和4个未来时期(2021—2040、2041—2060、2061—2080、2081—2100年)的马铃薯气候适宜区时空分布特征。【结果】(1)最湿月份的降水量、最暖月份的最高温度,以及最冷季度的平均温度是影响中国马铃薯气候适宜度的主要气象因子,对模拟结果的贡献率分别为54.7%、21.4%和18.1%。(2)4种温室气体排放情景下对于各适宜等级区域的预测结果变化基本一致,都呈现适宜区、低适宜区面积变大而高适宜区面积变小的趋势,仅在海南、西藏、新疆等地局部存在种植气候不适宜区。马铃薯适宜种植区(适宜区和高适宜区)的面积在各种情况下均超过50%。(3)在未来各时期马铃薯种植低适宜区和适宜区面积将大幅增加,而高适宜区面积则呈下降趋势,各适宜等级区域面积总体依旧保持:适宜区>低适宜区>高适宜区。(4)随着温室气体排放等级的提高,中国马铃薯高适宜区将大幅减小。从空间分布上看,中国马铃薯种植高适宜区主要以东北地区、甘肃地区、新疆西部,以及西南部分区域为主;从时间顺序上看,陕西北部、长江中下游区域、内蒙古中西部等区域受未来气候变化影响较大,马铃薯气候适宜度减小趋势明显。【结论】利用构建的集成物种分布模型预测了未来时期中国马铃薯气候适宜区时空分布特征。根据模型模拟结果,建议东北、甘肃、西南等地区可以作为未来马铃薯的主要种植区域,新疆等地区可以作为主要发展区域,其他地区应按照当地情况优先发展其他粮食和经济作物。
基金sponsored by the Major Program of National Natural Science Foundation of China(40930101)Key Laboratory of Resources Remote Sensing and Digital Agriculture of Chinese Ministry of Agriculture(RDA0910)+2 种基金the Commonweal Foundation of China’s National Academy(200990124)the Commonweal Foundation of China’s National Academy(2010002-2)National Technology Introduction Program of China(948program,2009-Z31)。
文摘Data assimilation is extensively applied in agricultural remote sensing application.However,integration of multi-temporal and high spatial resolution images with crop growth model to evaluate the effect of cold damage on paddy rice was still lacking.In this paper,authors applied data assimilation combining LANDSAT/TM,a series of terra MODIS images with SIMRIW model to detect how cold damage affected paddy rice yield per unit in the Wuchang county,Heilongjiang province for the year 2006.In the study,MODIS images selected corresponding to a series of the key rice growth phases were utilized to retrieve daily LAI values that were needed in the SIMRIW model.Meanwhile,TM was applied to accurately extract paddy rice sown areas.The study results showed that the yield per unit was 10,628.5840 kg/ha under cold damage condition,which was little less than 10,768.3210 kg/ha under optimal condition.Moreover,the ratio of the calculated yield per value under cold damage condition to the actual value of paddy rice yield per unit was 0.56.The result was better than that acquired in USA and Japan.The results of this study expected to provide suggestions to policy-makers and reference to related research.
