利用最大熵和CARAH模型评估重庆春马铃薯晚疫病气候风险
基于 2019-2023 年 2-6 月重庆市 260 个地面气象观测站逐小时平均气温、平均相对湿度数据,利用CARAH 晚疫病模型模拟重庆春马铃薯晚疫病侵染风险的空间分布,通过气候网格数据构建最大熵模型,筛选马铃薯晚疫病气候影响因子,评估春马铃薯晚疫病气候风险,为春马铃薯晚疫病预测与科学防控提供参考依据.结果表明:基于CARAH模型采用小时级气象数据模拟晚疫病侵染的准确性较高,空发生率为 12.5%,漏发生率为 18.5%,TS评分为 0.73.降水量是影响重庆春马铃薯晚疫病风险分布的主导因子,相对湿度和气温是重要因子,其幼苗期、现蕾开花期气候变量对晚疫病风险的影响较大.各马铃薯熟性(早/晚...
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| Published in | 中国农业气象 Vol. 45; no. 9; pp. 984 - 997 |
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| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
南方丘区节水农业研究四川省重点实验室,成都 610072%四川省农村经济综合信息中心,成都 610072%中国气象局气候资源经济转化重点开放实验室,重庆 401147
20.09.2024
中国气象局气候资源经济转化重点开放实验室,重庆 401147 重庆市气象服务中心,重庆 401147%重庆市江津现代农业气象试验站,重庆 402260%重庆市气象科学研究所,重庆 401147 重庆市气象科学研究所,重庆 401147%四川省农业气象中心,成都 610072 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-6362 |
| DOI | 10.3969/j.issn.1000-6362.2024.09.004 |
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| Abstract | 基于 2019-2023 年 2-6 月重庆市 260 个地面气象观测站逐小时平均气温、平均相对湿度数据,利用CARAH 晚疫病模型模拟重庆春马铃薯晚疫病侵染风险的空间分布,通过气候网格数据构建最大熵模型,筛选马铃薯晚疫病气候影响因子,评估春马铃薯晚疫病气候风险,为春马铃薯晚疫病预测与科学防控提供参考依据.结果表明:基于CARAH模型采用小时级气象数据模拟晚疫病侵染的准确性较高,空发生率为 12.5%,漏发生率为 18.5%,TS评分为 0.73.降水量是影响重庆春马铃薯晚疫病风险分布的主导因子,相对湿度和气温是重要因子,其幼苗期、现蕾开花期气候变量对晚疫病风险的影响较大.各马铃薯熟性(早/晚)与感病性(抗病/感病)组合的晚疫病低风险区面积少于或接近 1 万km2,平均面积占比为 10.2%,中风险区和高风险区面积均超过 3 万km2,平均面积占比分别为 43.7%和 46.1%.重庆春马铃薯晚疫病气候风险呈中间高、周边低的空间分布特征,高风险区集中于重庆的川东平行岭谷地区,中风险区主要分布于渝东北大巴山区、渝东南武陵山区以及渝西川中丘陵一带,低风险区多呈片状分散在重庆边缘地带.重庆春马铃薯生产面临较高的晚疫病气候风险,空间分异特征显著,应通过合理生产布局和改进栽培技术加以应对. |
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| AbstractList | 基于 2019-2023 年 2-6 月重庆市 260 个地面气象观测站逐小时平均气温、平均相对湿度数据,利用CARAH 晚疫病模型模拟重庆春马铃薯晚疫病侵染风险的空间分布,通过气候网格数据构建最大熵模型,筛选马铃薯晚疫病气候影响因子,评估春马铃薯晚疫病气候风险,为春马铃薯晚疫病预测与科学防控提供参考依据.结果表明:基于CARAH模型采用小时级气象数据模拟晚疫病侵染的准确性较高,空发生率为 12.5%,漏发生率为 18.5%,TS评分为 0.73.降水量是影响重庆春马铃薯晚疫病风险分布的主导因子,相对湿度和气温是重要因子,其幼苗期、现蕾开花期气候变量对晚疫病风险的影响较大.各马铃薯熟性(早/晚)与感病性(抗病/感病)组合的晚疫病低风险区面积少于或接近 1 万km2,平均面积占比为 10.2%,中风险区和高风险区面积均超过 3 万km2,平均面积占比分别为 43.7%和 46.1%.重庆春马铃薯晚疫病气候风险呈中间高、周边低的空间分布特征,高风险区集中于重庆的川东平行岭谷地区,中风险区主要分布于渝东北大巴山区、渝东南武陵山区以及渝西川中丘陵一带,低风险区多呈片状分散在重庆边缘地带.重庆春马铃薯生产面临较高的晚疫病气候风险,空间分异特征显著,应通过合理生产布局和改进栽培技术加以应对. |
| Abstract_FL | The hourly average temperature and average relative humidity data of 260 meteorological stations in Chongqing from February to June in 2019-2023 were used to simulate the geographic distribution of spring potato late blight infection risk using the CARAH late blight model.The accuracy of the simulation was tested by using the late blight infection data of 26 monitoring stations in Wuxi county,Chongqing in 2022.Based on the geographic distribution of spring potato late blight infection risk simulated,the maximum entropy model was constructed using the climate grid data of the monthly average temperature,maximum temperature,minimum temperature,water vapor pressure and precipitation from February to June in 1970-2000 to analyze the climate impact factors of spring potato late blight in Chongqing,and to evaluate the climate risk of spring potato late blight,providing a reference for the prediction and scientific prevention of the disease.The results showed that simulations of late blight infection based on hourly weather data had high accuracy,with a false positive rate of 12.5%,false negative rate of 18.5%and TS score of 0.73.The mean area under curve(AUC)of the receiver operating characteristic(ROC)was above 0.9,indicating higher accuracy of the simulation results.Precipitation was the dominant climate factor affecting the risk distribution of late blight of spring potato in Chongqing,while relative humidity and temperature were important climate factors.Climate variables at the seedling stage and bud flowering stage had a great impact on the distribution of late blight risk.The low risk area of late blight of each maturity(early/late)and susceptibility(resistant/susceptible)combination of spring potato was less than or close to 10000km2,with an average area proportion of 10.2%.The medium risk area and high risk area were both more than 30000km2,with an average area proportion of 43.7%and 46.1%,respectively.The climate risk of spring potato late blight showed a spatial distribution characteristic of"high in the middle and low in the periphery"in Chongqing.The high risk area was concentrated in the parallel valley area in eastern Sichuan,the medium risk area was mainly distributed in Daba mountain area in northeast Chongqing,Wuling mountain area in southeast Chongqing,and the hilly area in central Sichuan in west Chongqing,and the low risk area was scattered in the fringe of Chongqing.Spring potato production in Chongqing area faces a high climate risk of late blight,with significant spatial differentiation characteristics.It should be addressed through reasonable production layout and improved cultivation techniques. |
| Author | 唐余学 陈东东 阳园燕 韩旭 王茹琳 陈欢 朱玉涵 张悦 罗孳孳 |
| AuthorAffiliation | 中国气象局气候资源经济转化重点开放实验室,重庆 401147;重庆市气象科学研究所,重庆 401147%四川省农业气象中心,成都 610072;南方丘区节水农业研究四川省重点实验室,成都 610072%四川省农村经济综合信息中心,成都 610072%中国气象局气候资源经济转化重点开放实验室,重庆 401147;重庆市气象服务中心,重庆 401147%重庆市江津现代农业气象试验站,重庆 402260%重庆市气象科学研究所,重庆 401147 |
| AuthorAffiliation_xml | – name: 中国气象局气候资源经济转化重点开放实验室,重庆 401147;重庆市气象科学研究所,重庆 401147%四川省农业气象中心,成都 610072;南方丘区节水农业研究四川省重点实验室,成都 610072%四川省农村经济综合信息中心,成都 610072%中国气象局气候资源经济转化重点开放实验室,重庆 401147;重庆市气象服务中心,重庆 401147%重庆市江津现代农业气象试验站,重庆 402260%重庆市气象科学研究所,重庆 401147 |
| Author_FL | LUO Zi-zi WANG Ru-lin CHEN Dong-dong CHEN Huan TANG Yu-xue HAN Xu YANG Yuan-yan ZHANG Yue ZHU Yu-han |
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| DocumentTitle_FL | Evaluating of Spring Potato Late Blight Climate Risk Based on MaxEnt and CARAH Model in Chongqing |
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| Keywords | 气候风险 MaxEnt model Climate risk 最大熵模型MaxEnt CARAH model 马铃薯晚疫病 CARAH模型 Potato late blight |
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| Title | 利用最大熵和CARAH模型评估重庆春马铃薯晚疫病气候风险 |
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