中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 地理科学与资源研究所
  3. 中国科学院地理科学与资源研究所
Mapping the Spatio-Temporal Distribution of Fall Armyworm in China by Coupling Multi-Factors

文献类型：期刊论文

作者Huang, Yanru1,2,3; Lv, Hua4; Dong, Yingying1,2,3; Huang, Wenjiang1,2,3; Hu, Gao4; Liu, Yang5; Chen, Hui4; Geng, Yun1,2,3; Bai, Jie3,6; Guo, Peng7
刊名REMOTE SENSING
出版日期2022-09-01
卷号14期号:17页码:19
关键词fall armyworm dynamic distribution migration simulation maize phenology environmental suitability
DOI10.3390/rs14174415
通讯作者Huang, Wenjiang(huangwj@aircas.ac.cn)
英文摘要The fall armyworm (FAW) (Spodoptera frugiperda) (J. E. Smith) is a migratory pest that lacks diapause and has raised widespread concern in recent years due to its global dispersal and infestation. Seasonal environmental changes lead to its large-scale seasonal activities, and quantitative simulations of its dispersal patterns and spatiotemporal distribution facilitate integrated pest management. Based on remote sensing data and meteorological assimilation products, we constructed a mechanistic model of the dynamic distribution of FAW (FAW-DDM) by integrating weather-driven flight of FAW with host plant phenology and environmental suitability. The potential distribution of FAW in China from February to August 2020 was simulated. The results showed a significant linear relationship between the dates of the first simulated invasion and the first observed invasion of FAW in 125 cities (R-2 = 0.623; p < 0.001). From February to April, FAW was distributed in the Southwestern and Southern Mountain maize regions mainly due to environmental influences. From May to June, FAW spread rapidly, and reached the Huanghuaihai and North China maize regions between June to August. Our results can help in developing pest prevention and control strategies with data on specific times and locations, reducing the impact of FAW on food security.
WOS关键词SPODOPTERA-FRUGIPERDA ; MIGRATORY ROUTES ; TEMPERATURE ; LEPIDOPTERA ; MODEL ; NOCTUIDAE ; PHENOLOGY ; INSECTS ; PREDICTION ; FOREST
资助项目National Key R&D Program of China[2021YFE0194800] ; National Natural Science Foundation of China[42071320] ; International Partnership Program of Chinese Academy of Science[183611KYSB20200080] ; Alliance of International Science Organizations[ANSO-CR-KP-2021-06] ; SINO-EU, Dragon 5 proposal: Application of Sino-Eu Optical Data into Agronomic Models[57457]
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者MDPI
WOS记录号WOS:000851739000001
资助机构National Key R&D Program of China ; National Natural Science Foundation of China ; International Partnership Program of Chinese Academy of Science ; Alliance of International Science Organizations ; SINO-EU, Dragon 5 proposal: Application of Sino-Eu Optical Data into Agronomic Models
源URL[http://ir.igsnrr.ac.cn/handle/311030/182804]  
专题中国科学院地理科学与资源研究所
通讯作者Huang, Wenjiang
作者单位1.Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
2.Int Res Ctr Big Data Sustainable Dev Goals, Beijing 100094, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Nanjing Agr Univ, Coll Plant Protect, Nanjing 210095, Peoples R China
5.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China
6.Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
7.Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China
8.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714		 Huang, Yanru,Lv, Hua,Dong, Yingying,et al. Mapping the Spatio-Temporal Distribution of Fall Armyworm in China by Coupling Multi-Factors[J]. REMOTE SENSING,2022,14(17):19.
APA Huang, Yanru.,Lv, Hua.,Dong, Yingying.,Huang, Wenjiang.,Hu, Gao.,...&Cui, Yifeng.(2022).Mapping the Spatio-Temporal Distribution of Fall Armyworm in China by Coupling Multi-Factors.REMOTE SENSING,14(17),19.
MLA Huang, Yanru,et al."Mapping the Spatio-Temporal Distribution of Fall Armyworm in China by Coupling Multi-Factors".REMOTE SENSING 14.17(2022):19.

入库方式： OAI收割

来源：地理科学与资源研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。