Pine caterpillar occurrence modeling using satellite spring phenology and meteorological variables
文献类型：期刊论文
| 作者 | Hua, Hao1,2; Wu, Chaoyang1,2; Jassal, Rachhpal S.3; Huang, Jixia4; Liu, Ronggao1,2; Wang, Yue5 |
| 刊名 | ENVIRONMENTAL RESEARCH LETTERS
 |
| 出版日期 | 2022-10-01 |
| 卷号 | 17期号:10页码:12 |
| 关键词 | day of insect occurrence (DIO) evapotranspiration larval feeding overwinter period spring phenology |
| ISSN号 | 1748-9326 |
| DOI | 10.1088/1748-9326/ac9636 |
| 通讯作者 | Wu, Chaoyang(wucy@igsnrr.ac.cn) |
| 英文摘要 | Outbreaks of leaf-feeding Lepidopteran insects substantially weaken the quality of forest trees and strongly affect the ecosystem functions of plant photosynthesis and carbon uptake. The narrow phenological time window of leaf out about ten days, during which Lepidopteran larvae feed on high nutrient newly flushed leaves, may change the insect community and outbreak dynamics by determining the survival rate of larvae. The Chinese pine Caterpillar (Dendrolimus tabulaeformis Tsai et Liu) infestation of the northern Chinese pine (Pinus tabulaeformis) forest in China is a major concern, and accurately modeling the day of insect occurrence (DIO) in the spring remains challenging. With continuous in-situ observed insect activities of 20 plots and satellite and meteorological observations from 1983 to 2014, we found a strong synchronization (r = 0.54, p = 0.001) between the satellite-based vegetation spring phenology, i.e. the green-up day (GUD), and DIO of the pine caterpillar over time. We used partial least squares regression and ridge regression models, and identified that monthly preseason air temperature, wind speed, specific humidity, and downward radiation were key environmental cues that awakened the overwintering pine caterpillars. After removing the collinearity of multiple variables, we showed that the dimensionality reduction-based regression models substantially improved the accuracy of DIO modeling than commonly used models, such as interval and degree-day models. In particular, including GUD significantly enhanced the predictive strength of the models increasing the coefficient of determination (R (2)) by 17.1% and consequently a decrease of 16.5% in the root mean square error. We further showed that evapotranspiration changed the environmental moisture content, which indirectly affected the activities of insects. Our results revealed a useful linkage between spring leaf development and insect occurrence, and therefore are of great importance for the large-scale monitoring of pest outbreaks with future remote sensing observations. |
| WOS关键词 | DENDROLIMUS-TABULAEFORMIS LEPIDOPTERA ; WESTERN SPRUCE BUDWORM ; PARTIAL LEAST-SQUARES ; CLIMATE-CHANGE ; RIDGE-REGRESSION ; QUERCUS-ROBUR ; PREDICTION ; BUDBURST ; IMPACT ; DISTURBANCES |
| 资助项目 | National Key R&D program of China[2019YFA0606603] ; National Natural Science Foundation of China[42125101] ; CAS Interdisciplinary Innovation Team[JCTD-2020-05] |
| WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000867408900001 |
| 出版者 | IOP Publishing Ltd |
| 资助机构 | National Key R&D program of China ; National Natural Science Foundation of China ; CAS Interdisciplinary Innovation Team |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/185588]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wu, Chaoyang |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Univ British Columbia, 2357 Main Mall, Vancouver, BC V6T 1Z4, Canada 4.Beijing Forestry Univ, Precis Forestry Key Lab Beijing, Beijing 100083, Peoples R China 5.Natl Forestry & Grassland Adm, Ctr Biol Disaster Prevent & Control, Beijing 100013, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hua, Hao,Wu, Chaoyang,Jassal, Rachhpal S.,et al. Pine caterpillar occurrence modeling using satellite spring phenology and meteorological variables[J]. ENVIRONMENTAL RESEARCH LETTERS,2022,17(10):12. |
| APA | Hua, Hao,Wu, Chaoyang,Jassal, Rachhpal S.,Huang, Jixia,Liu, Ronggao,&Wang, Yue.(2022).Pine caterpillar occurrence modeling using satellite spring phenology and meteorological variables.ENVIRONMENTAL RESEARCH LETTERS,17(10),12. |
| MLA | Hua, Hao,et al."Pine caterpillar occurrence modeling using satellite spring phenology and meteorological variables".ENVIRONMENTAL RESEARCH LETTERS 17.10(2022):12. |
入库方式： OAI收割
来源：地理科学与资源研究所
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