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Effects of stand and landscape level variables on shoot damage ratios caused by shoot beetles in Southwest China.

Authors :
Yu, Linfeng
Zhan, Zhongyi
Ren, Lili
Liu, Yujie
Huang, Huaguo
Luo, Youqing
Source :
Forest Ecology & Management; Mar2022, Vol. 507, pN.PAG-N.PAG, 1p
Publication Year :
2022

Abstract

• No study verified the factors affecting the dispersal of shoot beetles in Southwest China. • Landscape-level variables are the more important predictor, the roles of the stand-level variables are also important. • The prediction of damage severity distribution of Tomicus spp. highlights the need for forest management improvement. The outbreaks of shoot beetles (Tomicus yunnanensis Kirkendall and Faccoli and Tomicus minor Hartig) have caused widespread tree mortality in Southwest China. However, multi-scale variables explaining the shoot damage ratio (SDR) caused by shoot beetles have never been studied. The objective of this study was to determine the effects of stand-level and landscape-level variables on SDR during outbreaks of shoot beetles in Yunnan pine forests. Sixty-five plots were generated during 2015–2017 based on beetle infestation maps derived from multi-data Landsat images and field survey. Nine explanatory variables were quantified to explain the SDR severity. The forest cover was obtained from a Worldview-3 high‐resolution image. We used the forest resource planning and design survey data to develop landscape context variables. The beetle pressure variable was calculated using beetle infestation maps. The relative importance of the explanatory variables was analyzed using multi-model inference. We established that SDR was higher in the plots that were closer to roads and severely damaged forest areas in the previous year. SDR was negatively affected by edge density (ED) and forest cover, but positively affected by the mean shape index (SHAPE MN) and aspect. Landscape-level variables are probably the more important predictor, stand-level variables also had a significant effect on the shoot beetle outbreak. The prediction models including stand-level variables and landscape-level variables were built. Identifying variables that drive beetle-caused SDR contributed to the improvement of the existing strategies for outbreak control. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03781127
Volume :
507
Database :
Supplemental Index
Journal :
Forest Ecology & Management
Publication Type :
Academic Journal
Accession number :
154893050
Full Text :
https://doi.org/10.1016/j.foreco.2022.120030