Background: Pine wilt disease (PWD) outbreaks have affected extensive areas of South China's forests, but the factors explaining landscape patterns of pine mortality are poorly understood. The objective of this study was to determine the relative importance of stand structure, topography, landscape context, and beetle pressure in explaining PWD severity. During 2020-2021, we identified 66 plots based on mapped PWD infestation severity. We built PWD infestation maps for 2019-2021 through field surveys. Stand structure and topography were obtained from Forest Resources Management 'One Map' and elevation raster data. We then used 'One Map' and PWD infestation maps to determine landscape context and beetle pressure variables at different spatial scales. The relative importance of 12 explanatory variables was analyzed using multi-model inference.
Results: In this study, we show that: (i) 1 km was the best spatial scale related to pine mortality, and (ii) models including landscape context and beetle pressure were much better at predicting pine mortality than models using only stand-level variables.
Conclusion: Landscape-level variables, particularly beetle pressure, were the most consistent predictors of subsequent pine mortality within susceptible stands. These results may help forest managers identify locations vulnerable to PWD and improve existing strategies for outbreak control. © 2023 Society of Chemical Industry.
Keywords: Pinus massoniana; beetle pressure; edge density; landscape context; multi-model analysis.
© 2023 Society of Chemical Industry.