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Pengxiang Zhao

Researcher

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Exploring the spatial heterogeneity of bark beetle infestation risk factors with geographically weighted regression and random forest

Author

  • Pengxiang Zhao
  • Per Ola Olsson
  • Albert Øhrman Wellendorf
  • Mitro Müller
  • Ali Mansourian

Summary, in English

This study investigated the spatial dynamics of bark beetle infestations and their relationships with risk factors in south-eastern Swedish forests during the years 2018–2020, highlighting the importance of spatial heterogeneity of risk factors, particularly under climate change. First, global Random Forest (RF) models were developed to examine the relationships between bark beetle infestations and risk factors during normal and drought periods. Second, spatial heterogeneity of the relationships was explored in local RF models by integrating Geographically Weighted Regression (GWR) with RF. The global RF models achieved accuracies of 0.89 and 0.84 for the normal and drought periods, respectively. In contrast, the local RF models performed better in many areas, capturing spatial variations in infestation drivers. Local models successfully identified the varying importance of risk factors, such as tree species composition, stand age, and local climate conditions, especially during drought. These findings underscore the necessity of spatially adaptive forest management strategies. The essential targeted interventions should consider local conditions, particularly during droughts, to mitigate infestation damage, instead of applying a “one-size-fits-all” strategy. The research highlights the need for monitoring and interventions at local scales, offering a more effective approach to managing bark beetle outbreaks in vulnerable forest ecosystems.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • Centre for Geographical Information Systems (GIS Centre)
  • eSSENCE: The e-Science Collaboration
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • MERGE: ModElling the Regional and Global Earth system
  • LU Profile Area: Nature-based future solutions

Publishing year

2025

Language

English

Pages

188-204

Publication/Series

Scandinavian Journal of Forest Research

Volume

40

Issue

3-4

Document type

Journal article

Publisher

Taylor and Francis A.S.

Topic

  • Other Earth Sciences (including Geographical Information Science)
  • Environmental Sciences
  • Forest Science

Keywords

  • bark beetle infestation
  • geographically weighted regression
  • Ips typographus
  • Picea abies
  • random forest
  • risk factors
  • spatial heterogeneity

Status

Published

ISBN/ISSN/Other

  • ISSN: 0282-7581