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

Zhao, Pengxiang LU ; Olsson, Per Ola LU ; Øhrman Wellendorf, Albert ; Müller, Mitro LU orcid and Mansourian, Ali LU orcid (2025) In Scandinavian Journal of Forest Research 40(3-4). p.188-204
Abstract

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... (More)

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.

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Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
bark beetle infestation, geographically weighted regression, Ips typographus, Picea abies, random forest, risk factors, spatial heterogeneity
in
Scandinavian Journal of Forest Research
volume
40
issue
3-4
pages
17 pages
publisher
Taylor and Francis A.S.
external identifiers
  • scopus:105005513228
ISSN
0282-7581
DOI
10.1080/02827581.2025.2503807
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
id
b4f9909b-caf3-462a-8a29-f1ecea23850e
date added to LUP
2025-07-04 18:26:44
date last changed
2025-08-12 09:55:24
@article{b4f9909b-caf3-462a-8a29-f1ecea23850e,
  abstract     = {{<p>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.</p>}},
  author       = {{Zhao, Pengxiang and Olsson, Per Ola and Øhrman Wellendorf, Albert and Müller, Mitro and Mansourian, Ali}},
  issn         = {{0282-7581}},
  keywords     = {{bark beetle infestation; geographically weighted regression; Ips typographus; Picea abies; random forest; risk factors; spatial heterogeneity}},
  language     = {{eng}},
  number       = {{3-4}},
  pages        = {{188--204}},
  publisher    = {{Taylor and Francis A.S.}},
  series       = {{Scandinavian Journal of Forest Research}},
  title        = {{Exploring the spatial heterogeneity of bark beetle infestation risk factors with geographically weighted regression and random forest}},
  url          = {{http://dx.doi.org/10.1080/02827581.2025.2503807}},
  doi          = {{10.1080/02827581.2025.2503807}},
  volume       = {{40}},
  year         = {{2025}},
}