Features predisposing forest to bark beetle outbreaks and their dynamics during drought
Müller, Mitro LU
; Olsson, Per-Ola
LU
; Eklundh, Lars
LU
; Jamali, Sadegh
LU
and Ardö, Jonas
LU
(2022)
In Forest Ecology and Management
523.
- Abstract
- Climate change is estimated to increase the risk of the bark beetle (Ips typographus L.) mass outbreaks in Norway Spruce (Picea abies (L.) Karst) forests. Habitats that are thermally suitable for bark beetles may expand, and an increase in the frequency and intensity of droughts can promote drought stress on host trees. Drought affects tree vigor and in unison with environmental features it influences the local predisposition risk of forest stands to bark beetle attacks. We aimed to study how various environmental features influence the risk of bark beetle attacks during a drought year and the following years with more normal weather conditions but with higher bark beetle populations. We included features representing local forest stand... (More)
- Climate change is estimated to increase the risk of the bark beetle (Ips typographus L.) mass outbreaks in Norway Spruce (Picea abies (L.) Karst) forests. Habitats that are thermally suitable for bark beetles may expand, and an increase in the frequency and intensity of droughts can promote drought stress on host trees. Drought affects tree vigor and in unison with environmental features it influences the local predisposition risk of forest stands to bark beetle attacks. We aimed to study how various environmental features influence the risk of bark beetle attacks during a drought year and the following years with more normal weather conditions but with higher bark beetle populations. We included features representing local forest stand attributes, topography, soil type and wetness, the proximity of clear-cuts and previous bark beetle attacks, and a machine learning algorithm (random forest) was applied to study the variation of predisposition risk across a 48,600 km2 study area in SE Sweden.
Forest stands with increased risk of bark beetle attack were distinguished with high accuracy both during drought and in normal weather conditions. The results show that during both study periods, spruce and mixed coniferous forests had elevated risk of attack, while forests with a mix of deciduous and coniferous trees had a lower risk. Forests with high average canopy height were strongly predisposed to bark beetle attacks. However, during the drought year risk was more similar between stands with lower and higher canopy height, suggesting that during drought periods younger trees can be predisposed to bark beetle attacks. The importance of soil moisture and position within the local landscape were highlighted as important features during the drought year.
Identifying areas with increased risk, supported by information on how environmental features control the predisposition risk during drought, could aid adaptation strategies and forest management intervention efforts. We conclude that geospatial data and machine learning have the potential to further support the digitalization of the forest industry, facilitating development of methods capable to quantify importance and dynamics of environmental features controlling the risk in local context. Corresponding methods could help to direct management actions more effectively and offer information for decision-making in changing climate. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/9f6996db-15c9-48fd-bb7d-9d10b7d9bc2f
- author
- Müller, Mitro
LU
; Olsson, Per-Ola
LU
; Eklundh, Lars
LU
; Jamali, Sadegh
LU
and Ardö, Jonas
LU
- organization
- publishing date
- 2022-11-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Forest Ecology and Management
- volume
- 523
- article number
- 120480
- publisher
- Elsevier
- external identifiers
-
- scopus:85137171153
- ISSN
- 1872-7042
- DOI
- 10.1016/j.foreco.2022.120480
- language
- English
- LU publication?
- yes
- id
- 9f6996db-15c9-48fd-bb7d-9d10b7d9bc2f
- date added to LUP
- 2022-09-08 09:47:32
- date last changed
- 2022-10-17 08:58:38
@article{9f6996db-15c9-48fd-bb7d-9d10b7d9bc2f,
abstract = {{Climate change is estimated to increase the risk of the bark beetle (Ips typographus L.) mass outbreaks in Norway Spruce (Picea abies (L.) Karst) forests. Habitats that are thermally suitable for bark beetles may expand, and an increase in the frequency and intensity of droughts can promote drought stress on host trees. Drought affects tree vigor and in unison with environmental features it influences the local predisposition risk of forest stands to bark beetle attacks. We aimed to study how various environmental features influence the risk of bark beetle attacks during a drought year and the following years with more normal weather conditions but with higher bark beetle populations. We included features representing local forest stand attributes, topography, soil type and wetness, the proximity of clear-cuts and previous bark beetle attacks, and a machine learning algorithm (random forest) was applied to study the variation of predisposition risk across a 48,600 km2 study area in SE Sweden.<br/><br/>Forest stands with increased risk of bark beetle attack were distinguished with high accuracy both during drought and in normal weather conditions. The results show that during both study periods, spruce and mixed coniferous forests had elevated risk of attack, while forests with a mix of deciduous and coniferous trees had a lower risk. Forests with high average canopy height were strongly predisposed to bark beetle attacks. However, during the drought year risk was more similar between stands with lower and higher canopy height, suggesting that during drought periods younger trees can be predisposed to bark beetle attacks. The importance of soil moisture and position within the local landscape were highlighted as important features during the drought year.<br/><br/>Identifying areas with increased risk, supported by information on how environmental features control the predisposition risk during drought, could aid adaptation strategies and forest management intervention efforts. We conclude that geospatial data and machine learning have the potential to further support the digitalization of the forest industry, facilitating development of methods capable to quantify importance and dynamics of environmental features controlling the risk in local context. Corresponding methods could help to direct management actions more effectively and offer information for decision-making in changing climate.}},
author = {{Müller, Mitro and Olsson, Per-Ola and Eklundh, Lars and Jamali, Sadegh and Ardö, Jonas}},
issn = {{1872-7042}},
language = {{eng}},
month = {{11}},
publisher = {{Elsevier}},
series = {{Forest Ecology and Management}},
title = {{Features predisposing forest to bark beetle outbreaks and their dynamics during drought}},
url = {{http://dx.doi.org/10.1016/j.foreco.2022.120480}},
doi = {{10.1016/j.foreco.2022.120480}},
volume = {{523}},
year = {{2022}},
}