Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Integrating process-based vegetation modelling with high-resolution imagery to assess bark beetle infestation and land surface temperature effects on forest net primary productivity

Abdullah, Haidi ; Neinavaz, Elnaz ; Darvishzadeh, Roshanak LU ; Huesca, Margarita ; Skidmore, Andrew K. LU ; Lindeskog, Mats LU ; Smith, Benjamin LU ; Heurich, Marco ; Steinbrecher, Rainer and Paganini, Marc (2025) In Remote Sensing Applications: Society and Environment 37.
Abstract

The European spruce bark beetle (Ips typographus) is an insect species that causes significant damage to Norway spruce (Picea abies) forests across Europe. Infestation by bark beetles can profoundly impact forest ecosystems, affecting their structure and composition and affecting the carbon cycle and biodiversity, including a decrease in net primary productivity (NPP), a key indicator of forest health. The primary objective of this study is to enhance our understanding of the interplay among NPP, bark beetle infestation, land surface temperature (LST), and soil moisture content as key components influencing the effects of climate change-related events (e.g., drought) during and after a drought event in the Bavarian Forest National Park... (More)

The European spruce bark beetle (Ips typographus) is an insect species that causes significant damage to Norway spruce (Picea abies) forests across Europe. Infestation by bark beetles can profoundly impact forest ecosystems, affecting their structure and composition and affecting the carbon cycle and biodiversity, including a decrease in net primary productivity (NPP), a key indicator of forest health. The primary objective of this study is to enhance our understanding of the interplay among NPP, bark beetle infestation, land surface temperature (LST), and soil moisture content as key components influencing the effects of climate change-related events (e.g., drought) during and after a drought event in the Bavarian Forest National Park in southeastern Germany. Earth observation data, specifically Landsat-8 TIR and Sentinel-2, were used to retrieve LST and leaf area index (LAI), respectively. Furthermore, for the first time, we incorporated a time series of high-resolution (20 m) LAI as a remote sensing biodiversity product into a process-based ecological model (LPJ-GUESS) to accurately generate high-resolution (20 m) NPP products. The study found a gradual decline in NPP values over time due to drought, increased LST, low precipitation, and a high rate of bark beetle infestation. We observed significantly lower LST in healthy Norway spruce stands compared to those infested by bark beetles. Likewise, low soil moisture content was associated with minimal NPP value. Our results suggest synergistic effects between bark beetle infestations and elevated LST, leading to amplified reductions in NPP value. This study highlights the critical role of integrating high-resolution remote sensing data with ecological models for advancing the understanding of forest carbon dynamics and improving predictive capabilities to inform forest management under climate change.

(Less)
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, Climate change, Land surface temperature, Leaf area index, LPJ-GUESS, Net primary productivity, Sentinel-2
in
Remote Sensing Applications: Society and Environment
volume
37
article number
101499
publisher
Elsevier
external identifiers
  • scopus:85218902804
ISSN
2352-9385
DOI
10.1016/j.rsase.2025.101499
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2025 The Author(s)
id
7faa502d-6ba4-4efd-be25-88eac50b5ac5
date added to LUP
2025-07-04 13:38:57
date last changed
2025-07-04 13:39:59
@article{7faa502d-6ba4-4efd-be25-88eac50b5ac5,
  abstract     = {{<p>The European spruce bark beetle (Ips typographus) is an insect species that causes significant damage to Norway spruce (Picea abies) forests across Europe. Infestation by bark beetles can profoundly impact forest ecosystems, affecting their structure and composition and affecting the carbon cycle and biodiversity, including a decrease in net primary productivity (NPP), a key indicator of forest health. The primary objective of this study is to enhance our understanding of the interplay among NPP, bark beetle infestation, land surface temperature (LST), and soil moisture content as key components influencing the effects of climate change-related events (e.g., drought) during and after a drought event in the Bavarian Forest National Park in southeastern Germany. Earth observation data, specifically Landsat-8 TIR and Sentinel-2, were used to retrieve LST and leaf area index (LAI), respectively. Furthermore, for the first time, we incorporated a time series of high-resolution (20 m) LAI as a remote sensing biodiversity product into a process-based ecological model (LPJ-GUESS) to accurately generate high-resolution (20 m) NPP products. The study found a gradual decline in NPP values over time due to drought, increased LST, low precipitation, and a high rate of bark beetle infestation. We observed significantly lower LST in healthy Norway spruce stands compared to those infested by bark beetles. Likewise, low soil moisture content was associated with minimal NPP value. Our results suggest synergistic effects between bark beetle infestations and elevated LST, leading to amplified reductions in NPP value. This study highlights the critical role of integrating high-resolution remote sensing data with ecological models for advancing the understanding of forest carbon dynamics and improving predictive capabilities to inform forest management under climate change.</p>}},
  author       = {{Abdullah, Haidi and Neinavaz, Elnaz and Darvishzadeh, Roshanak and Huesca, Margarita and Skidmore, Andrew K. and Lindeskog, Mats and Smith, Benjamin and Heurich, Marco and Steinbrecher, Rainer and Paganini, Marc}},
  issn         = {{2352-9385}},
  keywords     = {{Bark beetle infestation; Climate change; Land surface temperature; Leaf area index; LPJ-GUESS; Net primary productivity; Sentinel-2}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Remote Sensing Applications: Society and Environment}},
  title        = {{Integrating process-based vegetation modelling with high-resolution imagery to assess bark beetle infestation and land surface temperature effects on forest net primary productivity}},
  url          = {{http://dx.doi.org/10.1016/j.rsase.2025.101499}},
  doi          = {{10.1016/j.rsase.2025.101499}},
  volume       = {{37}},
  year         = {{2025}},
}