View in EDS HTML Full Text PDF Full Text

Climate change will increase forest disturbances in Europe throughout the 21st century.

Saved in:
Bibliographic Details
Title: Climate change will increase forest disturbances in Europe throughout the 21st century.
Authors: Grünig, Marc (AUTHOR), Rammer, Werner (AUTHOR), Senf, Cornelius (AUTHOR), Albrich, Katharina (AUTHOR), André, Frédéric (AUTHOR), Augustynczik, Andrey L. D. (AUTHOR), Baumann, Martin (AUTHOR), Bohn, Friedrich J. (AUTHOR), Bouwman, Meike (AUTHOR), Bugmann, Harald (AUTHOR), Collalti, Alessio (AUTHOR), Cristal, Irina (AUTHOR), Dalmonech, Daniela (AUTHOR), De Coligny, Francois (AUTHOR), Dobor, Laura (AUTHOR), Dollinger, Christina (AUTHOR), Espelta, Josep Maria (AUTHOR), Forrester, David I. (AUTHOR), Garcia-Gonzalo, Jordi (AUTHOR), González-Olabarria, José Ramón (AUTHOR)
Source: Science. 3/5/2026, Vol. 391 Issue 6789, p1-12. 12p.
Subjects: Climate change, Wildfires, Bark beetles, Storms, Tree mortality, Computer simulation, Forest degradation, Continents
Geographic Terms: Southern Europe, Europe
Abstract: Wildfires, insect outbreaks, and storms cause large pulses of tree mortality. Climate change amplifies these forest disturbances, yet their future magnitude and extent remain uncertain. Here, we simulated future forest disturbance regimes at 100-meter resolution across Europe using a deep learning–based simulation framework. Our results show that forest disturbances will continue to increase throughout the 21st century, with disturbed areas more than doubling relative to the recent past under an unabated continuation of climate change. Wildfires are the main agent driving future disturbance change. Changing disturbances result in an increase in young forests, substantially altering Europe's forest demography. Because of their profound implications for forest carbon storage and the habitat value of forest ecosystems, disturbances should be a priority of forest policy and management. Editor's summary: Climate change has already increased the occurrence of wildfires, convective storms, and bark beetle outbreaks, all of which are major drivers of tree mortality in forests. However, the future trajectories of these disturbances are unknown, particularly because they can interact with one another. Grünig et al. projected changes in disturbance rates and tree mortality across Europe in the 21st century under three climate change scenarios. They predicted an increase in disturbance-induced mortality especially that due to wildfires. These changes will lead to a decline in old forests and an increase in young forests, particularly in the Mediterranean, with implications for carbon sequestration and biodiversity. —Bianca Lopez INTRODUCTION: Forests across the globe face increasing risks from natural disturbances such as wildfires, insect outbreaks, and windstorms. These disturbances are highly sensitive to changes in the climate system and have already increased in many parts of the globe recently. Changing disturbance regimes can substantially alter ecosystems, e.g., through changing their demography and habitat value as well as altering the ecosystem services they provide to society. Anticipating potential future disturbance change is thus crucial for forest policy and management. However, projecting future disturbance regimes remains challenging because there are intricate interactions between individual disturbance agents, and feedbacks between vegetation development and disturbance change could considerably dampen or amplify climate impacts. RATIONALE: Here, we present a modeling framework to simulate future trajectories of forest disturbance at high spatial resolution (100 × 100 meters) and across a large spatial extent (187 million hectares of forests in Europe). We leveraged a deep learning–based simulation framework to integrate a large body of local projections made by process-based forest models with climate-sensitive disturbance modules for wildfire, windthrow, and bark beetle outbreaks. Our modeling framework is designed to capture crucial disturbance processes such as the spatial spread of fire and bark beetles across forest landscapes and incorporates disturbance interactions and vegetation feedbacks. Our specific objectives were to quantify potential changes in stand-replacing forest disturbances in Europe until the end of the 21st century under different scenarios of climate change and to assess impacts of disturbance change on Europe's forest demography. RESULTS: Forest disturbances in Europe are highly likely to increase in the coming decades. Simulated future levels of disturbance were higher than those observed for the period 1986 to 2020 under all climate scenarios. Under scenarios of unabated climate change, the simulated area disturbed more than doubled by the end of the century (+122%). In scenarios assuming effective emissions reduction, peak disturbance was reached by midcentury. Wildfire was the disturbance agent most sensitive to changes in the climate system, heavily affecting Mediterranean areas but also expanding into temperate and boreal regions. Vegetation feedbacks dampened climate-induced disturbance change but were not able to completely buffer from disturbance increases. We project profound implications of future disturbance change on Europe's forest demography, with the share of young forests increasing by up to 14% and old forests decreasing by up to 3% relative to simulations without changing climate and disturbance regimes. CONCLUSION: The large-scale changes in forest disturbance regimes projected for the coming decades have important implications for biodiversity and the ecosystem services provided by forests. They could, for instance, hamper policy goals of using nature-based solutions for climate change mitigation, further amplifying climate change. Consequently, forest policy and management need to plan for a future with more disturbance. Nonetheless, our results highlight that mitigating anthropogenic climate change remains a potent lever for limiting future disturbance risk and safeguarding forests and their services to society. Simulation framework.: Shown is a simulation framework combining process-oriented disturbance models trained with remote sensing data and local process-model simulations in a deep learning–based dynamic forest and disturbance model (top). This framework was used to simulate future forest disturbance regimes in Europe at 100-meter spatial resolution (bottom left) and annual time step (bottom right). Our results show that disturbances in Europe's forests will increase throughout the 21st century (shown here for a scenario of unabated warming). [ABSTRACT FROM AUTHOR]
Copyright of Science is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 192125651
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Climate change will increase forest disturbances in Europe throughout the 21st century.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Grünig%2C+Marc%22">Grünig, Marc</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rammer%2C+Werner%22">Rammer, Werner</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Senf%2C+Cornelius%22">Senf, Cornelius</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Albrich%2C+Katharina%22">Albrich, Katharina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22André%2C+Frédéric%22">André, Frédéric</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Augustynczik%2C+Andrey+L%2E+D%2E%22">Augustynczik, Andrey L. D.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Baumann%2C+Martin%22">Baumann, Martin</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bohn%2C+Friedrich+J%2E%22">Bohn, Friedrich J.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bouwman%2C+Meike%22">Bouwman, Meike</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bugmann%2C+Harald%22">Bugmann, Harald</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Collalti%2C+Alessio%22">Collalti, Alessio</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cristal%2C+Irina%22">Cristal, Irina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dalmonech%2C+Daniela%22">Dalmonech, Daniela</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22De+Coligny%2C+Francois%22">De Coligny, Francois</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dobor%2C+Laura%22">Dobor, Laura</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dollinger%2C+Christina%22">Dollinger, Christina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Espelta%2C+Josep+Maria%22">Espelta, Josep Maria</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Forrester%2C+David+I%2E%22">Forrester, David I.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Garcia-Gonzalo%2C+Jordi%22">Garcia-Gonzalo, Jordi</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22González-Olabarria%2C+José+Ramón%22">González-Olabarria, José Ramón</searchLink> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Science%22">Science</searchLink>. 3/5/2026, Vol. 391 Issue 6789, p1-12. 12p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br /><searchLink fieldCode="DE" term="%22Wildfires%22">Wildfires</searchLink><br /><searchLink fieldCode="DE" term="%22Bark+beetles%22">Bark beetles</searchLink><br /><searchLink fieldCode="DE" term="%22Storms%22">Storms</searchLink><br /><searchLink fieldCode="DE" term="%22Tree+mortality%22">Tree mortality</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Forest+degradation%22">Forest degradation</searchLink><br /><searchLink fieldCode="DE" term="%22Continents%22">Continents</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Southern+Europe%22">Southern Europe</searchLink><br /><searchLink fieldCode="DE" term="%22Europe%22">Europe</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Wildfires, insect outbreaks, and storms cause large pulses of tree mortality. Climate change amplifies these forest disturbances, yet their future magnitude and extent remain uncertain. Here, we simulated future forest disturbance regimes at 100-meter resolution across Europe using a deep learning–based simulation framework. Our results show that forest disturbances will continue to increase throughout the 21st century, with disturbed areas more than doubling relative to the recent past under an unabated continuation of climate change. Wildfires are the main agent driving future disturbance change. Changing disturbances result in an increase in young forests, substantially altering Europe's forest demography. Because of their profound implications for forest carbon storage and the habitat value of forest ecosystems, disturbances should be a priority of forest policy and management. Editor's summary: Climate change has already increased the occurrence of wildfires, convective storms, and bark beetle outbreaks, all of which are major drivers of tree mortality in forests. However, the future trajectories of these disturbances are unknown, particularly because they can interact with one another. Grünig et al. projected changes in disturbance rates and tree mortality across Europe in the 21st century under three climate change scenarios. They predicted an increase in disturbance-induced mortality especially that due to wildfires. These changes will lead to a decline in old forests and an increase in young forests, particularly in the Mediterranean, with implications for carbon sequestration and biodiversity. —Bianca Lopez INTRODUCTION: Forests across the globe face increasing risks from natural disturbances such as wildfires, insect outbreaks, and windstorms. These disturbances are highly sensitive to changes in the climate system and have already increased in many parts of the globe recently. Changing disturbance regimes can substantially alter ecosystems, e.g., through changing their demography and habitat value as well as altering the ecosystem services they provide to society. Anticipating potential future disturbance change is thus crucial for forest policy and management. However, projecting future disturbance regimes remains challenging because there are intricate interactions between individual disturbance agents, and feedbacks between vegetation development and disturbance change could considerably dampen or amplify climate impacts. RATIONALE: Here, we present a modeling framework to simulate future trajectories of forest disturbance at high spatial resolution (100 × 100 meters) and across a large spatial extent (187 million hectares of forests in Europe). We leveraged a deep learning–based simulation framework to integrate a large body of local projections made by process-based forest models with climate-sensitive disturbance modules for wildfire, windthrow, and bark beetle outbreaks. Our modeling framework is designed to capture crucial disturbance processes such as the spatial spread of fire and bark beetles across forest landscapes and incorporates disturbance interactions and vegetation feedbacks. Our specific objectives were to quantify potential changes in stand-replacing forest disturbances in Europe until the end of the 21st century under different scenarios of climate change and to assess impacts of disturbance change on Europe's forest demography. RESULTS: Forest disturbances in Europe are highly likely to increase in the coming decades. Simulated future levels of disturbance were higher than those observed for the period 1986 to 2020 under all climate scenarios. Under scenarios of unabated climate change, the simulated area disturbed more than doubled by the end of the century (+122%). In scenarios assuming effective emissions reduction, peak disturbance was reached by midcentury. Wildfire was the disturbance agent most sensitive to changes in the climate system, heavily affecting Mediterranean areas but also expanding into temperate and boreal regions. Vegetation feedbacks dampened climate-induced disturbance change but were not able to completely buffer from disturbance increases. We project profound implications of future disturbance change on Europe's forest demography, with the share of young forests increasing by up to 14% and old forests decreasing by up to 3% relative to simulations without changing climate and disturbance regimes. CONCLUSION: The large-scale changes in forest disturbance regimes projected for the coming decades have important implications for biodiversity and the ecosystem services provided by forests. They could, for instance, hamper policy goals of using nature-based solutions for climate change mitigation, further amplifying climate change. Consequently, forest policy and management need to plan for a future with more disturbance. Nonetheless, our results highlight that mitigating anthropogenic climate change remains a potent lever for limiting future disturbance risk and safeguarding forests and their services to society. Simulation framework.: Shown is a simulation framework combining process-oriented disturbance models trained with remote sensing data and local process-model simulations in a deep learning–based dynamic forest and disturbance model (top). This framework was used to simulate future forest disturbance regimes in Europe at 100-meter spatial resolution (bottom left) and annual time step (bottom right). Our results show that disturbances in Europe's forests will increase throughout the 21st century (shown here for a scenario of unabated warming). [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Science is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=192125651
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1126/science.adx6329
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 1
    Subjects:
      – SubjectFull: Climate change
        Type: general
      – SubjectFull: Wildfires
        Type: general
      – SubjectFull: Bark beetles
        Type: general
      – SubjectFull: Storms
        Type: general
      – SubjectFull: Tree mortality
        Type: general
      – SubjectFull: Computer simulation
        Type: general
      – SubjectFull: Forest degradation
        Type: general
      – SubjectFull: Continents
        Type: general
      – SubjectFull: Southern Europe
        Type: general
      – SubjectFull: Europe
        Type: general
    Titles:
      – TitleFull: Climate change will increase forest disturbances in Europe throughout the 21st century.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Grünig, Marc
      – PersonEntity:
          Name:
            NameFull: Rammer, Werner
      – PersonEntity:
          Name:
            NameFull: Senf, Cornelius
      – PersonEntity:
          Name:
            NameFull: Albrich, Katharina
      – PersonEntity:
          Name:
            NameFull: André, Frédéric
      – PersonEntity:
          Name:
            NameFull: Augustynczik, Andrey L. D.
      – PersonEntity:
          Name:
            NameFull: Baumann, Martin
      – PersonEntity:
          Name:
            NameFull: Bohn, Friedrich J.
      – PersonEntity:
          Name:
            NameFull: Bouwman, Meike
      – PersonEntity:
          Name:
            NameFull: Bugmann, Harald
      – PersonEntity:
          Name:
            NameFull: Collalti, Alessio
      – PersonEntity:
          Name:
            NameFull: Cristal, Irina
      – PersonEntity:
          Name:
            NameFull: Dalmonech, Daniela
      – PersonEntity:
          Name:
            NameFull: De Coligny, Francois
      – PersonEntity:
          Name:
            NameFull: Dobor, Laura
      – PersonEntity:
          Name:
            NameFull: Dollinger, Christina
      – PersonEntity:
          Name:
            NameFull: Espelta, Josep Maria
      – PersonEntity:
          Name:
            NameFull: Forrester, David I.
      – PersonEntity:
          Name:
            NameFull: Garcia-Gonzalo, Jordi
      – PersonEntity:
          Name:
            NameFull: González-Olabarria, José Ramón
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 05
              M: 03
              Text: 3/5/2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 00368075
          Numbering:
            – Type: volume
              Value: 391
            – Type: issue
              Value: 6789
          Titles:
            – TitleFull: Science
              Type: main
ResultId 1