Spatial and temporal dynamics of a bark beetle outbreak in the Eastern European Alps.
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| Title: | Spatial and temporal dynamics of a bark beetle outbreak in the Eastern European Alps. |
|---|---|
| Authors: | Candotti, Anna1 (AUTHOR) anna.candotti@unibz.it, Carvalhais, Nuno2,3,4 (AUTHOR), Wang, Siyuan2,5 (AUTHOR), Tomelleri, Enrico1,6 (AUTHOR) |
| Source: | Ecosphere. Apr2026, Vol. 17 Issue 4, p1-15. 15p. |
| Subject Terms: | *Epidemics, *Biomass, *Forest degradation, *Plant biomass, Bark beetles, Alpine regions, Time series analysis, Spatial variation |
| Geographic Terms: | Alps |
| Abstract: | The Alps are currently considered among the ecoregions with the highest magnitude of average bark beetle disturbance per year in Europe. We present a disturbance characterization based on a unique database including more than 50,000 records of ground‐based bark beetle disturbance observations in the Eastern Alps from 2020 to 2023. The dataset was used to extract precise temporal and spatial information on disturbance events in terms of size, distance, intensity, and frequency. Disturbance events were modeled as spatial point processes based on scale dependency (landscape‐regional) and their deviations from random distributions were assessed. Parameters typically used in forest disturbance models such as clustering degree, intensity slope, and probability scale were retrieved. Additionally, aboveground biomass affected by bark beetle disturbance was estimated. Disturbance metrics were found to be heterogeneous over time, revealing a decrease in single infestation spot sizes as the epidemics progressed in combination with a reduction in inter‐event distances and an increase in spatial frequency. At the landscape scale, point processes showed very distinct distributions in space with nestlike clustering, clustering towards portions of the landscape, or no clustering at all. The clustering degree and the probability scale sharply increased from the build‐up to the highly epidemic phase. Four percent of the total regional aboveground biomass was affected by bark beetle disturbances over the four‐year study period. The extracted disturbance metrics and parameters can help in the correct parameterization of forest disturbance models, thus supporting our capability of predicting future patterns of beetle dispersal and their effects on carbon stocks in the alpine region. [ABSTRACT FROM AUTHOR] |
| Copyright of Ecosphere is the property of Wiley-Blackwell 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: | GreenFILE |
| FullText | Text: Availability: 0 |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 193280204 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Spatial and temporal dynamics of a bark beetle outbreak in the Eastern European Alps. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Candotti%2C+Anna%22">Candotti, Anna</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> anna.candotti@unibz.it</i><br /><searchLink fieldCode="AR" term="%22Carvalhais%2C+Nuno%22">Carvalhais, Nuno</searchLink><relatesTo>2,3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Siyuan%22">Wang, Siyuan</searchLink><relatesTo>2,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tomelleri%2C+Enrico%22">Tomelleri, Enrico</searchLink><relatesTo>1,6</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Ecosphere%22">Ecosphere</searchLink>. Apr2026, Vol. 17 Issue 4, p1-15. 15p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Epidemics%22">Epidemics</searchLink><br />*<searchLink fieldCode="DE" term="%22Biomass%22">Biomass</searchLink><br />*<searchLink fieldCode="DE" term="%22Forest+degradation%22">Forest degradation</searchLink><br />*<searchLink fieldCode="DE" term="%22Plant+biomass%22">Plant biomass</searchLink><br /><searchLink fieldCode="DE" term="%22Bark+beetles%22">Bark beetles</searchLink><br /><searchLink fieldCode="DE" term="%22Alpine+regions%22">Alpine regions</searchLink><br /><searchLink fieldCode="DE" term="%22Time+series+analysis%22">Time series analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Spatial+variation%22">Spatial variation</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Alps%22">Alps</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The Alps are currently considered among the ecoregions with the highest magnitude of average bark beetle disturbance per year in Europe. We present a disturbance characterization based on a unique database including more than 50,000 records of ground‐based bark beetle disturbance observations in the Eastern Alps from 2020 to 2023. The dataset was used to extract precise temporal and spatial information on disturbance events in terms of size, distance, intensity, and frequency. Disturbance events were modeled as spatial point processes based on scale dependency (landscape‐regional) and their deviations from random distributions were assessed. Parameters typically used in forest disturbance models such as clustering degree, intensity slope, and probability scale were retrieved. Additionally, aboveground biomass affected by bark beetle disturbance was estimated. Disturbance metrics were found to be heterogeneous over time, revealing a decrease in single infestation spot sizes as the epidemics progressed in combination with a reduction in inter‐event distances and an increase in spatial frequency. At the landscape scale, point processes showed very distinct distributions in space with nestlike clustering, clustering towards portions of the landscape, or no clustering at all. The clustering degree and the probability scale sharply increased from the build‐up to the highly epidemic phase. Four percent of the total regional aboveground biomass was affected by bark beetle disturbances over the four‐year study period. The extracted disturbance metrics and parameters can help in the correct parameterization of forest disturbance models, thus supporting our capability of predicting future patterns of beetle dispersal and their effects on carbon stocks in the alpine region. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Ecosphere is the property of Wiley-Blackwell 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/ecs2.70603 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 1 Subjects: – SubjectFull: Epidemics Type: general – SubjectFull: Biomass Type: general – SubjectFull: Forest degradation Type: general – SubjectFull: Plant biomass Type: general – SubjectFull: Bark beetles Type: general – SubjectFull: Alpine regions Type: general – SubjectFull: Time series analysis Type: general – SubjectFull: Spatial variation Type: general – SubjectFull: Alps Type: general Titles: – TitleFull: Spatial and temporal dynamics of a bark beetle outbreak in the Eastern European Alps. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Candotti, Anna – PersonEntity: Name: NameFull: Carvalhais, Nuno – PersonEntity: Name: NameFull: Wang, Siyuan – PersonEntity: Name: NameFull: Tomelleri, Enrico IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 21508925 Numbering: – Type: volume Value: 17 – Type: issue Value: 4 Titles: – TitleFull: Ecosphere Type: main |
| ResultId | 1 |