Spatial and temporal dynamics of a bark beetle outbreak in the Eastern European 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.

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Publication Details

Journal
Ecosphere
Published
2026-04-01
DOI
https://doi.org/10.1002/ecs2.70603
Primary Topic
Forest Insect Ecology and Management
Type
article
Field-Weighted Citation Impact
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article

Spatial and temporal dynamics of a bark beetle outbreak in the Eastern European Alps

Anna Candotti, Nuno Carvalhais, Siyuan Wang, Enrico Tomelleri
Ecosphere
Forest Insect Ecology and Management
article

Spatial and temporal dynamics of a bark beetle outbreak in the Eastern European Alps

Anna Candotti, Nuno Carvalhais, Siyuan Wang, Enrico Tomelleri
article en

Abstract

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.

EcosphereVol. 17(4)
Free University of Bozen-Bolzano (IT), American Society for Photogrammetry and Remote Sensing (US), Max Planck Institute for Biogeochemistry (DE), Technische Universität Dresden (DE), Universidade Nova de Lisboa (PT)
Good health and well-being
Openalex Percentile: Top 25%
Forest Insect Ecology and Management
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