4.8 Article

Emergent vulnerability to climate-driven disturbances in European forests

期刊

NATURE COMMUNICATIONS
卷 12, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41467-021-21399-7

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资金

  1. Exploratory Project FOREST@RISK of the European Commission
  2. European Research Council (ERC) through the ERC Consolidator Grant SEDAL [647423]

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This study quantifies European forest vulnerability to fires, windthrows, and insect outbreaks from 1979 to 2018 using machine learning, disturbance data, and satellite products. Results show that about 33.4 billion tonnes of forest biomass could be seriously affected, with higher relative losses in windthrows and fires compared to insect outbreaks. The spatial pattern of vulnerability is influenced by forest characteristics and background climate, with hotspot regions identified at the borders of the climate envelope in southern and northern Europe.
Forest disturbance regimes are expected to intensify as Earth's climate changes. Quantifying forest vulnerability to disturbances and understanding the underlying mechanisms is crucial to develop mitigation and adaptation strategies. However, observational evidence is largely missing at regional to continental scales. Here, we quantify the vulnerability of European forests to fires, windthrows and insect outbreaks during the period 1979-2018 by integrating machine learning with disturbance data and satellite products. We show that about 33.4 billion tonnes of forest biomass could be seriously affected by these disturbances, with higher relative losses when exposed to windthrows (40%) and fires (34%) compared to insect outbreaks (26%). The spatial pattern in vulnerability is strongly controlled by the interplay between forest characteristics and background climate. Hotspot regions for vulnerability are located at the borders of the climate envelope, in both southern and northern Europe. There is a clear trend in overall forest vulnerability that is driven by a warming-induced reduction in plant defence mechanisms to insect outbreaks, especially at high latitudes. Natural disturbances imperil healthy and productive forests, but quantifying their effects at large scales is challenging. Here the authors apply machine learning to disturbance records and satellite data to quantify and map European forest vulnerability to fires, windthrows, and insect outbreaks through 1979-2018.

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