Abstract
Aim: Forest ecosystems around the globe are facing increasing natural and human disturbances. Increasing disturbances can challenge forest resilience, that is, the capacity of forests to sustain their functions and services in the face of disturbance. Quantifying resilience across large spatial extents remains challenging, as it requires the assessment of the ability of forests to recover from disturbance. Here we analysed the resilience of Europe’s forests by means of satellite-based recovery and disturbance indicators. Location: Continental Europe (35 countries). Time period: 1986–2018. Major taxa studied: Gymnosperm and angiosperm woody plant species. Methods: We used a comprehensive set of manually interpreted reference plots and random forest regression to model annual canopy cover from remote sensing data across more than 30 million disturbance patches in Europe over the time period 1986–2018. From annual time series of canopy cover, we estimated the time it takes disturbed areas to recover to pre-disturbance canopy cover levels using space-for-time substitution. We quantified forest resilience as the ratio between canopy disturbance and recovery intervals, with critical resilience defined as forest areas where canopy disturbances occurred faster than canopy recovery. Results: On average across Europe, forests recover to pre-disturbance canopy cover within 30 years. The resilience of Europe’s forests to disturbance is high, with recovery being > 10 times faster than disturbance on 69% of the forest area. However, 14% of Europe’s forests had low or critical resilience, with disturbances occurring as fast or faster than forest canopy can recover. Main conclusions: We conclude that Europe’s forests are widely resilient to past disturbance regimes, yet changing climate and disturbance regimes could erode resilience.
Original language | English |
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Pages (from-to) | 25-36 |
Number of pages | 12 |
Journal | Global Ecology and Biogeography |
Volume | 31 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2022 |
Keywords
- Landsat
- disturbance
- recovery
- remote sensing
- resilience
- tree mortality