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Mapping the forest disturbance regimes of Europe

An Author Correction to this article was published on 09 February 2021

This article has been updated

Abstract

Changes in forest disturbances can have strong impacts on forests, yet we lack consistent data on Europe’s forest disturbance regimes and their changes over time. Here we used satellite data to map three decades of forest disturbances across continental Europe, and analysed the patterns and trends in disturbance size, frequency and severity. Between 1986 and 2016, 17% of Europe’s forest area was disturbed by anthropogenic and/or natural causes. We identified 36 million individual disturbance patches with a mean patch size of 1.09 ha, which equals an annual average of 0.52 disturbance patches per km2 of forest area. The majority of disturbances were stand replacing. While trends in disturbance size were highly variable, disturbance frequency consistently increased and disturbance severity decreased. Here we present a continental-scale characterization of Europe’s forest disturbance regimes and their changes over time, providing spatial information that is critical for understanding the ongoing changes in Europe’s forests.

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Fig. 1: Forest disturbances in Europe, 1986–2016.
Fig. 2: Forest disturbance regimes mapped across Europe.
Fig. 3: Trends in Europe’s forest disturbance regimes, 1986–2016.

Data availability

The Landsat data are freely available via either USGS Earth Explorer (https://earthexplorer.usgs.gov) or Google Earth Engine (https://earthengine.google.com). The reference data used in this paper are available at https://doi.org/10.5281/zenodo.3561925. All other data used are available at https://doi.org/10.5281/zenodo.3925447. The disturbance maps produced in this paper are available at https://doi.org/10.5281/zenodo.3924381.

Code availability

The code used for processing the Landsat data is available at https://github.com/eMapR/LT-GEE. The code for reproduction of all analyses is available at https://doi.org/10.5281/zenodo.3925447.

Change history

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Acknowledgements

C.S. acknowledges funding from the Austrian Science Fund (FWF) Lise Meitner Programme (no. M2652). R.S. acknowledges funding from FWF START grant no. Y895-B25. We thank J. Braaten (Oregon State University) for making the code of LandTrendr open source, which greatly helped in implementation of this research.

Author information

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Authors

Contributions

C.S. and R.S. designed the research. C.S. performed all computations and analyses. C.S. wrote the manuscript with input from R.S.

Corresponding author

Correspondence to Cornelius Senf.

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Extended data

Extended Data Fig. 1 Analysis of map omission and commission errors.

Spectral change magnitude in Tasseled Cap Wetness (TCW), Normalized Burn Ration (NBR), Landsat shortwave-infrared I (B5), and Landsat shortwave-infrared II (B7) for all validation pixels (n = 5,000) with commission errors, omission errors and no error (i.e., matching label between mapped and interpreted). For omission errors, spectral change magnitudes were substantially lower than for correctly classified disturbances, highlighting that many omission errors stem from very low spectral changes, indistinguishable from noise in currently available Landsat-based time series methods.

Extended Data Fig. 2 Validation of the disturbance year.

Estimated disturbance year versus manually interpreted year of disturbance for 5,000 independent reference pixels. The majority of the pixels is on or close to the 1:1-line, indicating that the correct year of disturbance was assigned. The hue indicates data point density (higher hue = more data points).

Extended Data Fig. 3 Validation of disturbance severity.

Distribution of estimated disturbance severities (i.e., the probability that a pixel has lost its complete canopy during disturbance) among pixels classified as stand-replacing disturbances, non-stand-replacing disturbances and undisturbed forest. The classification labels were derived from reference data and are based on a manual interpretation of Landsat time series and auxiliary use of aerial photos. Stand-replacing disturbances have the highest disturbance severities and are well separated from non-stand-replacing disturbances.

Extended Data Fig. 4 Relationship between changing disturbance rates, disturbance frequencies, and disturbance sizes.

Changes in disturbance rates (y-axis; percent of forest area disturbed) in relation to changes in disturbance size (color) and disturbance frequency (x-axis). Trends in disturbance rates are mainly explained by changes in disturbance frequencies (71 %), while changes in disturbance size explained a substantial lower proportion of the variability (24 %).

Extended Data Fig. 5 Country-wise disturbance regime indicators.

Mean disturbance size, frequency and severity summarized for each country of this study. For exact values and other country-wise statistics, please see Supplementary Table 3.

Extended Data Fig. 6 Examples of differences in disturbance regimes among countries with varying forest management.

Differences in spatial disturbance patterns between countries in similar ecoregions and with similar forest types: (1) Central European Mixed Forests with larger and more frequent disturbances in Poland compared to Germany. (2) Alps Conifer and Mixed Forests with substantially higher disturbance frequencies in Austria compared to Italy. (3) Carpathian Montane Forests, with widely varying disturbances sizes and frequencies between Poland, Slovakia and Ukraine. (4) Scandinavian and Russian Taiga with differences in disturbance size between Norway and Sweden. Background maps are from https://gadm.org.

Extended Data Fig. 7 Forest disturbances in Europe 1986-2016.

Large version of the disturbance map shown in Fig. 1a for presentation. Background maps are from https://gadm.org.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2 and Tables 1 and 2.

Reporting Summary

Supplementary Table 3

Country-wise statistics on forest disturbance regimes and their changes over time.

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Senf, C., Seidl, R. Mapping the forest disturbance regimes of Europe. Nat Sustain 4, 63–70 (2021). https://doi.org/10.1038/s41893-020-00609-y

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