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Abrupt increase in harvested forest area over Europe after 2015

Nature volume 583, pages 72–77 (2020)Cite this article

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Matters Arising to this article was published on 28 April 2021

Matters Arising to this article was published on 28 April 2021

Abstract

Forests provide a series of ecosystem services that are crucial to our society. In the European Union (EU), forests account for approximately 38% of the total land surface1. These forests are important carbon sinks, and their conservation efforts are vital for the EU’s vision of achieving climate neutrality by 20502. However, the increasing demand for forest services and products, driven by the bioeconomy, poses challenges for sustainable forest management. Here we use fine-scale satellite data to observe an increase in the harvested forest area (49 per cent) and an increase in biomass loss (69 per cent) over Europe for the period of 2016–2018 relative to 2011–2015, with large losses occurring on the Iberian Peninsula and in the Nordic and Baltic countries. Satellite imagery further reveals that the average patch size of harvested area increased by 34 per cent across Europe, with potential effects on biodiversity, soil erosion and water regulation. The increase in the rate of forest harvest is the result of the recent expansion of wood markets, as suggested by econometric indicators on forestry, wood-based bioenergy and international trade. If such a high rate of forest harvest continues, the post-2020 EU vision of forest-based climate mitigation may be hampered, and the additional carbon losses from forests would require extra emission reductions in other sectors in order to reach climate neutrality by 20503.

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Fig. 1: Harvested forest area per year.
Fig. 2: Spatial statistics of European harvested forest area.
Fig. 3: Temporal trends of forest harvests.
Fig. 4: Mean harvested-patch size and recent change by country.

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Data availability

To ensure full reproducibility and transparency of our research, we provide all of the data analysed during the current study. The data are permanently and publicly available on a Zenodo repository, https://doi.org/10.5281/zenodo.3687090.

Code availability

To ensure full reproducibility and transparency of our research, we provide all of the scripts used in our analysis. Codes used for this study (Google Earth Engine and R scripts, the harvest-removals dataset and shapefiles of the validation) are permanently and publicly available on a Zenodo repository, https://doi.org/10.5281/zenodo.3687096.

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Acknowledgements

The views expressed are purely those of the writers and may not in any circumstances be regarded as stating an official position of the European Commission.

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Authors and Affiliations

  1. Bio-Economy Unit, European Commission Joint Research Centre, Ispra, Italy

    Guido Ceccherini, Gregory Duveiller, Giacomo Grassi, Valerio Avitabile, Roberto Pilli & Alessandro Cescatti

  2. Food Security Unit, European Commission Joint Research Centre, Ispra, Italy

    Guido Lemoine

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  1. Guido Ceccherini
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Contributions

G.C. and A.C. conceived the idea and designed the methodology; G.C. analysed the data and wrote the Google Earth Engine and R scripts; G.C. and A.C. wrote the manuscript with contributions from G.D., G.L., V.A., R.P. and G.G.. All authors contributed critically to the interpretation of the results and gave final approval for publication.

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Correspondence to Guido Ceccherini.

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Extended data figures and tables

Extended Data Fig. 1 From tree cover to forest cover.

a, Tree-cover threshold needed to define a forest (colours) and percentage error between FAOSTAT-2015 and remote-sensing-based forests (labels). b, Forest threshold sensitivity. Maps were generated using GEE22.

Extended Data Fig. 2 Verification of EU forest area.

a, GFC data versus FAOSTAT for 2000 and 2010. b, GFC data versus LUCAS for 2009, 2012 and 2015.

Extended Data Fig. 3 Validation of GFC-derived forest loss with high-resolution data.

a, b, Validation of the classification of harvested areas in the years 2012 and 2017 by forest patches of sizes small (≤0.27 ha) and large (>0.27 ha and ≤4.5 ha; a), and big (>4.5 ha; b). c, Accuracy of harvest area derived from GFC-derived forest loss versus patch size (labels and circle size refer to the EU26-wise cumulative harvested forest).

Extended Data Fig. 4 Harvested forest area by forest type.

Time series of land cover type (from GlobCover)25 for EU26. Colours refer to the three forest types: mixed, broadleaf and needleleaf.

Extended Data Fig. 5 Harvested forest area components.

a, b, Annual distribution of harvested forest for different classes of patch size, ranging from small patches (harvested forest area less than 0.27 ha) to big patches (harvested forest area greater than 7.2 ha) for all of EU26 (a), each EU26 country (b).

Extended Data Fig. 6 GFC-derived harvested forest area versus official harvest removal data.

Harvested forest area from the GFC maps (red bars, normalized between 0 and 1) and volumes of harvest removals from national statistics (black lines, normalized between 0 and 1). We excluded areas affected by forest fires and retained areas affectedby major windstorms because they appear in the harvest removal data. Statistical significance at P = 0.05 for remote sensing and national statistics is indicated by an asterisk and a hash, respectively, in the country label panels. The value in brackets is the correlation coefficient, r. Maximum values of harvested forest area and official harvest removal data for each country are reported in the second and third lines of each label, respectively.

Extended Data Fig. 7 Harvested forest area versus Eurostat32 economic aggregates.

Harvested forest area from the GFC maps (red bars, normalized between 0 and 1) and volumes of economic aggregates of forestry from Eurostat data (black lines, normalized between 0 and 1). We excluded areas affected by forest fires and retained areas affected by major windstorms because they appear in the harvest removal data. Percentages in the first and second brackets after the country label refer to the percentage change 2008–2016 (or 2012–2016 when 2008 records are not available) of remote sensing and market value, respectively. Maximum values of harvested forest area and volumes of economic aggregates of forestry for each country are reported in the second and third lines of each label, respectively.

Extended Data Fig. 8 Harvested forest biomass per year.

Percentage of AGB harvested (expressed as relative amount of biomass affected by management practices) per year in a 0.2° grid cell excluding forest losses due to fires and major windstorms and areas with sparse forest cover. As in Fig. 1 but measuring biomass instead. This map was generated using GEE22.

Extended Data Fig. 9 Cloud-free land coverage of Landsat in Europe.

a, Time series of cloud-free Landsat scenes (cloud cover less than 20%) for EU26. b, Spatial distribution of cloud-free Landsat images over Europe. Grey areas indicate where no data was available for the selected year using satellite imagery. Map and time series were generated using GEE22.

Extended Data Fig. 10 Growth rates of forest biomass.

a, b, Relative (a) and absolute (b) growth rate of forest biomass as derived from the State of Europe’s Forests 2015 report1 in combination with GlobBiomass27 and GFC21 data. The data in a are given over five European regions, with colours corresponding to the colour scale: north (yellow), central west (green), central east (lime), south west (purple) and south east (blue). Maps were generated using GEE22.

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Ceccherini, G., Duveiller, G., Grassi, G. et al. Abrupt increase in harvested forest area over Europe after 2015. Nature 583, 72–77 (2020). https://doi.org/10.1038/s41586-020-2438-y

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  1. Mike W

    This is an excellent and timely report.
    It is concerning that energy fueled by wood-burning, is expanding and that this is widely perceived as a "green alternative" to coal-based power plants. Reports regarding power production from so called green energy initiatives including wind turbines, hydro-electric plants and solar energy, should not be grouped together with energy from wood burning.
    This "green initiative" appears to be yet another way we are actively destroying our planet.

  2. Jacek Kozak

    The research uses data from the Global Forest Change (GFC) map published by Hansen et al. (2013) and updated till 2019. While the results and most conclusions of the authors seem to be convincing as far as the dynamics of harvested forest area in Europe is concerned, the methods proposed in the paper to process GFC data to receive forest cover estimates in Europe should be proposed with great caution for an analysis to be carried out elsewhere or for other purposes.
    GFC is a breakthrough achievement of the contemporary remote sensing, offering a dense temporal series of global tree cover dynamics with a high spatial resolution based on thousands of processed Landsat scenes. The data available in GFC, globally consistent, provide therefore a valuable information on the dynamics of forest cover, especially in quickly deforested areas. GFC, however, is not strictly speaking ‘a forest map’ as, for a given moment in time, it presents exclusively land cover information related to tree cover, without any reference to land use which, in various definitions of ‘forest’ is an inevitable part of the definition or legal regulations.
    Though the authors of the commented paper are aware of a variety of forest definitions, and acknowledge the fact that GFC uses a land cover based forest definition only (Methods section), they propose “a simple approach towards defining for each EU26 country the minimum tree cover (percentage) that qualifies as forest using the GFC maps”. The approach relies on adjusting the tree cover in each country so as to receive forested area equal to forest area recorded in independent sources (in case of the commented study, FAOSTAT).
    The use of GFC data in a forest-related study may in fact imply accepting a certain tree cover threshold to divide GFC into a ‘forest’ and ‘non-forest’ spatial masks and thus receive a reference area for analysis. Its value, however, remains exclusively operational. Regardless how complex the procedure to find the right threshold value is, no reasonable tree cover threshold can eliminate two types of discrepancies between GFC and the real forest cover that occur in most European countries:
    - ‘false forests’, that is areas with a dense (close to 100%) tree cover that are not under forest management – for instance, urban green areas,
    - ‘false non-forests’ that is areas with no or scarce tree cover that are under forest management – for instance, areas of salvation logging following windstorms or pests.
    The authors of the study are aware of these caveats related to the use of GFC to approximate forest cover (Methods section). Therefore, for clarity, they should not refer to the proposed solution as “From tree cover to forest cover” (a sub-section heading in the Methods sections), because such a wording wrongly suggests that the authors have found and proposed a valid method that adjusts, in some mysterious way, boundaries based on the occurrence of trees in the landscape to forest boundaries coherent with national forest definitions and their land use component.
    It is striking that the authors have not considered to use ancillary data to eliminate, at least partially, ‘false forests’ and ‘false non-forests’ from GFC. For instance, Corine Land Cover, though with low spatial resolution related to its minimum mapping unit of 25 ha, maps various land use and land cover classes that include ‘trees outside forests’ (that is, ‘false forests’), like urban green areas and orchards as well as ‘false non-forests’, e.g., areas affected by major windstorms or forest fires that are included in the ‘transitional woodland-shrub’ or ‘burnt areas’ classes.

  3. kiiski

    Incorrect figures on harvested forests in Nature article
    https://www.slu.se/en/ew-ne...

  4. Aleksi Lehtonen

    According to EU GHG inventory by DG Clima supported by JRC (Joint Research Centre) mean annual biomass losses were -122953.67 Kt C and -134233.58 Kt C for periods of 2011-2015 and 2016-2018, respectively for forest land. Therefore, statistics compiled by JRC to UNFCCC under convention [https://unfccc.int/ghg-inve...] show that biomass losses have increased by 9% with EU-28 between 2011-2015 and 2016-2018. Biomass losses include harvested biomass and that of natural mortality. According to Ceccherini et al. 2020 (JRC) increase in biomass loss has been 69% between periods of 2011-2015 and 2016-2018. There seems the be a substantial gap between official GHG statistics (9%) and the estimate by Ceccherini et al. 2020 (69%). Official GHG statistics have been based on national forest inventories and also on national harvesting statistics. While, the analysis of Ceccherini et al. 2020 builds on optical satellite images.

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