Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Abrupt increase in harvested forest area over Europe after 2015

Matters Arising to this article was published on 28 April 2021

Matters Arising to this article was published on 28 April 2021


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.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

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.

Similar content being viewed by others

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,

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,


  1. Forest Europe. State of Europe’s Forests 2015 (Ministerial Conference on the Protection of Forests in Europe, 2015);

  2. Grassi, G. et al. The key role of forests in meeting climate targets requires science for credible mitigation. Nat. Clim. Chang. 7, 220–226 (2017).

    Article  ADS  Google Scholar 

  3. Masson-Delmotte, V. et al. (eds) IPCC 2018: Global Warming of 1.5 °C (Intergovernmental Panel on Climate Change, 2018);

  4. Reid, W. V. et al. Ecosystems and Human Well-being – Synthesis: A Report of the Millennium Ecosystem Assessment (Island Press, 2005).

  5. Duncker, P. et al. Classification of forest management approaches: a new conceptual framework and its applicability to European forestry. Ecol. Soc. 17, 51 (2012).

    Google Scholar 

  6. Schelhaas, M.-J. et al. Actual European forest management by region, tree species and owner based on 714,000 re-measured trees in national forest inventories. PLoS One 13, e0207151 (2018).

    Article  Google Scholar 

  7. European Commission. A New EU Forest Strategy: For Forests and the Forest-Based Sector Communication to the European Parliament Document no. 52013DC0659 (Publications Office of the European Union, 2013);

  8. Alkama, R. & Cescatti, A. Biophysical climate impacts of recent changes in global forest cover. Science 351, 600–604 (2016).

    Article  ADS  CAS  Google Scholar 

  9. Duveiller, G., Hooker, J. & Cescatti, A. The mark of vegetation change on Earth’s surface energy balance. Nat. Commun. 9, 679 (2018).

    Article  ADS  Google Scholar 

  10. Luyssaert, S. et al. Trade-offs in using European forests to meet climate objectives. Nature 562, 259–262 (2018); correction 567, E13 (2019).

    Article  ADS  CAS  Google Scholar 

  11. Le Quéré, C. et al. Global carbon budget 2017. Earth Syst. Sci. Data 10, 405–448 (2018).

    Article  ADS  Google Scholar 

  12. Shukla, P. R. et al. (eds) IPCC, 2019: Climate Change and Land (Intergovernmental Panel on Climate Change, 2019);

  13. United Nations Framework Convention on Climate Change. The Paris Agreement (United Nations, 2015);

  14. European Commission. The European Green Deal Communication to the European Parliament Document no. 52019DC0640 (Publications Office of the European Union, 2019);

  15. Mandl, N. & Pinterits, M. (eds) Annual European Union Greenhouse Gas Inventory 1990–2016 and Inventory Report 2018. EAA Report no. 5/2018 (European Environment Agency, 2018);

  16. Bastrup-Birk, A. et al. European Forest Ecosystems – State and Trends. EAA Report No. 5/2016 (European Environment Agency, 2016);

  17. Pilli, R., Grassi, G., Kurz, W. A., Viñas, R. A. & Guerrero, N. H. Modelling forest carbon stock changes as affected by harvest and natural disturbances. I. Comparison with countries’ estimates for forest management. Carbon Balance Manag. 11, 5 (2016).

    Article  Google Scholar 

  18. Nabuurs, G.-J. et al. First signs of carbon sink saturation in European forest biomass. Nat. Clim. Chang. 3, 792–796 (2013).

    Article  ADS  CAS  Google Scholar 

  19. Kallio, A. M. I. & Solberg, B. On the reliability of international forest sector statistics: problems and needs for improvements. Forests 9, 407 (2018).

    Article  Google Scholar 

  20. Buongiorno, J. On the accuracy of international forest product statistics. Forestry 91, 541–551 (2018).

    Article  Google Scholar 

  21. Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).

    Article  ADS  CAS  Google Scholar 

  22. Gorelick, N. et al. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017).

    Article  ADS  Google Scholar 

  23. Grassi, G., Pilli, R., House, J., Federici, S. & Kurz, W. A. Science-based approach for credible accounting of mitigation in managed forests. Carbon Balance Manag. 13, 8 (2018).

    Article  Google Scholar 

  24. Ericsson, K. & Werner, S. The introduction and expansion of biomass use in Swedish district heating systems. Biomass Bioenergy 94, 57–65 (2016).

    Article  Google Scholar 

  25. Bontemps, S. et al. Consistent global land cover maps for climate modeling communities: current achievements of the ESA’s land cover CCI. In ESA Living Planet Symp. 2013 CCI-4 (ESA, 2013).

  26. Wolf-Crowther, M., Mozes, C. & Laczko, R. (eds) Forestry in the EU and the World: A Statistical Portrait (Eurostat, 2011);

  27. Santoro, M. GlobBiomass – Global Datasets of Forest Biomass (PANGAEA, 2018).

  28. Noss, R. F. Assessing and monitoring forest biodiversity: a suggested framework and indicators. For. Ecol. Manage. 115, 135–146 (1999).

    Article  Google Scholar 

  29. Wilcox, B. A. & Murphy, D. D. Conservation strategy the effects of fragmentation on extinction. Am. Nat. 125, 879–887 (1985).

    Article  Google Scholar 

  30. FAOSTAT. Forest Land (Food and Agriculture Organization of the United Nations, 2019);

  31. Levers, C. et al. Drivers of forest harvesting intensity patterns in Europe. For. Ecol. Manage. 315, 160–172 (2014).

    Article  Google Scholar 

  32. Eurostat. Economic Aggregates of Forestry (2019).

  33. Forestry and Timber – UNECE. Forest Products Annual Market Review, 2017–2018 (United Nations, 2018);

  34. European Commission. Bioeconomy: the European way to use our natural resources  (European Commission, 2018);

  35. European Parliament. The Promotion of the Use of Energy from Renewable Sources Directive of the European Parliament Document no. 32018L2001 (Publications Office of the European Union, 2018);

  36. Searchinger, T. D. et al. Europe’s renewable energy directive poised to harm global forests. Nat. Commun. 9, 3741 (2018).

    Article  ADS  Google Scholar 

  37. European Parliament. The Inclusion of Greenhouse Gas Emissions and Removals from Land Use, Land Use Change and Forestry in the 2030 Climate and Energy Framework Regulation of the European Parliament Document no. 32018R0841 (Publications Office of the European Union, 2018);

  38. Achard, F. et al. Determination of tropical deforestation rates and related carbon losses from 1990 to 2010. Glob. Change Biol. 20, 2540–2554 (2014).

    Article  ADS  Google Scholar 

  39. Gibbs, H. K., Brown, S., Niles, J. O. & Foley, J. A. Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environ. Res. Lett. 2, 045023 (2007).

    Article  ADS  Google Scholar 

  40. Hansen, M. C., Stehman, S. V. & Potapov, P. V. Quantification of global gross forest cover loss. Proc. Natl Acad. Sci. USA 107, 8650–8655 (2010).

    Article  ADS  CAS  Google Scholar 

  41. Nabuurs, G.-J. et al. Next-generation information to support a sustainable course for European forests. Nat. Sustain. 2, 815–818 (2019).

    Article  Google Scholar 

  42. European Space Agency. Copernicus Open Access Hub (2015).

  43. Zhu, Z. et al. Benefits of the free and open Landsat data policy. Remote Sens. Environ. 224, 382–385 (2019).

    Article  ADS  Google Scholar 

  44. European Commission. Stepping Up EU Action to Protect and Restore the World’s Forests Communication to the European Parliament Document no. 52019DC0352 (European Commission, 2019);

  45. UNFCCC. Report of the Conference of the Parties on its Seventh Session (United Nations Framework Convention on Climate Change, 2001);

  46. Potapov, P. V. et al. Eastern Europe’s forest cover dynamics from 1985 to 2012 quantified from the full Landsat archive. Remote Sens. Environ. 159, 28–43 (2015).

    Article  ADS  Google Scholar 

  47. Food and Agriculture Organization of the United Nations. Global Forest Resources Assessment 2015 (Food and Agriculture Organization of the United Nations, 2015);

  48. Tyukavina, A. et al. Types and rates of forest disturbance in Brazilian Legal Amazon, 2000–2013. Sci. Adv. 3, e1601047 (2017).

    Article  ADS  Google Scholar 

  49. McNicol, I. M., Ryan, C. M. & Mitchard, E. T. A. Carbon losses from deforestation and widespread degradation offset by extensive growth in African woodlands. Nat. Commun. 9, 3045 (2018).

    Article  ADS  Google Scholar 

  50. Baccini, A., Walker, W., Carvalho, L., Farina, M. & Houghton, R. A. Response to Comment on “Tropical forests are a net carbon source based on aboveground measurements of gain and loss”. Science 363, eaat1205 (2019).

    Article  CAS  Google Scholar 

  51. Ballin, M., Barcaroli, G., Masselli, M. & Scarnó, M. Redesign Sample for Land Use/Cover Area Frame Survey (LUCAS) 2018 (Eurostat, 2018).

  52. EFFIS. Statistics Portal (EFFIS, 2019).

  53. Gardiner, B. et al. Destructive Storms in European Forests: Past and Forthcoming Impacts (European Forest Institute, 2010).

  54. Hengeveld, G. et al. A Forest Management Map of European Forests. Ecol. Soc. 17, 53 (2012).

    Article  Google Scholar 

  55. Vaahtera, E. et al. Finnish Forest Statistics (Natural Resources Institute Finland (Luonnonvarakeskuksen), 2018);

  56. Sweden Statistical Database (2019).

  57. National Forestry Accounting Plan for Austria (Bundesministerium Nachhaltigkeit und Tourismus, 2018);

  58. Foglar-Deinhardstein, A., Hangler, J. & Prem, J. (eds) Sustainable Forest Management in Austria, Austrian Forest Report 2008 (Federal Ministry of Agriculture, Republic of Austria, 2008).

  59. Institut Européen De La Forêt Cultivée. Forestorm

  60. Stoeva, L., Markoff, I. & Zhiyanski, M. National Forestry Accounting Plan for Bulgaria, Including Forest Reference Levels for the Period 2021–2025 (Ministry of Environment and Water, Republic of Bulgaria, 2018);

  61. National Forestry Accounting Plan For The Republic Of Croatia (Ministry of Environment and Energy and Ministry of Agriculture, Republic of Croatia, 2018);

  62. Ministry of Agriculture & Ministry of the Environment, Czech Republic. National Forestry Accounting Plan For The Czech Republic, Including A Proposed Forest Reference Level (Ministry of Agriculture and Ministry of the Environment, Czech Republic, 2018);

  63. Cienciala, E. et al. Recent spruce decline with biotic pathogen infestation as a result of interacting climate, deposition and soil variables. Eur. J. For. Res. 136, 307–317 (2017).

    Article  Google Scholar 

  64. Johannsen, V. K., Nord-Larsen, T., Scott Bentsen, N. & Vesterdal, L. Danish National Forest Accounting Plan 2021–2030 (University of Copenhagen, 2019);

  65. Finnish Forest Sector Economic Outlook (2019).

  66. Somogyi, Z. et al. National Forest Accounting Plan of Hungary (2021–2025) (2018);

  67. Gasparini, P., Di Cosmo, L., Cenni, E., Pompei, E. & Ferretti, M. Towards the harmonization between National Forest Inventory and Forest Condition Monitoring. Consistency of plot allocation and effect of tree selection methods on sample statistics in Italy. Environ. Monit. Assess. 185, 6155–6171 (2013).

    Article  CAS  Google Scholar 

  68. State Forest Service, Environment Protection and Forest Department & Aleksandras Stulginskis University. National Forestry Accounting Plan by Lithuania (Ministry of the Environment, 2018);

  69. FAOSTAT. Forestry Production and Trade (Food and Agriculture Organization of the United Nations, 2019).

  70. Ministry of the Environment. Poland National Forestry Accounting Plan (NFAP) (2018);

  71. Barka, I., Priwitzer, T. & Hušťáková, E. National Forestry Accounting Plan of the Slovak Republic Including a Proposed Forest Reference Level (Ministry of Agriculture and Rural Development of the Slovak Republic, National Forest Centre, 2018);

  72. National Forestry Accounting Plan for Spain (2018);

  73. United Nations Climate Change. National Inventory Submissions 2019 (UNFCCC, 2019).

  74. Nabuurs, G.-J., Arets, E. J. M. M. & Schelhaas, M.-J. Understanding the implications of the EU-LULUCF regulation for the wood supply from EU forests to the EU. Carbon Balance Manag. 13, 18 (2018).

    Article  Google Scholar 

  75. Joint Research Centre. Brief on Biomass for Energy in the European Union (European Commission, 2019);

  76. Hoepffner, N. et al. Biomass Production, Supply, Uses and Flows in the European Union: First Results From an Integrated Assessment (European Commission, 2018);

  77. Slovenian National Forestry Accounting Plan, Including Forest Reference Levels – Draft (2018);

  78. National Forestry Accounting Plan for Sweden (2018);

  79. Grassi, G. et al. Wrong premises mislead the conclusions by Kallio et al. on forest reference levels in the EU. For. Policy Econ. 95, 10–12 (2018).

    Article  Google Scholar 

  80. Kallio, A. M. I., Solberg, B., Käär, L. & Päivinen, R. Economic impacts of setting reference levels for the forest carbon sinks in the EU on the European forest sector. For. Policy Econ. 92, 193–201 (2018).

    Article  Google Scholar 

Download references


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.

Author information

Authors and Affiliations



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.

Corresponding author

Correspondence to Guido Ceccherini.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Mathew Williams and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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.

Supplementary information

Supplementary Information

This file contains Supplementary Figures 1-6 and Supplementary Table 1.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ceccherini, G., Duveiller, G., Grassi, G. et al. Abrupt increase in harvested forest area over Europe after 2015. Nature 583, 72–77 (2020).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing Anthropocene

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Anthropocene