The growth of past, present, and future forests was, is and will be affected by climate variability. This multifaceted relationship has been assessed in several regional studies, but spatially resolved, large-scale analyses are largely missing so far. Here we estimate recent changes in growth of 5800 beech trees (Fagus sylvatica L.) from 324 sites, representing the full geographic and climatic range of species. Future growth trends were predicted considering state-of-the-art climate scenarios. The validated models indicate growth declines across large region of the distribution in recent decades, and project severe future growth declines ranging from -20% to more than -50% by 2090, depending on the region and climate change scenario (i.e. CMIP6 SSP1-2.6 and SSP5-8.5). Forecasted forest productivity losses are most striking towards the southern distribution limit of Fagus sylvatica, in regions where persisting atmospheric high-pressure systems are expected to increase drought severity. The projected 21st century growth changes across Europe indicate serious ecological and economic consequences that require immediate forest adaptation.

Applied Vegetation Ecology Faculty of Environment and Natural Resources University of Freiburg Freiburg Germany

Biological and Environmental Sciences Faculty of Natural Sciences University of Stirling Stirling Scotland

Biotechnical Faculty Department of Wood Science and Technology University of Ljubljana Ljubljana Slovenia

Chair of Forest Growth and Woody Biomass Production TU Dresden Tharandt Germany

Departamento de Sistemas y Recursos Naturales Escuela Técnica Superior de Ingeniería de Montes Forestal y del Medio Natural Universidad Politécnica de Madrid Madrid Spain

Department of Agriculture Forestry and Food Sciences University of Turin Grugliasco Italy

Department of Crop and Forest Sciences and Joint Research Unit CTFC AGROTECNIO CERCA Center University of Lleida Lleida Spain

Department of Earth and Environmental Sciences University of Pavia Pavia Italy

Department of Forestry University of Applied Sciences Weihenstephan Triesdorf Triesdorf Germany

Department of Geography and Planning School of Environmental Sciences University of Liverpool Liverpool UK

Department of Geography and Regional Planning University of Zaragoza Zaragoza Spain

Department of Geography Autonomous University of Madrid Madrid Spain

Department of Geography Johannes Gutenberg University Mainz Germany

Faculty of Forestry and Wood Sciences Czech University of Life Sciences Prague Czech Republic

Faculty of Forestry and Wood Technology University of Zagreb Zagreb Croatia

Faculty of Forestry Sciences Agricultural University of Tirana Koder Kamez Albania

Faculty of Silviculture and Forest Engineering University of Brasov Brașov Romania

Forest Dynamics Swiss Federal Research Institute for Forest Snow and Landscape WSL Birmendorf Switzerland

Forest Resources Department Centro de Investigación y Tecnología Agroalimentaria de Aragón Zaragoza Spain

Global Change Research Institute of the Czech Academy of Sciences Brno Czech Republic

Institute for Botany and Landscape Ecology University Greifswald Greifswald Germany

Institute of Biodiversity and Ecosystem Research Bulgarian Academy of Sciences Sofia Bulgaria

Institute of Forest Ecosystems Thünen Institute Eberswalde Germany

Land Surface Atmosphere Interactions Technical University Munich Freising Germany

National Institute for Research and Development in Forestry Marin Dracea Voluntari Romania

Nature Rings Environmental Research and Education Mainz Germany

Plant Ecology Albrecht von Haller Institute for Plant Sciences University of Goettingen Goettingen Germany

School of Life Science and Engineering Southwest University of Science and Technology Mianyang China

Slovenian Forestry Institute Ljubljana Slovenia

Systems and Natural Resources Department Universidad Politécnica de Madrid Madrid Spain

TERRA Teaching and Research Centre Gembloux Agro Bio Tech University of Liege Gembloux Belgium

TUM School of Life Sciences Ecoclimatology Technical University of Munich Munich Germany

University of Belgrade Faculty of Forestry Belgrade Serbia

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IPCC. IPCC Fifth Assessment Report (AR5). 10–12 (IPCC, 2014).

Cailleret M, et al. A synthesis of radial growth patterns preceding tree mortality. Glob. Chang. Biol. 2017;23:1675–1690. PubMed

Forzieri G, et al. Emergent vulnerability to climate-driven disturbances in European forests. Nat. Commun. 2021;12:1–12. PubMed PMC

Bonan GB. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science. 2008 doi: 10.1126/science.1155121. PubMed DOI

Buras A, Menzel A. Projecting tree species composition changes of European forests for 2061–2090 under RCP 4.5 and RCP 8.5 scenarios. Front. Plant Sci. 2019;9:1–13. PubMed PMC

van der Maaten E, et al. Species distribution models predict temporal but not spatial variation in forest growth. Ecol. Evol. 2017;7:2585–2594. PubMed PMC

Lebaube S, Le Goff NL, Ottorini JM, Granier A. Carbon balance and tree growth in a Fagus sylvatica stand. Ann. Sci. 2000;57:49–61.

Dobbertin M. Tree growth as indicator of tree vitality and of tree reaction to environmental stress: a review. Eur. J. For. Res. 2005;124:319–333.

Büntgen U. Re-thinking the boundaries of dendrochronology. Dendrochronologia. 2019;53:1–4.

Klesse S, et al. Continental-scale tree-ring-based projection of Douglas-fir growth: Testing the limits of space-for-time substitution. Glob. Chang. Biol. 2020;26:5146–5163. PubMed

Zhao S, et al. The International Tree-Ring Data Bank (ITRDB) revisited: data availability and global ecological representativity. J. Biogeogr. 2019;46:355–368.

Babst F, et al. When tree rings go global: challenges and opportunities for retro- and prospective insight. Quat. Sci. Rev. 2018;197:1–20.

Klesse S, et al. Sampling bias overestimates climate change impacts on forest growth in the southwestern United States. Nat. Commun. 2018;9:1–9. PubMed PMC

Yousefpour R, et al. Realizing mitigation efficiency of European commercial forests by climate smart forestry. Sci. Rep. 2018;8:1–11. PubMed PMC

Giesecke T, Hickler T, Kunkel T, Sykes MT, Bradshaw RHW. Towards an understanding of the Holocene distribution of Fagus sylvatica L. J. Biogeogr. 2007;34:118–131.

Fang J, Lechowicz MJ. Climatic limits for the present distribution of beech (Fagus L.) species in the world. J. Biogeogr. 2006;33:1804–1819.

Luterbacher J, Dietrich D, Xoplaki E, Grosjean M, Wanner H. European seasonal and annual temperature variability, trends, and extremes since 1500. Science. 2004;303:1499–1503. PubMed

Luterbacher, J. et al. European summer temperatures since Roman times. Environ. Res. Lett. 11, 24001 (2016).

Nabuurs GJ, et al. By 2050 the mitigation effects of EU forests could nearly double through climate smart forestry. Forests. 2017;8:1–14.

Walentowski H, et al. Assessing future suitability of tree species under climate change by multiple methods: a case study in southern Germany. Ann. Res. 2017;60:101–126.

Mäkelä A, et al. Process-based models for forest ecosystem management: current state of the art and challenges for practical implementation. Tree Physiol. 2000;20:289–298. PubMed

Leech SM, Almuedo PL, Neill GO. Assisted migration: adapting forest management to a changing climate. BC J. Ecosyst. Manag. 2011;12:18–34.

Sass-Klaassen UGW, et al. A tree-centered approach to assess impacts of extreme climatic events on forests. Front. Plant Sci. 2016;7:1069. PubMed PMC

Bowman DMJS, Brienen RJW, Gloor E, Phillips OL, Prior LD. Detecting trends in tree growth: not so simple. Trends Plant Sci. 2013;18:11–17. PubMed

Hacket-Pain AJ, et al. Climatically controlled reproduction drives interannual growth variability in a temperate tree species. Ecol. Lett. 2018;21:1833–1844. PubMed PMC

Dorji, Y., Annighöfer, P., Ammer, C. & Seidel, D. Response of beech (Fagus sylvatica L.) trees to competition-new insights from using fractal analysis. Remote Sens. 11, 2656 (2019).

Petit-Cailleux, C. et al. Combining statistical and mechanistic models to unravel the drivers of mortality within a rear-edge beech population. bioRxiv10.1101/645747 (2019).

Weigel R, Gilles J, Klisz M, Manthey M, Kreyling J. Forest understory vegetation is more related to soil than to climate towards the cold distribution margin of European beech. J. Veg. Sci. 2019;30:746–755.

Etzold S, et al. Nitrogen deposition is the most important environmental driver of growth of pure, even-aged and managed European forests. Forest Ecol. Manag. 2020;458:117762.

Martínez-Sancho E, et al. The GenTree dendroecological collection, tree-ring and wood density data from seven tree species across Europe. Sci. Data. 2020;7:1–7. PubMed PMC

Hartl-Meier C, Dittmar C, Zang C, Rothe A. Mountain forest growth response to climate change in the Northern Limestone Alps. Trees. 2014;28:819–829.

Way DA, Montgomery RA. Photoperiod constraints on tree phenology, performance and migration in a warming world. Plant Cell Environ. 2015;38:1725–1736. PubMed

Martínez del Castillo E, et al. Spatial patterns of climate – growth relationships across species distribution as a forest management tool in Moncayo Natural Park (Spain) Eur. J. Res. 2019;138:299.

Hacket-Pain AJ, Cavin L, Friend AD, Jump AS. Consistent limitation of growth by high temperature and low precipitation from range core to southern edge of European beech indicates widespread vulnerability to changing climate. Eur. J. Res. 2016;135:897–909.

van der Maaten E. Climate sensitivity of radial growth in European beech (Fagus sylvatica L.) at different aspects in southwestern Germany. Trees. 2012;26:777–788.

Decuyper M, et al. Spatio-temporal assessment of beech growth in relation to climate extremes in Slovenia – an integrated approach using remote sensing and tree-ring data. Agric. Meteorol. 2020;287:107925.

Kraus C, Zang C, Menzel A. Elevational response in leaf and xylem phenology reveals different prolongation of growing period of common beech and Norway spruce under warming conditions in the Bavarian Alps. Eur. J. Res. 2016;135:1011–1023.

Martínez del Castillo E, et al. Living on the edge: contrasted wood-formation dynamics in Fagus sylvatica and Pinus sylvestris under mediterranean conditions. Front. Plant Sci. 2016;7:370. PubMed PMC

Čufar K, et al. Temporal shifts in leaf phenology of beech (Fagus sylvatica) depend on elevation. Trees. 2012;26:1091–1100.

Bontemps JD, Hervé JC, Dhôte JF. Dominant radial and height growth reveal comparable historical variations for common beech in north-eastern France. Forest Ecol. Manag. 2010;259:1455–1463.

Latte N, Lebourgeois F, Claessens H. Increased tree-growth synchronization of beech (Fagus sylvatica L.) in response to climate change in northwestern Europe. Dendrochronologia. 2015;33:69–77.

Zimmermann J, Hauck M, Dulamsuren C, Leuschner C. Climate warming-related growth decline affects Fagus sylvatica, but not other broad-leaved tree species in central european mixed forests. Ecosystems. 2015;18:560–572.

Tegel W, et al. A recent growth increase of European beech (Fagus sylvatica L.) at its Mediterranean distribution limit contradicts drought stress. Eur. J. Res. 2014;133:61–71.

Hacket-Pain AJ, Friend AD. Increased growth and reduced summer drought limitation at the southern limit of Fagus sylvatica L., despite regionally warmer and drier conditions. Dendrochronologia. 2017;44:22–30.

Dulamsuren C, Hauck M, Kopp G, Ruff M, Leuschner C. European beech responds to climate change with growth decline at lower, and growth increase at higher elevations in the center of its distribution range (SW Germany) Trees. 2017;31:673–686.

Spiecker, H., Mielikäinen, K., Köhl, M. & Skovsgaard, J. P. Growth trends in European forests: studies from 12 countries. European Forest Institute Research Report (1996).

Cavin L, Jump AS. Highest drought sensitivity and lowest resistance to growth suppression are found in the range core of the tree Fagus sylvatica L. not the equatorial range edge. Glob. Chang. Biol. 2016;23:1–18. PubMed

Mette T, et al. Climatic turning point for beech and oak under climate change in Central Europe. Ecosphere. 2013;4:1–19.

Michelot A, Simard S, Rathgeber CBK, Dufrêne E, Damesin C. Comparing the intra-annual wood formation of three European species (Fagus sylvatica, Quercus petraea and Pinus sylvestris) as related to leaf phenology and non-structural carbohydrate dynamics. Tree Physiol. 2012;32:1033–1045. PubMed

Meier IC, Leuschner C. Belowground drought response of European beech: Fine root biomass and carbon partitioning in 14 mature stands across a precipitation gradient. Glob. Chang. Biol. 2008;14:2081–2095.

Leuschner, C. & Ellenberg, H. Ecology of Central European Forests. Vegetation Ecology of Central Europe. Vol. I (Springer, 2017).

Allen CD, Breshears DD, McDowell NG. On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene. Ecosphere. 2015;6:1–55.

Pechanec, V., Purkyt, J., Benc, A., Nwaogu, C. & Lenka, Š. Ecological Informatics Modelling of the carbon sequestration and its prediction under climate change. 10.1016/j.ecoinf.2017.08.006 (2017).

Speer, J. H. Fundamentals of Tree-Ring Research (University of Arizona Press, 2010).

Biondi F, Qeadan F. A theory-driven approach to tree-ring standardization: defining the biological trend from expected basal area increment. Tree-Ring Res. 2008;64:81–96.

Biondi, F. & Qeadan, F. Removing the tree-ring width biological trend using expected basal area increment. in USDA Forest Service RMRS-P-55 124–131 (2008).

Karger DN, et al. Climatologies at high resolution for the earth’s land surface areas. Sci. Data. 2017;4:1–20. PubMed PMC

De Martonne, E. Une nouvelle fonction climatologique: L’indice d’aridité. La Meteorol. 2, 449–458 (1926).

Martínez del Castillo E, Longares LA, Serrano-Notivoli R, de Luis M. Modeling tree-growth: assessing climate suitability of temperate forests growing in Moncayo Natural Park (Spain) . Ecol. Manag. 2019;435:128–137.

Bolker BM, et al. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol. Evol. 2009;24:127–135. PubMed

Calcagno V, Mazancourt C. De. glmulti: an R package for easy automated model selection with (generalized) linear models. J. Stat. Softw. 2010;34:1–29.

Detry MA, Ma Y. Analyzing repeated measurements using mixed models. JAMA J. Am. Med. Assoc. 2016;315:407. PubMed

Harrison XA, et al. A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ. 2018;2018:1–32. PubMed PMC

Johnson JB, Omland KS. Model selection in ecology and evolution. Trends Ecol. Evol. 2004;19:101–108. PubMed

Caudullo G, Welk E, San-Miguel-Ayanz J. Chorological maps for the main European woody species. Data Brief. 2017;12:662–666. PubMed PMC

Meinshausen M, et al. The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500. Geosci. Model Dev. 2020;13:3571–3605.

Karger, D. N. & Zimmermann, N. E. CHELSAcruts - High Resolution Temperature And Precipitation Timeseries For The 20th Century And Beyond. 10.16904/envidat.159 (2018).

Norinder U, Rybacka A, Andersson PL. Conformal prediction to define applicability domain - a case study on predicting ER and AR binding. SAR QSAR Environ. Res. 2016;27:303–316. PubMed

Metzger MJ, Bunce RGH, Jongman RHG, Mücher CA, Watkins JW. A climatic stratification of the environment of Europe. Glob. Ecol. Biogeogr. 2005;14:549–563.