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The original version of this Data Descriptor omitted the following information from the Acknowledgements.

Background and Purpose: The structure of the crown volume in a forest stand is one of the main factors that drive the growth and development of trees. It changes dynamically with the age of the forest stand and according to the management activities and natural disturbances that remove trees from the stand. The aim of this article is to analyse crown volume structure in relation to the stand age and diameter at breast height (DBH) of pedunculate oak and common hornbeam trees in one of the most important forest types in Croatia. Materials and Methods: Data for the research were collected from a set of 47 permanent sample plots established as a chronosequence over the distribution range of pedunculate oak and common hornbeam forests in Croatia. The combined area of all the plots amounted to 33.45 ha. Trees were measured for DBH, total height and height to crown base, and a detailed map of crown projection areas was made for each plot. In total, the crowns of 1,609 pedunculate oak trees and 1,979 common hornbeam trees were measured. Crown volumeswere calculated for each tree, the trees were pooled into age classes of 20 years, and analyses were carried out per tree species, per age class. A nonlinear regression with an exponential function of crown volume was performed to establish the relationship between the crown volume and DBH in each age class. Results and Discussion: Up to a stand age of 40 years, crowns of pedunculate oak dominate in the canopy layer (66%), after which crowns of common hornbeam trees assume dominance. Coefficients of determination for the regression lines for pedunculate oak crowns are higher than the coefficients for common hornbeam. In all age classes, they are higher than 0.50, except for the first age class for common hornbeam and the seventh age class for pedunculate oak. The shape of the regression lines of pedunculate oak crown volume shift more to the right side of the diameter range as the stand matures, while those of common hornbeam are more static and form a bundle of lines. Conclusions: Results indicate that the relationship between the crown volume of pedunculate oak and common hornbeam trees and DBH can be described by a nonlinear regression model with an exponential function. Further research is needed to assess the possibilities of integrating the obtained regression models into simulators of forest growth and development.

Richards, Lundqvist-Korf and Hossfeld growth functions were fitted to age-height data of European chestnut (Castanea sativa Mill.) dominant trees on the northern slopes of Belasitsa mountain, Southwest Bulgaria. The model prediction performance was evaluated using quantitative as well as qualitative examinations. Goodness of fit of each model was estimated by the coefficient of determination, F-test for significance of the regression and t-tests for significance of the coefficients of the model. Models were further compared by the evaluation of the standard error of the model and Akaike’s Information Criteria. Site index curves were constructed following the "guide curve method" procedure. In accordance with the evaluation tests, the Richards function was chosen as most adequate to express the age-dominant height relationship. Accordingly, it was further employed as a guide function to derive site index curves for studied chestnut population. It was recommended that the growth model and the site index curves elaborated in the current study are used within the data range 10−110 years., U ovome su radu jednadžbe rasta koje su razvili Richards (jednadžba 1), Lundqvist-Korf (jednadžba 2) i Hossfeld (jednadžba 3) upotrijebljene za modeliranje dominantne visine populacije stabala pitomoga kestena (Castanea sativa Mill.) sa sjevernih ekspozicija planine Belasitsa u jugozapadnoj Bugarskoj. Mogućnost predikcije dominantnih visina pomoću izrađenih modela procijenjena je koristeći kvantitativne i kvalitativne kriterije. Uklapanje linije izjednačenja svakoga modela procijenjena je pomoću koeficijenta determinacije R2, F-testa značajnosti regresije i t-testa značajnosti parametara modela. Nadalje, modeli su međusobno uspoređeni kroz evaluaciju standardne pogreške modela (Sy) i AIC kriterija (Akaike’s Information Criteria). Linije svih upotrijebljenih funkcija rasta zadovoljavajuće naliježu na podatke ovisnosti visine o starosti. Uklapanje linija izjednačenja za sve je modele statistički značajno na razini α < 0.01, pri čemu se objašnjava najmanje 60 % cjelokupne varijabilnosti dominantne visine stabala pitomoga kestena. Funkcija Richardsa pokazala je marginalno bolje rezultate od ostala dva modela s koeficijentom determinacije od R2 = 0.62 (tablica 1). Ovaj je model također imao i najmanje vrijednosti standardne pogreške (Sy) i AIC kriterija. Nadalje, funkcije Lundqvist-Korfa i Hossfelda daju krivulju koja odstupa od asimptotskoga trenda u većoj mjeri nego krivulja Richardsa (slika 1), pri čemu se ova zadnja smatra bližom biološkim zakonitostima rasta. U skladu s provedenim analizama, funkcija Richardsa odabrana je kao najpovoljniji model ovisnosti dominantne visine o starosti, te je dalje upotrijebljena za izradu krivulja indeksa staništa za istraživanu populaciju pitomoga kestena (slika 3). Za određenu starost i dominantnu visinu, indeks staništa može se izraditi i pomoću jednadžbe 10. Dobiveni model visinskoga rasta kao i krivulje indeksa staništa mogu se koristiti u starosnom rasponu od 10 do 110 godina.

Coppice forests in South-Eastern Europe (SEE) cover a broad range of ecological conditions. So far approaches to structure the variety of coppice forests were either highly aggregated or relied on very specific local to regional phytocoenological classification systems which defy a coherent comparison between SEE countries and at European level. To bridge this gap this article presents a methodological approach to allocate current coppice forests in SEE to European forest types (EFT) using readily available information. Te approach is presented by means of the example of Croatia, a country that shares many common features with other countries in SEE with regard to biogeographical and vegetation diversity of forests, but also with regard to the currently used methods for assessment of national forest resources and coppice forests in particular. In the presented approach the map of natural vegetation of Europe (Bohn et al., 2004) is combined with the area of regional forest offices (RFO), the forest area of Corine 2000 land cover map, and the area distribution of 12 coppice management classes within RFOs. Within each RFO, coppice management classes are linked with occurring EFTs. If more than one EFT could be linked with a particular coppice management class, random distribution of coppice forests over eligible EFTs is assumed. In total 499.687 ha (93.6% of the total coppice area) were classified, whereof for 76.4% the classification to EFTs was possible with high confidence, in other cases an approximation was made based on the available information. Te presented methodology appears useful for a rapid stratification of coppice forest resources by the combined use of currently available national data on coppice forests in countries of the SEE region and available data sets at European level. As soon as plot-level national forest inventory data becomes available an evaluation and eventual improvement of the approach will be possible.

Primary forests, defined here as forests where the signs of human impacts, if any, are strongly blurred due to decades without forest management, are scarce in Europe and continue to disappear. Despite these losses, we know little about where these forests occur. Here, we present a comprehensive geodatabase and map of Europe’s known primary forests. Our geodatabase harmonizes 48 different, mostly field-based datasets of primary forests, and contains 18,411 individual patches (41.1 Mha) spread across 33 countries. When available, we provide information on each patch (name, location, naturalness, extent and dominant tree species) and the surrounding landscape (biogeographical regions, protection status, potential natural vegetation, current forest extent). Using Landsat satellite-image time series (1985–2018) we checked each patch for possible disturbance events since primary forests were identified, resulting in 94% of patches free of significant disturbances in the last 30 years. Although knowledge gaps remain, ours is the most comprehensive dataset on primary forests in Europe, and will be useful for ecological studies, and conservation planning to safeguard these unique forests., Measurement(s)Geographic DistributionTechnology Type(s)digital curationFactor Type(s)countrySample Characteristic - Environmentprimary forestSample Characteristic - LocationEurope Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14540625

The mechanistic pathways connecting ocean-atmosphere variability and terrestrial productivity are well-established theoretically, but remain challenging to quantify empirically. Such quantification will greatly improve the assessment and prediction of changes in terrestrial carbon sequestration in response to dynamically induced climatic extremes. The jet stream latitude (JSL) over the North Atlantic-European domain provides a synthetic and robust physical framework that integrates climate variability not accounted for by atmospheric circulation patterns alone. Surface climate impacts of north-south summer JSL displacements are not uniform across Europe, but rather create a northwestern-southeastern dipole in forest productivity and radial-growth anomalies. Summer JSL variability over the eastern North Atlantic-European domain (5-40E) exerts the strongest impact on European beech, inducing anomalies of up to 30% in modelled gross primary productivity and 50% in radial tree growth. The net effects of JSL movements on terrestrial carbon fluxes depend on forest density, carbon stocks, and productivity imbalances across biogeographic regions. Here the authors show that extremes in the summer jet stream position over Europe create a beech forest productivity dipole between northwestern and southeastern Europe and can result in regional anomalies in forest carbon uptake and growth., This work was supported by Fundacio La Caixa through the Junior Leader Program (LCF/BQ/LR18/11640004) and the Universidad Politécnica de Madrid through the Programa Propio (PINV-18-SBSYN2-105-F1TXYR). The following authors acknowledge funding support. I.D.L.: Agnese N. Haury Visiting Scholar & Trainee Fellowship (Laboratory of Tree-Ring Research, University of Arizona), the Mobility Award Jose Castillejo, Ministry of Education, Spanish Government (CAS19/00331) and the Programa de Ayudas Beatriz Galindo, Secretaría de Estado de Universidades, Investigación, Desarrollo e Innovación (#BG20/00065). V.T.: National Science Foundation CAREER grant (AGS-1349942). B.A.: Spanish Ministry of Science and Innovation through the JeDiS project (RTI-2018-096402-B-I00). F.B.: project "Inside out" (#POIR.04.04.00-00-5F85/18-00) funded by the HOMING program of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund. AB, AM, CSZ: Bavarian Ministry of Science and the Arts in the context of the Bavarian Climate Research Network (BayKliF). A.H.: PinCaR project (UHU-1266324) by ERD Funds, Andalucía Regional Government, Consejería de Economía, Conocimiento, Empresas y Universidad 2014-2020. EM-S: Swiss National Science Foundation project TRoxy (No. 200021_175888). A.S.J.: Natural Environment Research Council grants NE/V00929X/1 and NE/S010041/1. J.K., L.M., M.M.T., R.W., M.W.: research training group RESPONSE funded by the German Research Council (DFG Fi 846/8-1, DFG GRK2010). AMP: Romanian Ministry of Research, Innovation, and Digitization, Project-PN-19070506/Ctr. no. 12N/2019. I.C.P.: grant of the Romanian Ministry of Education and Research, CNCS-UEFISCDI within PNCDI III (PN-III-P4-ID-PCE-2020-2696). R.S.S.: DendrOlavide I (EQC2018-005303-P), Ministry of Science, Innovation and Universities, Spain; DendrOlavide II (IE19_074 UPO), VURECLIM (P20_00813) and VULBOS (UPO-1263216). T.L.: Slovenian Research Agency-research core funding no. P4-0107 Program research group "Forest Biology, Ecology and Technology". We thank Virgilio Gómez-Rubio for assistance and advice on the LMM development. We thank Christoph Dittmar, Wolfram Elling, and numerous students of the University of Applied Sciences Weihenstephan-Triesdorf for providing European beech tree-ring chronologies.

Aims: Primary forests are critical for forest biodiversity and provide key ecosystem services. In Europe, these forests are particularly scarce and it is unclear whether they are sufficiently protected. Here we aim to: (a) understand whether extant primary forests are representative of the range of naturally occurring forest types, (b) identify forest types which host enough primary forest under strict protection to meet conservation targets and (c) highlight areas where restoration is needed and feasible. Location: Europe. Methods: We combined a unique geodatabase of primary forests with maps of forest cover, potential natural vegetation, biogeographic regions and protected areas to quantify the proportion of extant primary forest across Europe's forest types and to identify gaps in protection. Using spatial predictions of primary forest locations to account for underreporting of primary forests, we then highlighted areas where restoration could complement protection. Results: We found a substantial bias in primary forest distribution across forest types. Of the 54 forest types we assessed, six had no primary forest at all, and in two-thirds of forest types, less than 1% of forest was primary. Even if generally protected, only ten forest types had more than half of their primary forests strictly protected. Protecting all documented primary forests requires expanding the protected area networks by 1,132km2 (19,194km2 when including also predicted primary forests). Encouragingly, large areas of non-primary forest existed inside protected areas for most types, thus presenting restoration opportunities. Main conclusion: Europe's primary forests are in a perilous state, as also acknowledged by EU's “Biodiversity Strategy for 2030.” Yet, there are considerable opportunities for ensuring better protection and restoring primary forest structure, composition and functioning, at least partially. We advocate integrated policy reforms that explicitly account for the irreplaceable nature of primary forests and ramp up protection and restoration efforts alike.

Aim: Primary forests have high conservation value but are rare in Europe due to his-toric land use. Yet many primary forest patches remain unmapped, and it is unclear to what extent they are effectively protected. Our aim was to (1) compile the most com-prehensive European-scale map of currently known primary forests, (2) analyse the spatial determinants characterizing their location and (3) locate areas where so far unmapped primary forests likely occur.Location: Europe.Methods: We aggregated data from a literature review, online questionnaires and 32 datasets of primary forests. We used boosted regression trees to explore which bio-physical, socio- economic and forest- related variables explain the current distribution of primary forests. Finally, we predicted and mapped the relative likelihood of pri-mary forest occurrence at a 1- km resolution across Europe.Results: Data on primary forests were frequently incomplete or inconsistent among countries. Known primary forests covered 1.4 Mha in 32 countries (0.7% of Europe’s forest area). Most of these forests were protected (89%), but only 46% of them strictly. Primary forests mostly occurred in mountain and boreal areas and were un-evenly distributed across countries, biogeographical regions and forest types. Unmapped primary forests likely occur in the least accessible and populated areas, where forests cover a greater share of land, but wood demand historically has been low.Main conclusions: Despite their outstanding conservation value, primary forests are rare and their current distribution is the result of centuries of land use and forest management. The conservation outlook for primary forests is uncertain as many are not strictly protected and most are small and fragmented, making them prone to ex- tinction debt and human disturbance. Predicting where unmapped primary forests likely occur could guide conservation efforts, especially in Eastern Europe where large areas of primary forest still exist but are being lost at an alarming pace.