Eleonora Cagliero

Donato Morresi

Laure Paradis

Milic Curovic

Velibor Spalevic

Niccolò Marchi

Fabio Meloni

Ilham Bentaleb

Renzo Motta

Matteo Garbarino

Milić Čurović

Emanuele Lingua

Walter Finsinger
email: walter.finsinger@umontpellier.fr

Legacies of past human activities on one of the largest old-growth forests in the south-east European mountains

Keywords: disturbance history, forest structure, land-use legacy, mountain ecosystem, old-growth forest, palaeoecology

établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Forest ecosystems that have developed for a long period of time without important anthropogenic disturbance are rare (<3% of the total forest extent), small and fragmented in Europe [START_REF] Sabatini | Where are Europe's last primary forests?[END_REF][START_REF] Barredo | Mapping and assessment of primary and old-growth forests in Europe[END_REF].

Major human imprints on many, if not all, forest ecosystems, including high conversion rates to agriculture (often with the use of fire) for millennia and intense forest exploitation [START_REF] Kaplan | The prehistoric and preindustrial deforestation of Europe[END_REF][START_REF] Birks | Past forests of Europe[END_REF] are generally viewed as causes for their current small extent [START_REF] Nagel | The natural disturbance regime in forests of the Dinaric Mountains: A synthesis of evidence[END_REF][START_REF] Sabatini | Protection gaps and restoration opportunities for primary forests in Europe[END_REF]. Despite their small extent, these primary and old-growth forests provide valuable opportunities to study forest dynamics and biotic responses to non-anthropogenic disturbances [START_REF] Foster | Ecological and conservation insights from reconstructive studies of temperate old-growth forests[END_REF], thereby contributing to the development of close-to-nature forest management methods [START_REF] Bauhus | Silviculture for old-growth attributes[END_REF][START_REF] Schütz | Comparing close-to-nature silviculture with processes in pristine forests: lessons from Central Europe[END_REF]) and guiding restoration and adaptation to environmental changes [START_REF] Mazziotta | Restoring hydrology and old-growth structures in a former production forest: Modelling the long-term effects on biodiversity[END_REF]. Even if generally protected and particularly the smaller ones (<1000 ha), these forests are vulnerable to both biotic and abiotic disturbances [START_REF] Nagel | The natural disturbance regime in forests of the Dinaric Mountains: A synthesis of evidence[END_REF][START_REF] Sabatini | Protection gaps and restoration opportunities for primary forests in Europe[END_REF], climate change [START_REF] Elsen | Keeping pace with climate change in global terrestrial protected areas[END_REF] as well as by land-use and altered disturbance regimes (e.g. fires) in surrounding areas [START_REF] Hansen | Ecological mechanisms linking protected areas to surrounding lands[END_REF] that may hinder the development of features associated with old-growth stage.

Old-growth forests are typically characterised by functional, structural and compositional features which distinguishes them from forests of younger age classes: high amounts and size of deadwood, presence of old trees approaching their natural longevity and a mosaic of heterogeneous stands arising through gap dynamics [START_REF] Wirth | Old-growth forest definitions: a pragmatic view[END_REF]). These features indirectly reflect the length of time an area has been continuously wooded without human influence and major stand-replacing disturbances, as well as the history of land-use and forest management [START_REF] Buchwald | A hierarchical terminology for more or less natural forests in relation to sustainable management and biodiversity conservation[END_REF]. However, features reflecting the old-growthness of current forest structures cannot provide information on their longer-term history and dynamics. Paleoecology, instead, is sometimes the best and only tool for evaluating the history and ecosystem responses to past environmental changes such as climate, fire and land use [START_REF] Whitlock | Land-use history as a guide for forest conservation and management[END_REF]. Moreover, palaeoecology can document the legacies of land-use history, climate change and disturbances such as fire on present-day forest composition [START_REF] Lindbladh | The influence of former land-use on vegetation and biodiversity in the boreo-nemoral zone of Sweden[END_REF][START_REF] Mclachlan | Anthropogenic ties to late-successional structure and composition in four New England Hemlock stands[END_REF][START_REF] Birks | Contributions of Quaternary botany to modern ecology and biogeography[END_REF], which is a critical information for clarifying conservation objectives and evaluating outcomes [START_REF] Whitlock | Land-use history as a guide for forest conservation and management[END_REF][START_REF] Mcmullin | Out with OLD growth, in with ecological continNEWity: new perspectives on forest conservation[END_REF].

The distribution of primary and old-growth forests is uneven in Europe, likely because the intensity and extent of human pressure differed among regions [START_REF] Sabatini | Protection gaps and restoration opportunities for primary forests in Europe[END_REF]. Old-growth forests in east-central Europe have captured the attention of foresters long ago [START_REF] Leibundgut | Über Zweck und Methodik der Struktur und Zuwachsanalyse von Urwäldern[END_REF][START_REF] Horvat | Fagus sylvatica in Europe: distribution, habitat, usage and threats[END_REF] as their dominant tree species (Abies alba Mill., Fagus sylvatica L., and Picea abies (L.) Karst) prevail in the montane belt of central Europe.

For instance, the Dinaric Mountains is considered a hotspot for late-successional montane old-growth forests [START_REF] Sabatini | Where are Europe's last primary forests?[END_REF] presumably due to early protection of forests during the 19 th century and lower historical human pressure compared to other mountain ranges in Europe due to the extent of rugged mountain areas and land with low agricultural productivity (Diaci 1999; [START_REF] Kaplan | The prehistoric and preindustrial deforestation of Europe[END_REF][START_REF] Nagel | The natural disturbance regime in forests of the Dinaric Mountains: A synthesis of evidence[END_REF]. However, records documenting long-term vegetation dynamics in conjunction with environmental changes are lacking for the montane zone in this region [START_REF] Finsinger | Holocene vegetation and fire dynamics at Crveni Potok, a small mire in the Dinaric Alps (Tara National Park, Serbia)[END_REF]. Thus, the factors leading to their fragmentation and the extent to which the current landscape retains legacies of past land-uses and natural components [START_REF] Vale | The Pre-European landscape of the United States[END_REF][START_REF] Whitlock | Land-use history as a guide for forest conservation and management[END_REF]) are largely unknown. For instance, in the montane zone of the Apennines, monospecific beech forests established in relatively recent times following the decline of Abies alba and other mesophilous deciduous trees due to enhanced fire activity and multi-millennial land-use intensification superimposed on late-Holocene cooling and moistening [START_REF] Morales-Molino | Long-term responses of mediterranean mountain forests to climate change, fire and human activities in the northern Apennines (Italy)[END_REF].

Here, we present novel multi-proxy palaeoecological data (pollen, spores, macrofossils, macroscopic charcoal, and magnetic susceptibility) and current forest structure data from Biogradska Gora (central Dinaric Mountains, Montenegro) to provide new insights into the long-term vegetation dynamics of old-growth forests in the montane zone of the Dinaric Mountains. The forest has been continually under protection for the past 140 years and includes one of the largest central-southern European old-growth stands dominated by mixed fir and beech with sparse spruce that is surrounded by almost pure beech stands (Motta et al. 2015a). Our specific aims are: (1) to assess differences in current forest structure within the old-growth stands and the surrounding forest, (2) to track standscale long-term vegetation dynamics and occurrence of past disturbances by fire, and (3) assess potential legacy effects on present-day forests.

Materials and Methods

Study area

The Biogradska Gora valley (Fig. 1) is located on the Bjelasica massif, which bears relatively small amounts of carbonate bedrocks compared to the rest of the Dinaric mountain system, where limestone substrata are prevalent.

Dystric cambisols (brown soils) on eruptive rock are the dominant type of soil (Čurović et al. 2011). The climate is influenced by continental and maritime airstreams, with annual average precipitation of c. 1960 mm, lowest rainfall in July-August and monthly temperatures ranging between -2 and 16 ºC (Motta et al. 2015a;[START_REF] Fick | WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas[END_REF].

Tree cover in the valley is dominated by beech, fir and spruce, with minor amounts of Acer pseudoplatanus L., A. platanoides L. and A. heldreichii Orph. ex Boiss, Fraxinus excelsior L., Ulmus montana With., Ulmus glabra Huds., and Sorbus aucuparia L. [START_REF] Stijovic | Bazna studija o sumama u Nacionalnom parku Biogradska Gora (Podloga za upravljanje sumama)[END_REF]. Betula L. and Pinus mugo Turra occur at the upper treeline in adjacent valleys, and Pinus peuce Griseb, P. leucodermis Ant., and P. sylvestris L. are absent in the valley but sparsely occur on the Bjelasica (Černjavski 1937).

The forest is protected since 1878 CE, when the area was set aside as a royal hunting reserve (Motta et al. 2015a).

The area is included in the Biogradska Gora National Park since 1952 to protect the forest from exploitation by logging companies [START_REF] Luburić | The introduction of new management measures in protected areas with the aim of improving models of nature protection of Montenegro[END_REF]) and has been proclaimed Biosphere Reserve in 1977(UNESCO 2010). This includes a 2830-ha strictly protected core area (IUCN category II) where land-use activities (logging, farming, grazing) are prohibited. The core area is surrounded by a buffer zone characterised by meadows (Fig. 1) and groups of shepherds' huts (locally called "katun") whose presence possibly dates back to the Middle Ages when pasturing was widespread in Montenegro [START_REF] Pluskowski | The animal bones from the 2004 excatavation at Stari Bar, Montenegro. In: Gelichi S (ed) The Archaeology of an abandoned town. The 2005 Project in Stari[END_REF]. The number of occupied huts has declined considerably during the past decades due to rural areas depopulation and many of them have been converted for tourism purposes.

Current forest composition and structure

We surveyed 51 plots predominantly in the outer part of the forest (Fig. 1). Their location was guided by a preliminary segmentation of a SPOT5 satellite image that identified polygons of homogeneous forest canopy composition and structure (Motta et al. 2015a).

In each circular plot (radius = 14 m), we recorded the species and measured the diameter at breast height (DBH) of all living stems with a DBH ≥ 7.5 cm and the heights (H) of at least three individuals for each species and in different diameter classes when available. We measured the minimum and maximum diameter and length (Dmin, Dmax, L) of all coarse woody debris (CWD) with L ≥ 100 cm and Dmin ≥ 10 cm, classifying the deadwood as snags (standing dead trees), logs (lying deadwood), or stumps (H<130 cm). In a smaller area (radius = 6 m) centred on each plot centroid we identified and counted the regeneration (DBH < 7.5 cm).

We pooled our 51-plots dataset with the 30-plots dataset recorded by Motta et al. (2015), which were concentrated in a small (50 ha) portion of the inner part of the forest, and for each plot calculated variables to assess the current old-growthness and forest structure. Then we estimated the overall tree density (De; #/ha), basal area (BA; m 2 /ha), and amount of regeneration (Re; #/ha). To estimate the volume of living wood biomass (V; m 3 /ha) we used a local volume table, deriving tree heights from species-specific hypsometric curves. We computed CWD volumes (m 3 /ha) for CWD classes, and the dead to live wood ratio (Öder et al. 2021). To estimate tree species diversity, we computed the Brillouin index [START_REF] Brillouin | Science and Information Theory[END_REF]). To measure the structural diversity, we calculated the DBH standard deviation, Tree Diameter Diversity index (TDD) to 5 cm DBH classes of living stems [START_REF] Rouvinen | Tree diameter distributions in natural and managed old Pinus sylvestrisdominated forests[END_REF], and the Gini coefficient [START_REF] Gini | Variabilità e Mutabilità (Variability and Mutability). C. Cuppini, Bologna, Italy Green DG[END_REF][START_REF] Weiner | The meaning and measurement of size hierarchies in plant populations[END_REF], which quantifies the structural heterogeneity in tree diameters (GDBH) and basal areas (GBA) (Table S1).

Subsequently, we identified forest structural types (FST) using a Hierarchical Cluster Analysis (HCA) based on selected structural and compositional variables and tested the statistical differences among FSTs using a nonparametric Kruskal-Wallis test, followed, in the case of significance, by a Dunn's post hoc test (see ESI1 for further details).

To explore the influence of accessibility, we calculated Spearman's correlations between variables describing forest structure and a proxy for potential human pressure namely the cost of access, that is the minimum accumulative distance (m) to each plot from the main roads (see ESI1 for further details), following [START_REF] Garbarino | Land-use history and topographic gradients as driving factors of subalpine Larix decidua forests[END_REF].

To assess the distribution of land-cover types and to upscale FSTs at a landscape scale we used an object-based image analysis. We pre-processed two high-resolution satellite images (Table S2) by pan-sharpening multispectral bands through the nearest neighbour diffusion (NNDiffuse) algorithm [START_REF] Sun | Nearest-neighbor diffusion-based pan-sharpening algorithm for spectral images[END_REF] and by co-registering them to the Bing satellite image with ENVI software (v5.3.1; Exelis Visual Information Solutions, Boulder, Colorado).

We then created image objects through the Large-Scale Mean-Shift (LSMS) segmentation algorithm [START_REF] Michel | Stable mean-shift algorithm and Its application to the segmentation of arbitrarily large remote sensing images[END_REF] implemented in Orfeo ToolBox v7.0 [START_REF] Grizonnet | Orfeo ToolBox: open source processing of remote sensing images[END_REF], using a raster stack formed by the near infrared band, the Normalized Difference Vegetation Index (NDVI) and textural data derived from granulometric analysis based on the opening procedure (see ESI1 for further details). We performed a supervised classification of image objects using the Random Forest (RF) algorithm implemented in the 'ranger' R package [START_REF] Wright | ranger: A fast implementation of random forests for high dimensional data in C++ and R[END_REF], employing the spectral and textural information of the image objects as predictor variables for the RF model (Table S3). We trained the RF model using 1457 objects that were classified through on-screen visual interpretation. Most of the training objects (n=1305) intersected the 81 ground-survey plots and belonged to one of the following land-cover types: broadleaved trees, conifers and forest canopy gaps. We identified training objects of land-cover types that we did not survey (grasslands, bare ground and water) through on-screen interpretation. We assessed the performance of the RF model by computing the average overall accuracy and Cohen's Kappa statistic obtained from a 5-fold cross-validation procedure. We performed the analyses separately for two satellite images and then merged the land-cover maps.

Long-term vegetation and fire disturbance histories

We collected a 245-cm long sediment sequence from a small pond (0.047 ha; 42°54'5.898"N; 19°35'53.538"E; 1155 m a.s.l.; Fig. 1) located in the beech-dominated outer part of the forest to reconstruct stand-scale vegetation dynamics. We combined two parallel and overlapping cores (drives 1-m long and 8 cm in diameter) collected near to the centre of the basin with a Russian-type corer at 5 cm water depth.

To constrain the depth-age model, we used eight AMS 14 C dates from terrestrial plant macrofossils (Table S4) calibrated using the IntCal13 dataset [START_REF] Reimer | IntCal13 and Marine13 radiocarbon age calibration curves 0-50,000 years cal BP[END_REF]. We built the model using the RBacon v2.4.1 package [START_REF] Blaauw | Flexible Paleoclimate Age-Depth Models Using an Autoregressive Gamma Process[END_REF] and verified the accuracy in its most recent part by comparing the expected and actual ages of the first occurrence of Ambrosia artemisiifolia L. pollen. Documentary evidence [START_REF] Makra | The history and impacts of airborne Ambrosia (Asteraceae) pollen in Hungary[END_REF][START_REF] Csontos | Early distribution and spread of Ambrosia artemisiifolia in Central and Eastern Europe[END_REF] indicates that ragweed (Ambrosia) became invasive in Central and Eastern Europe around 1910-1920 CE.

We measured the magnetic susceptibility at 1-cm intervals with a Bartington MS2E surface-scanning sensor following [START_REF] Nowaczyk | Logging of magnetic susceptibility[END_REF]. Magnetic susceptibility is influenced by the amount of minerogenic input that results from erosion. Negative magnetic-susceptibility values are found in sediments with minerals that do not contain Fe (e.g. quartz and calcite) and in organic-rich sediments.

We used macroscopic charcoal analyses to reconstruct long-term fire activity [START_REF] Whitlock | Charcoal as a fire proxy[END_REF][START_REF] Conedera | Reconstructing past fire regimes: methods, applications, and relevance to fire management and conservation[END_REF]). We counted charcoal particles in contiguous 1-cm 3 samples, and additionally measured areas of charcoal particles for 42 samples (6-cm resolution) using an image-analysis software (see ESI1). We transformed charcoal concentrations to charcoal accumulation rates (CHAR) based on the chronology.

To uncover local-scale vegetation dynamics, we analysed 41 plant macrofossil samples in conjunction with pollen and stomata (see Fig. S1 and ESI for details of laboratory and identification methods used) [START_REF] Birks | Future uses of pollen analysis must include plant macrofossils[END_REF][START_REF] Ammann | The potential of stomata analysis in conifers to estimate presence of conifer trees: examples from the Alps[END_REF][START_REF] Finsinger | New insights on stomata analysis of European conifers 65 years after the pioneering study of Werner Trautmann (1953)[END_REF]. We calculated pollen percentages relative to the terrestrial pollen sum, which included pollen from trees, shrubs, herbs and Pteridium spores. A sum of at least 250 pollen and spores was counted for each sample. However, the lowermost sample has a substantially lower pollen sum (n=36) due to an extremely low pollen concentration.

To evaluate human impact, we considered the abundances of primary anthropogenic indicators, secondary adventives and apophytes [START_REF] Behre | The interpretation of anthropogenic indicators in pollen diagrams[END_REF][START_REF] Deza-Araujo | A critical assessment of human-impact indices based on anthropogenic pollen indicators[END_REF], which include pollen of cultivated plants, ruderals, and plants of meadows. In addition, we used Sporormiella-type dung-fungi spores, which are linked to the presence and abundance of large herbivores [START_REF] Davis | Spores of the dung fungus Sporormiella: increased abundance in historic sediments and before Pleistocene megafaunal extinction[END_REF][START_REF] Baker | Do dung fungal spores make a good proxy for past distribution of large herbivores?[END_REF], and Tilletia caries-type spores (see ESI1), a pathogen associated mostly with grasses, including cereals (Mazurkiewicz-Zapałowicz and Okuniewska-Nowaczyk 2015). Abundances of non-pollen palynomorphs are presented as influx (number cm -2 year -1 ).

We determined pollen assemblage zones based on terrestrial pollen taxa (excluding taxa with maximum abundance <5%) using optimal partitioning by sums-of-squares [START_REF] Birks | Numerical Methods in Quaternary Pollen Analysis[END_REF] in Psimpoll v4.26 (Bennett 2008).

The number of statistically significant zone boundaries was determined by comparison with the broken-stick model [START_REF] Bennett | Determination of the number of zones in a biostratigraphical sequence[END_REF].

We analysed the CHAR data using CharAnalysis v1.1 [START_REF] Higuera | Vegetation mediated the impacts of postglacial climate change on fire regimes in the south-central Brooks Range, Alaska[END_REF]) to determine centennial-scale trends in CHAR that were interpreted as relative changes in biomass burned over time [START_REF] Marlon | Climate and human influences on global biomass burning over the past two millennia[END_REF]Higuera et al. 2010a), and to identify peaks in charcoal, which were interpreted as fire episodes. The analysis involved interpolating CHAR values to a constant sampling resolution, decomposing that record into a background and a peak component using a robust LOWESS, and evaluating peak samples using both the 99 th percentile of the modelled noise distribution obtained with a Gaussian mixture model and a peak-screening test. The suitability of the record for peak detection was assessed with the signal-to-noise index (SNI; [START_REF] Kelly | A signal-to-noise index to quantify the potential for peak detection in sediment-charcoal records[END_REF]. We calculated fire return intervals (FRI) using the screened peak record.

We used change-point analysis to determine significant changes in biomass burning and test the potential effect of sedimentation rates on change-point detection [START_REF] Finsinger | Holocene fire-regime changes near the treeline in the Retezat Mts. (Southern Carpathians, Romania)[END_REF].

To test the simultaneity between fire and erosion events, thereby allowing identification of high-severity local catchment fires [START_REF] Chileen | Vegetation response to wildfire and climate forcing in a Rocky Mountain lodgepole pine forest over the past 2500 years[END_REF], we used Event Coincidence Analysis (ECA; [START_REF] Siegmund | CoinCalc -A new R package for quantifying simultaneities of event series[END_REF]. We determined erosion events as (i) peaks of magnetic susceptibility, which respond to increases in minerogenic input that often follow fire events as a result of erosion, and to in-washing of secondary ferromagnetic minerals that are formed when soils with a high concentration of convertible Fe are heated [START_REF] Thompson | Environmental magnetism[END_REF][START_REF] Millspaugh | A 750-year fire history based on lake sediment records in central Yellowstone National Park, USA[END_REF], and (ii) peaks of Cenococcum geophilum Fr. sclerotia influx, whose abundances are linked to soil erosion [START_REF] Van Geel | A palaeoecological study of Holocene peat bog sections in Germany and The Netherlands, based on the analysis of pollen, spores and macro-and microscopic remains of fungi, algae, cormophytes and animals[END_REF]. The two datasets were analysed with a custom-made computer code (R Core Team 2020) in a similar way to the CHAR record to statistically identify distinct peaks. We performed the ECA using two binary event time series (CHAR peaks and erosion peaks), a lag of 8 years, and a tolerance window 8-48 years that detects erosion events within 10-50 years of fire episodes, and tested the significance based on the assumption of independent and sparse Poisson processes (α=0.05).

To identify leads and lags between fire activity (macroscopic charcoal influx values) and vegetation and land-use change (pollen percentages and dung-fungi spores' influx), we used cross-correlation analyses (Green 1981;[START_REF] Tinner | Long-term forest fire ecology and dynamics in southern Switzerland[END_REF][START_REF] Valsecchi | Testing the influence of climate, human impact, and fire on the Holocene population expansions of Fagus sylvatica in the southern Prealps (Italy)[END_REF]. We performed the analyses for two time intervals that show different intensity of human pressure: 970-1350 CE (higher pressure); 1600 CE to the present (lower pressure). Within the selected time intervals, the sampling resolution was relatively stable (32±3 and 21±3 years between samples, respectively). The cross-correlations' span was restricted to one-fourth of the sample number N (lag number ≤ N/4).

Results

Present vegetation composition and forest structure

The forest includes plots characterized by large trees (up to 148 cm of DBH; Fig. 2) and by a high CWD volume (up to 791.6 m 3 ha -1 ; Fig. 3). Plots having a complex horizontal and vertical structure are present as shown by high volume of living trees (V; up to 1781.9 m 3 ha -1 ) and high values of structural diversity indices (GBA up to 0.8) (Table 1). CWD consists mostly of logs (65%) and snags (33%) and rarely stumps (2%). Although beech is the species with the highest overall stems density, beech trees are generally smaller than fir and spruce trees.

The HCA (Fig. S2) identified three forest structural types (FST) that differ significantly from each other (Table 1; Fig. 3). Their overlap on the land-cover type map that we obtained through remote-sensing analysis (Fig. 1; see ESI1 Table S5 for assessment of accuracies) shows that FST1 plots predominantly occur in the beech-dominated outer part of the forest. These plots are dominated by small and mostly multi-stemmed beech trees (DBH generally <40 cm from single stools), and have negligible amounts of CWD, and low BA and density of conifers and other deciduous species. We found an inactive charcoal kiln in one of these plots, and cut stumps in two plots. FST2 and FST3 plots are in a 957-ha conifer-dominated area (34% of the core area) and are dominated by fir (FST3) and predominantly co-dominated by fir and spruce (FST2). FST2 also includes a plot dominated by sycamore maple.

CWD and dead to live wood ratio values are significantly higher, and BA and density of beech are significantly lower than in FST1 plots.

The indices of structural diversity (DBHSD, HSD, GDBH, GBA) indicate that plots in the inner part of the forest are structurally more heterogeneous than those in the outer part. FST2 plots have the highest species and structural diversity (Table 1) as they consist of large fir and spruce trees (up to 148 cm in DBH), and small to intermediate beech trees (mostly 10-65 cm in DBH). In FST3 plots, spruce trees are extremely rare, and the prevalent species are fir (intermediate to large diametric classes, up to 115 cm) and beech (small to intermediate diametric classes).

Moreover, the DBHmean and volume are significantly lower and the amount of CWD and dead to live wood ratio values are significantly higher. Regeneration of spruce is very scarce in all plots, while regeneration of fir and beech is significantly higher in FST1 and FST3, respectively.

Median cost of access is lower for FST1 plots in the outer part of the forest (Fig. 3). Cost of access is significantly and positively correlated to BA of fir (Spearman's ρ=0.43, P<0.001) and negatively to BA of beech (Spearman's ρ=-0.36, P <0.01). Positive significant correlations of cost of access are also found with CWD amount (Spearman's ρ=0.44, P<0.001), dead to live wood ratio (Spearman's ρ=0.38, P<0.001) and heterogeneity as described by the DBH standard deviation (Spearman's ρ=0.29, P<0.05) and Gini indices (Spearman's ρ=0.35 for GDBH and 0.30 for GBA, P<0.01).

The difference among forest structures is also supported by the textural analysis of the forest canopy (Figs S3a-c), which are finer and more homogeneous in the outer part, whereas more complex and heterogeneous canopies, probably arising from gap dynamics, are common in the inner part. Most (99%) of the detected gaps occur in the conifer-dominated area. Gap sizes are highly variable (mean: 210 m 2 ; range: 3.33-5636 m 2 ) and their distribution is right-skewed (76% of gaps <200 m 2 , only 2% >1000 m 2 ).

Long-term environmental changes

The sediment core spans the past c. 1000 years (Fig. S4a). The reliability of the chronology in its most recent part is confirmed by the first occurrence of Ambrosia pollen around 1920 CE (Fig. 4). Sediment deposition time (Fig. S4b) varies little (3-8 years cm -1 ; median=4.4 years cm -1 ). Sediments deposited before 1300 CE are lighter in colour than the darker-brown detritus gyttja deposited thereafter (see ESI1 for further details on sediment composition and the chronology).

The pollen record (Fig. 4, see ESI1 Fig. S5-S6 for more detailed pollen and macrofossil diagram) was divided into three statistically significant assemblage zones at 123.5 and 52 cm depth (c. 1600 and 1850 CE, respectively).

However, to better illustrate the long-term vegetation changes we additionally selected a non-significant pollen zone boundary at 171.5 cm (c. 1350 CE).

The lowermost pollen assemblages (950-1150 CE) of zone 1a are characterized by decreasing abundance of tree pollen (from 80% to 40%), particularly pollen of conifers (Abies, Pinus sylvestris-type and Picea) and of fern spores (e.g. Athyrium filix-femina), which grow in fresh and shaded understorey environments [START_REF] Ellenberg | Vegetation ecology of Central Europe, 4th Edition[END_REF]. Macroscopic charcoal concentration values ranged between 0 and 271 (median = 34 pieces cm -3 ). Charcoal counts and charcoal areas are significantly correlated (R 2 =0.91, P<0.001). Peak analyses based on different parameters are highly comparable among one another with mean SNI values generally higher than the critical threshold (Table S6; Figs S8-S9). The periods of shorter fire-return intervals (1000-1150 CE, FRI=25 years; 1460-1520 CE, FRI=60 years; and 1730-1810 CE, FRI=75 years) occur predominantly during phases of high biomass burning (1000-1030, 1340-1730, and 1730-1850 CE, Figs 5 and S10). A large majority (75%, P=0.05) of the erosion events occurred 10-50 years after fire episodes (Fig. S11). This is the case for erosion events occurring at the onset of the Middle Ages (1050 CE), towards the end of the Middle Ages (1500-1550 CE), and during the 20 th -century. The coincidence between fire episodes and erosion events suggests that these were triggered by higher-severity catchment fires, whereas fire episodes occurring during the medieval land-use phase (1050-1150 CE) and around 1800 CE were of lower intensity or occurred outside the catchment.

We used cross-correlation analyses (Fig. 6) to explore leads and lags between fire activity and vegetation and landuse change separately for (i) the Middle Ages when human pressure was higher (970-1350 CE; zone 1b), and (ii) the more recent centuries (1600 CE to the present; zones 2-3) when human pressure was lower and the forest was protected. Significant negative correlation coefficients (P<0.05) between charcoal-accumulation rates (CHAR) and arboreal pollen, Abies, Picea and Fagus in the Middle Ages indicate that fires contributed considerably to the decline of late seral species. We found the highest correlation coefficients when CHAR lagged primary indicators and dung spores by 30 years, consistently with mechanisms of charcoal taphonomy leading to delayed deposition at a coring location (Duffin et al., 2008;Higuera et al., 2010). Thus, the significant positive correlations between CHAR and primary anthropogenic indicators and dung spores at negative lags support the hypothesis of humandriven fires used to create open areas for agriculture and grazing.

For the time interval when human pressure was lower (1600 CE to the present) arboreal pollen is negatively correlated with fire, and primary anthropogenic indicators are positively correlated with fire at lag 0, thus corroborating the link between cultivation and fire. Dung fungi also show positive significant correlations with fire, though the highest coefficients are found at positive lags, suggesting a delayed increase of grazing ca. 60 years after fire activity rises. By contrast, in this time interval the correlation coefficients between CHAR and Abies, Picea and Fagus are not significant. However, Corylus and Betula show positive significant correlations ahead of the charcoal peaks (at lags -4 and -5), suggesting that these light-demanding pioneer species acted as fire precursors, and Fraxinus shows a negative significant correlation at lag 0. It thus seems likely that land-use and fires mainly occurred in gaps within the overall Fagus-dominated forest.

Discussion

Current forest structure within the old-growth stands and the surrounding forest

Our extensive ground surveys and the detailed remote-sensing analyses show that the Biogradska Gora forest is characterised by a large compositional and structural variability. We detected a fine-scale variability due to gap dynamics within the conifer-dominated matrix in the inner part, which allow the recruitment of more lightdemanding species, like sycamore maple, in larger gaps [START_REF] Nagel | Disturbance, life history traits, and dynamics in an old-growth forest landscape of southeastern Europe[END_REF]. In addition to this fine-scale variability, we identified three forest structural types (FSTs) showing different degrees of old-growthness (Fig. 3) that are unevenly distributed within the forest (Fig. 1). The structural and compositional variability supports the notion that plots placed in a limited area that is considered representative of old-growth characteristics may lead to an overestimation of average old-growthness [START_REF] Peck | Should reference conditions be drawn from a single 10 ha plot? Assessing representativeness in a 10,000 ha old-growth European beech forest[END_REF][START_REF] Carrer | Tree spatial patterns and stand attributes in temperate forests: The importance of plot size, sampling design, and null model[END_REF].

The structure in the inner part of the forest (FST2 and FST3) is comparable to that of other mixed old-growth forests such as Perućica, Lom, and Jani in Bosnia-Herzegovina [START_REF] Motta | Toward a definition of the range of variability of central European mixed Fagus -Abies -Picea forests: the nearly steady-state forest of Lom (Bosnia and Herzegovina)[END_REF](Motta et al. , 2015b, a;, a;[START_REF] Keren | Comparative structural dynamics of the Janj mixed old-growth mountain forest in Bosnia and Herzegovina: Are conifers in a long-term decline?[END_REF][START_REF] Keren | Relationships between structural indices and conventional stand attributes in an old-growth forest in southeast Europe[END_REF][START_REF] Zenner | Integration of small-scale canopy dynamics smoothes live-tree structural complexity across development stages in old-growth Oriental beech (Fagus orientalis Lipsky) forests at the multi-gap scale[END_REF][START_REF] Chivulescu | Development phases and structural characteristics of the Penteleu-Viforâta virgin forest in the Curvature Carpathians[END_REF], both in terms of variables assessed previously (BA, V, and CWD) by Motta et al. (2015a) as well as in terms of dead to live wood ratio and structural diversity (Table 1, Figs 2 and3). Moreover, the heterogeneous texture of the forest canopy with small-scale gaps also shows that the conifer-dominated stands in the inner part of the forest likely had the time to develop typical old-growth attributes [START_REF] Spies | Old growth and forest dynamics in the Douglas-fir region of Western Oregon and Washington[END_REF][START_REF] Wirth | Old-growth forest definitions: a pragmatic view[END_REF]).

The HCA confirms prior studies showing that the old-growth forest includes two structural types, their main differences being the rarity of spruce (Motta et al. 2015a) and significantly higher dead biomass (CWD and dead to live wood ratio values) in the fir-dominated FST3 plots (Fig. 3). Because spruce is rare in these plots, their significantly higher amount of dead biomass could be linked to higher spruce mortality. This would fit with the persisting decline of the spruce population, as indicated by its extremely low seedling regeneration and the absence of spruce saplings in all plots (Table 1). The decline of spruce may agree with evidence showing that at the southern boundary of its distributional range populations of the cold-adapted spruce are more vulnerable to drought than fir and beech [START_REF] Hanewinkel | Climate change may cause severe loss in the economic value of European forest land[END_REF][START_REF] Zang | Patterns of drought tolerance in major European temperate forest trees: climatic drivers and levels of variability[END_REF]. In agreement with this, in the Dinaric Alps spruce dominated stands are common in karst depressions and sinkholes where temperature inversions cause significantly colder microclimates [START_REF] Nagel | The natural disturbance regime in forests of the Dinaric Mountains: A synthesis of evidence[END_REF]. Conversely, the low spruce regeneration could be explained by the scarcity of expanded gaps, as spruce is less shade tolerant than beech and fir (Stancioiu and O'Hara 2006a) and beech is the main gap filler species in a small-scale disturbance regime [START_REF] Petritan | Overstory succession in a mixed Quercus petraea-Fagus sylvatica old growth forest revealed through the spatial pattern of competition and mortality[END_REF]) typical of old-growth forests.

In the beech-dominated outer part of the forest (FST1) CWD consists mostly of logs with a lesser number of snags, as often observed in old-growth stands [START_REF] Nilsson | Erratum to "Densities of large living and dead trees in oldgrowth temperate and boreal forests[END_REF] and as observed in the inner part of the forest. However, the FST1 plots have substantially lower CWD values than FST2 and FST3 plots. While this is relatively unsurprising given that broadleaved trees produce a lower deadwood accumulation [START_REF] Harmon | Ecology of coarse woody debris in temperate ecosystems[END_REF]) due to their lower height and volume, and their deadwood decays faster than deadwood of conifer species (e.g. 20-40 years for Fagus, and within 58-191 years for conifer snags on moist sites; [START_REF] Vacek | The dynamics and structure of dead wood in natural spruce-beech forest stand -a 40 year case study in the Krkonoše National Park[END_REF][START_REF] Hararuk | Dynamics of dead wood decay in Swiss forests[END_REF], these plots also have substantially lower CWD values than other European beech-dominated old-growth forests [START_REF] Burrascano | Commonality and variability in the structural attributes of moist temperate old-growth forests: A global review[END_REF][START_REF] Meyer | Quantifying old-growthness of lowland European beech forests by a multivariate indicator for forest structure[END_REF]. Interestingly, CWD and dead to live wood ratio values are closer to those found in currently managed forests or in those recently withdrawn from regular management (Motta et al. 2015b). Moreover, the lower structural diversity of these plots and the finer texture of the forest canopy rather reflect a homogeneous structure and even-aged cohorts.

Stand-scale long-term vegetation dynamics, land-use changes and disturbances by fire

Despite the importance of pollen loading from regional sources, the proportion of pollen loading coming to the 0.05-ha-pond in the beech-dominated area from the relevant pollen source area (200-300 m for such sites) is adequate to reflect local vegetation composition [START_REF] Jp Nacionalni Parkovi Crne | Pollen representation of vegetation in Quaternary sediments -theory and method in patchy vegetation[END_REF][START_REF] Hofstetter | Lateglacial and Holocene vegetation history in the Insubrian Southern Alps-New indications from a small-scale site[END_REF]. This is also supported by the coherence between the pollen and the plant-macrofossil and stomata records (Fig. 7) that are generally dispersed over substantially shorter distances than pollen [START_REF] Birks | Can we detect a west Norwegian tree line from modern samples of plant remains and pollen? Results from the DOORMAT project[END_REF][START_REF] Ammann | The potential of stomata analysis in conifers to estimate presence of conifer trees: examples from the Alps[END_REF]. Similarly, while the source area of macroscopic charcoal particles can be relatively large (up to 30-50 km; [START_REF] Oris | Charcoal dispersion and deposition in boreal lakes from 3 years of monitoring: Differences between local and regional fires[END_REF][START_REF] Adolf | The sedimentary and remote-sensing reflection of biomass burning in Europe[END_REF], both empirical and simulated data support the assumption that charcoal peaks most accurately reflect fire episodes within 1-3 km of coring sites (Higuera et al. 2010b). Moreover, the coincidence of peaks in charcoal and erosion-indicators helped us to pinpoint the occurrence of local higher-severity catchment fire episodes (Fig. 7). Thus, our palaeoecological record predominantly documents local-scale vegetation dynamics, land-use and fire occurrence for the currently beech-dominated outer part of the forest.

During the Middle Ages, tree cover was substantially lower and cereal crop cultivation and cattle herding were more widespread than today (Fig. 7). Finds of spores of common bunt (Tilletia sp.) suggest that pathogens affected cultivated crops, as these pathogens can cause devastating yield reductions by up to 50% [START_REF] Kiesselbach | The effects of stinking smut (Bunt) and seed treatment upon the yield of winter wheat[END_REF]. Bunt was one of the most severe diseases of winter wheat (Triticum aestivum L.) in the Middle Ages [START_REF] Gaudet | Common bunt of wheat: an old foe remains a current threat[END_REF] and harvest failures were important factors for social vulnerability, particularly for people living in rural areas in pre-industrial economies [START_REF] Pfister | Social vulnerability to climate in the "Little Ice Age": an example from Central Europe in the early 1770s[END_REF]. These constraints on crop cultivation favoured abandonment of the fields surrounding the pond, thereby causing the tree cover increase around 1350 CE when the Black Death pandemic rapidly spread and substantially reduced population density [START_REF] Green | Taking "Pandemic" Seriously: Making the Black Death Global[END_REF][START_REF] Luterbacher | Past pandemics and climate variability across the Mediterranean[END_REF].

Despite setbacks due to the occurrence of more moderate and transient local land-use phases with the use of fire, tree cover increased after 1350 CE. This trajectory markedly contrasts with decreasing tree cover due to intensifying land-use since the 15 th -16 th century (Fig. 7) documented for nearby Bosnia-Herzegovina (Prokoško Jezero; Dörfler 2013), the coastal region of Albania-Montenegro (Shkodra Jezero; [START_REF] Sadori | Vegetation, climate and environmental history of the last 4500 years at lake Shkodra (Albania/Montenegro)[END_REF], as well as for elsewhere in Europe [START_REF] Fyfe | From forest to farmland: pollen-inferred land cover change across Europe using the pseudobiomization approach[END_REF][START_REF] Conedera | Insights about past forest dynamics as a tool for present and future forest management in Switzerland[END_REF], and as suggested by models [START_REF] Kaplan | The prehistoric and preindustrial deforestation of Europe[END_REF]).

The absence of evidence for intensifying land-use after the 15 th century at Biogradska Gora could be due to the transition to cooler temperatures and the beginning of the Little Ice Age (LIA), which may have discouraged cultivation and pasturing in the valley. Indeed, years with unusually cold spring seasons during the LIA had serious consequences on grain harvests and on cattle in the meridional Balkans and in Serbia [START_REF] Xoplaki | Variability of climate in meridional Balkans during the periods 1675-1717 and 1780-1830 and its impact on human life[END_REF][START_REF] Mrgic | Intemperate weather in violent times -narratives from the Western Balkans during the Little Ice Age (17-18th centuries)[END_REF]). An alternative, or additional, explanation could be the small pollen source area, which predominantly captured pollen from the surrounding expanding beech stand despite ongoing land use on the hilltops where meadows still exist today. Regardless, the tree-cover increase and decreasing land-use pressure that started around 1500-1600 CE suggests that the 19 th century's formal protection of the forest eventually took advantage of the preexisting situation, supporting the view that historical land-use pressure is a significant predictor for the occurrence of primary and old-growth forests [START_REF] Sabatini | Where are Europe's last primary forests?[END_REF].

The longer continuity of the conifer-dominated old-growth stands is currently not supported by firm evidence due to the lack of palaeoecological sites in that area. On one hand, these stands may have developed after the 15 th -16 th century, when land-use declined. This would fit with age estimates of deadwood showing that trees up to 400-500 years old occurred in the conifer-dominated stands (Motta et al. 2015a). On the other hand, the presence of stomata and plant macrofossils before the 15 th -16 th century in the currently beech-dominated outer part of the forest (Fig. 7) rather supports the hypothesis that the area of fir and spruce-dominated old-growth forest was reduced during the Middle Ages. In Central and in southern European mountains fir declined several millennia earlier [START_REF] Büntgen | Placing unprecedented recent fir growth in a European-wide and Holocene-long context[END_REF][START_REF] Morales-Molino | Long-term responses of mediterranean mountain forests to climate change, fire and human activities in the northern Apennines (Italy)[END_REF]) than at Biogradska Gora, and it is plausible to hypothesise that fir declined earlier in more accessible mountain areas. The higher cost of access may have prevented human activities in the old-growth forest, and land-use activities were probably limited to the outer part of the forest, as observed at Biogradska Gora (Černjavski 1937) and as is often the case for protected ecosystems [START_REF] Hansen | Ecological mechanisms linking protected areas to surrounding lands[END_REF].

Fires either did not propagate into the inner part of the forest, or their severity was not high enough to affect the fire-sensitive fir population. Overall, this supports the notions that human pressure played an important role for the small extent of old-growth forests [START_REF] Nagel | The natural disturbance regime in forests of the Dinaric Mountains: A synthesis of evidence[END_REF][START_REF] Sabatini | Where are Europe's last primary forests?[END_REF] and that buffer zones are key for protecting old-growth forests [START_REF] Barredo | Mapping and assessment of primary and old-growth forests in Europe[END_REF].

Legacies of past human activities

Forest composition in the surroundings of the small pond shifted from a mixed fir-spruce-broadleaf stand to one dominated by beech at the transition to cooler LIA temperatures and in conjunction to a land-use pressure decline around 1500-1600 CE (Fig. 7). Analogous expansions of beech at the expense of fir are well documented in midlate Holocene pollen records from central-southern Europe, and evidence suggests that despite the two species currently sharing large parts of the ecological niche (Houston Durrant et al. 2016;[START_REF] Mauri | Abies alba in Europe: distribution, habitat, usage and threats[END_REF], beech became more competitive after the decline of Abies alba and with the onset of cooler and moister summers and human fire disturbance [START_REF] Vescovi | A new Late-glacial and Holocene record of vegetation and fire history from Lago del Greppo, northern Apennines, Italy[END_REF][START_REF] Morales-Molino | Long-term responses of mediterranean mountain forests to climate change, fire and human activities in the northern Apennines (Italy)[END_REF]. While it is difficult to disentangle the effects of climate and land-use, it seems likely that land-use and fire occurrence probably played an important role in driving the vegetation shift. The conifer population was strongly reduced due to increased local fire activity (Fig. 6) in conjunction with land-use during the Middle Ages, and the local conifer population finally collapsed in 1500 CE when two higher-severity local fires occurred at the onset of a moderate land-use phase (Fig. 7). This is in line with a wealth of evidence showing that conspicuous canopy gaps (from fires and land-use) can cause a reshuffling of the dominant tree species in mixed fir, beech and spruce forests. Spruce, for instance, does not survive or resprout after high severity fires [START_REF] Niklasson | A 350-year tree-ring fire record from Białowieża Primeval Forest, Poland: implications for Central European lowland fire history[END_REF][START_REF] Feurdean | Fire frequency and intensity associated with functional traits of dominant forest type in the Balkans during the Holocene[END_REF]) despite bearing traits promoting fires (high resin content, ladder canopy structure) and being able to persist with a low to moderate fire severity [START_REF] Feurdean | Fire has been an important driver of forest dynamics in the Carpathian Mountains during the Holocene[END_REF]. Similarly, both large-infrequent and small-frequent fires lead to a rapid local extinction of the fire-intolerant Abies [START_REF] Tinner | The past ecology of Abies alba provides new perspectives on future responses of silver fir forests to global warming[END_REF]. By contrast, human activities and disturbance by fire can favour the spread of beech at the stand level [START_REF] Bradshaw | Regional spread and stand-scale establishment of Fagus sylvatica and Picea abies in Scandinavia[END_REF][START_REF] Tinner | Holocene expansions of Fagus silvatica and Abies alba in Central Europe: where are we after eight decades of debate?[END_REF]. Beech quickly resprouts and regenerates successfully after small or intermediate human and natural disturbances (windthrow, cutting, fire; [START_REF] Motta | Toward a definition of the range of variability of central European mixed Fagus -Abies -Picea forests: the nearly steady-state forest of Lom (Bosnia and Herzegovina)[END_REF][START_REF] Nagel | Disturbance, life history traits, and dynamics in an old-growth forest landscape of southeastern Europe[END_REF][START_REF] Maringer | Resilience of European beech forests (Fagus sylvatica L.) after fire in a global change context[END_REF]. Importantly, beech regenerates faster than fir and spruce in canopy gaps and overstorey releases (Stancioiu and O'Hara 2006b;[START_REF] Bolte | Understory dynamics after disturbance accelerate succession from spruce to beech-dominated forest-the Siggaboda case study[END_REF].

Additionally, beech encircles competitors and fills gaps after disturbances [START_REF] Pretzsch | Crown allometry and growing space efficiency of Norway spruce (Picea abies [L.] Karst.) and European beech (Fagus sylvatica L.) in pure and mixed stands[END_REF][START_REF] Bolte | Understory dynamics after disturbance accelerate succession from spruce to beech-dominated forest-the Siggaboda case study[END_REF] as it rapidly takes advantage of more favourable light conditions due to higher morphological plasticity of foliage and crown structures [START_REF] Dieler | Morphological plasticity of European beech (Fagus sylvatica L.) in pure and mixedspecies stands[END_REF]. Thus, frequent small or intermediate-scale disturbances [START_REF] Delarze | Effects of fire on forest dynamics in southern Switzerland[END_REF], such as those created by land-use associated with the use of fire, can promote beech [START_REF] Bolte | Understory dynamics after disturbance accelerate succession from spruce to beech-dominated forest-the Siggaboda case study[END_REF]). An additional explanation could involve clear-cutting and extraction of conifer timber in stands that are accessible for harvest [START_REF] Büntgen | Placing unprecedented recent fir growth in a European-wide and Holocene-long context[END_REF]. Other forms of land-use, such as coppicing, also could have favoured beech to obtain firewood or wood charcoal, as observed elsewhere in marginal areas of coniferous woodland in Central Europe [START_REF] Winkler | Beiträge zur Klimatologie hochalpiner Lagen der Zentralalpen[END_REF]. Coppicing and clear-cutting practices developed greatly due to increasing wood demand and demographic growth in the 16 th -17 th centuries and after 1850 CE [START_REF] Mcevedy | Atlas of World Population History[END_REF]. At Biogradska Gora, these practices are attested to by multi-stemmed beech trees and traces of charcoal kilns in some plots in the more accessible outer part of the forest.

The protected old-growth forest of Biogradska Gora should be sufficiently large (>1000 ha) to buffer the effects of small-scale natural disturbances [START_REF] Sabatini | Where are Europe's last primary forests?[END_REF]. Moreover, population density in mountain areas is predicted to decrease over the 21 st century in eastern Europe due to abandonment of pastoral and agricultural activities [START_REF] Wu | Sensitivity of burned area in Europe to climate change, atmospheric CO2 levels, and demography: A comparison of two fire-vegetation models: Projected future burned area in Europe[END_REF]. This may also be beneficial to the majority of primary and old-growth forests that are substantially smaller (<100 ha) [START_REF] Sabatini | Where are Europe's last primary forests?[END_REF]). However, old-growth forests may be at risk due to predicted environmental changes. For instance, despite the rare natural fire occurrence and the much greater importance of other disturbance agents (bark beetle outbreaks, windthrows; [START_REF] Nagel | The natural disturbance regime in forests of the Dinaric Mountains: A synthesis of evidence[END_REF], forest fires are predicted to increase in the region, which could potentially become a new fire-prone area [START_REF] Krawchuk | Global pyrogeography: the current and future distribution of wildfire[END_REF][START_REF] Wu | Sensitivity of burned area in Europe to climate change, atmospheric CO2 levels, and demography: A comparison of two fire-vegetation models: Projected future burned area in Europe[END_REF]. Warmer and drier conditions that may lead to increased fires will also likely affect vegetation structure modifying fuel type, fuel load and therefore fire intensity and spread, increasing mortality rates. For instance, as fir is known to be more drought tolerant than beech (Morales-Molino et al. 2020) its population may recover if other disturbances (e.g. fires) do not prevent the expansion of this fire-sensitive tree species.

Conclusions

The multi-proxy palaeoecological records (pollen, spores, stomata, macrofossils, macroscopic charcoal, and magnetic susceptibility) coupled with the extensive survey of current forest structures and with the map of landcover types from the Biogradska Gora forest provide new insights into the long-term vegetation dynamics of oldgrowth forests in the montane zone of the Dinaric Mountains. The stand-scale palaeoecological records show that human activities (agriculture, and pastures) as well as fires, which are rare today in these forest types [START_REF] Nagel | The natural disturbance regime in forests of the Dinaric Mountains: A synthesis of evidence[END_REF]) reduced the area of fir and spruce-dominated forest during the Middle Ages. Despite the local land-use decline 500-400 years ago and the early protection of the forest 140 years ago, the legacies of past land-use activities are still visible, as the conifer-dominated mixed forest in the inner part of the valley has more old-growth characteristics than the almost pure beech forest in the outer part. However, the continuity and increase of tree cover in the outer part of the forest since the 16 th century markedly contrasts with the widespread high conversion rates to agriculture and forest exploitation elsewhere in Europe during the past millennium [START_REF] Kaplan | The prehistoric and preindustrial deforestation of Europe[END_REF][START_REF] Fyfe | From forest to farmland: pollen-inferred land cover change across Europe using the pseudobiomization approach[END_REF][START_REF] Birks | Past forests of Europe[END_REF], thereby supporting the view that historical land-use pressure played an important role for the small extent and the continuity of disturbance-sensitive A. alba and P. abies-dominated oldgrowth stands.

Our study shows that combining stand-scale long-term ecological records with assessments of contemporary forest structure can generate valuable insights [START_REF] Foster | Ecological and conservation insights from reconstructive studies of temperate old-growth forests[END_REF], as the structures and spatial patterns of ecosystems are often a result of legacy effects arising from complex interactions between natural and human disturbances [START_REF] Mclachlan | Anthropogenic ties to late-successional structure and composition in four New England Hemlock stands[END_REF][START_REF] Vale | The Pre-European landscape of the United States[END_REF][START_REF] Willis | What is natural? The need for a long-term perspective in biodiversity conservation[END_REF][START_REF] Whitlock | Land-use history as a guide for forest conservation and management[END_REF], which is critical information for guiding forest management and conservation measures [START_REF] Conedera | Insights about past forest dynamics as a tool for present and future forest management in Switzerland[END_REF]. Macroscopic charcoal accumulation rate (CHAR) interpolated to 8 years (black), charcoal background modelled using a 500-year smoothing window (grey line), while red line indicates final positive and negative threshold values for peaks identification. Identified CHAR peaks are marked with "+" symbols. Grey shaded areas refer to periods of relatively stable biomass burning as determined by the change-point analysis (the darker the shade the higher the mean CHAR values are). See ESI1 for results obtained with other user-determined parameters (interpolation and smoothing-window widths). c) Fire return interval (FRI) values. Vertical continuous and dotted lines represent significant and non-significant pollen zone boundaries, respectively Fig. 6 Cross-correlograms of charcoal accumulation rates (CHAR), selected pollen percentages and dung-fungi spores' influxes for two phases of different intensity of human pressure. (i) The Middle Ages when human pressure was higher (970-1350 CE; <1350 CE) and (ii) the more recent centuries when human pressure was lower (1600 CE to the present; > 1600 CE). Horizontal axis shows the lag. One lag is equal to c. 30 years for phase (i) and to c. 20 years for phase (ii). Vertical axis: correlation coefficients; dashed horizontal lines: 95% confidence limits Fig. 7 Comparison between vegetation dynamics (pollen and non-pollen palynomorphs: filled areas; plant macrofossils: black barplots; stomata: full circles), macroscopic charcoal (CHAR) inferred fire history (red crosses: higher-severity fire events), and magnetic-susceptibility (MS) inferred erosion history (black and blue crosses: erosion events) at Biogradska Gora, and warm-season (May-August, MAMJJA) temperature (see ESI1 for further details). The bottom panels show the tree cover at Prokoško Jezero, Bosnia-Herzegovina [START_REF] Dörfler | Prokoško Jezero: An environmental record from a subalpine lake in Bosnia-Herzegovina[END_REF] and the abundance of total closed forest in Europe [START_REF] Fyfe | From forest to farmland: pollen-inferred land cover change across Europe using the pseudobiomization approach[END_REF]

Figures and Figure captions

  The continuous finds of pollen and plant macrofossils of the half-shade demanding Sambucus from 950 to 1150 CE indicate the presence of clearings. The transition to a land-use phase(1150( -1350 CE) CE), which is demonstrated by high abundance of primary anthropogenic indicators and adventives as well as by Sporormiella and Tilletia spores, is marked by a short-term expansion of Rhamnus (1050-1150 CE). Anthropogenic indicators and herb pollen abundances distinctly decrease around 1350 CE (onset of zone 1b) indicating a sudden abandonment of pasture and cultivation. Higher abundance of arboreal pollen percentages in conjunction with angiosperm leaves and fern spores indicates the establishment of broadleaf trees with a fern understorey. Picea was present in the surroundings, as shown by stomata and plant-macrofossil finds. The pollen record shows the expansion of trees and shrubs that typically colonise abandoned pastures (Sambucus, Betula, Alnus, Ulmus and Acer). A century later (around 1450 CE) pollen, stomata and plant-macrofossils of shade-tolerant Abies and Fagus trees increased. The development of a mixed woodland was interrupted by a short-term and milder land-use phase (1500-1600 CE), as suggested by the slight rise of primary and secondary anthropogenic indicators, fire-adapted Pteridium and upland herbs. Local conifer populations collapsed during this second land-use phase (onset of zone 2: 1590 CE) and a Fagusdominated forest gradually established around the site. Pollen and plant macrofossils indicate that light-demanding woody species (Corylus, Betula) expanded faster than the shade-tolerant Fagus, which peaked around 100 years later (1700 CE). Fagus and Fraxinus pollen as well as their plant macrofossils markedly decreased between 1760 and 1850 CE in conjunction with a slight rise in Sporormiella and Veratrum spores, which indicates a third landuse phase characterised by grazing. During the past 170 years (zone 3; 1850 CE to present), a Fagus-dominated forest type developed with increasing abundance of Ulmus, Alnus, Fraxinus and Acer, low abundance of anthropogenic indicators, and decreasing abundance of pioneer trees and shrubs (Corylus and Betula). Tree cover has been highest since 1950 CE.

Fig. 1 Fig. 2

 12 Fig. 1 Map showing the distribution of land-cover types in the Biogradska Gora National Park obtained through the remote-sensing analysis of Pléiades satellite images. Circles indicate the locations of field-survey plots (colourcoded by forest structural type, FST). The star shows the location of the palaeoecological site. The inset shows the study area location in a larger spatial context Fig. 2 Cumulative diametric (DBH) class distributions in the field-survey plots grouped by forest structural type Fig. 3 Boxplots illustrating differences among forest structural types in the Biogradska Gora forest. Whiskers represent the first and third quartiles of the distributions, and the horizontal black lines are referred to the median values. Y-axis indicates values of coarse woody debris (CWD), dead to live wood ratio, Tree diameter diversity index (TDD), Gini index referred to the basal area (GBA), diameter standard deviation (DBHSD), basal area (BA) and path distance

Figure 4

 4 Figure 4 Pollen percentage (continuous curves) and plant macrofossil (black bar plots) concentrations diagram of selected taxa from the small pond in the Biogradska Gora valley. Horizontal continuous and dotted lines represent significant and non-significant pollen zone boundaries, respectively. See ESI1 for more detailed pollen and plant-macrofossil diagrams Fig. 5 Comparison between erosion and charcoal-derived fire history. a) Magnetic susceptibility (MS); b)

Acknowledgements

We are grateful to D. D'Aprile for help during fieldwork, to I. Figueral, L. Bouby and F. Wagner-Cremer for help with identification of plant-macrofossil, wood and charcoal pieces and Fagus stomata, and to R. Marzano, D.

Ascoli, C. Urbinati, D. McKey, E. Ilardi, and D. Barbaro for discussions. We thank the Biogradska Gora National Park for granting permission to collect sediments and perform the field surveys.

Availability of data and material: All data will be made publicly available upon acceptance. The palaeoecological data (pollen, spores, stomata, plant macrofossils, macroscopic charcoal, and magnetic susceptibility) will be uploaded to the Neotoma database (DOI: 10.21233/XYZZ-XYZZ) through the European Pollen Database. The forest structure and composition data will be uploaded to Figshare (figshare.com).

Code availability (software application or custom code): The custom-made computer code in R will be available on GitHub (https://github.com/wfinsinger) and archived in Zenodo (https://zenodo.org/) upon acceptance.

Declarations

Authors' contributions

20

WF, RM, EL, MG, and EC conceived the ideas and designed methodology; EC, WF, EL, MG, NM, FM, LP collected the data; EC, WF and DM analysed the data; EC, WF, and EL led the writing of the manuscript; MG, RM, LP, NM, FM, MC, VS, IB reviewed the manuscript. All authors contributed critically to the drafts and gave final approval for publication.