Reliable quantitative vegetation reconstructions for Europe during the Holocene are crucial to improving our understanding of landscape dynamics, making it possible to assess the past effects of environmental variables and land-use change on ecosystems and biodiversity, and mitigating their effects in the future. We present here the most spatially extensive and temporally continuous pollen-based reconstructions of plant cover in Europe (at a spatial resolution of 1 degrees x 1 degrees) over the Holocene (last 11.7 ka BP) using the 'Regional Estimates of VEgetation Abundance from Large Sites' (REVEALS) model. This study has three main aims. First, to present the most accurate and reliable generation of REVEALS reconstructions across Europe so far. This has been achieved by including a larger number of pollen records compared to former analyses, in particular from the Mediterranean area. Second, to discuss methodological issues in the quantification of past land cover by using alternative datasets of relative pollen productivities (RPPs), one of the key input parameters of REVEALS, to test model sensitivity. Finally, to validate our reconstructions with the global forest change dataset. The results suggest that the RPPs.st1 (31 taxa) dataset is best suited to producing regional vegetation cover estimates for Europe. These reconstructions offer a long-term perspective providing unique possibilities to explore spatial-temporal changes in past land cover and biodiversity.

Quantitative reconstructions of past land cover are necessary to determine the processes involved in climate-human-land-cover interactions. We present the first temporally continuous and most spatially extensive pollen-based land-cover reconstruction for Europe over the Holocene (last 11 700 cal yr BP). We describe how vegetation cover has been quantified from pollen records at a 1 degrees x 1 degrees spatial scale using the "Regional Estimates of VEgetation Abundance from Large Sites" (REVEALS) model. REVEALS calculates estimates of past regional vegetation cover in proportions or percentages. REVEALS has been applied to 1128 pollen records across Europe and part of the eastern Mediterranean-Black Sea-Caspian corridor (30-75 degrees N, 25 degrees W-50 degrees E) to reconstruct the percentage cover of 31 plant taxa assigned to 12 plant functional types (PFTs) and 3 land-cover types (LCTs). A new synthesis of relative pollen productivities (RPPs) for European plant taxa was performed for this reconstruction. It includes multiple RPP values (>= 2 values) for 39 taxa and single values for 15 taxa (total of 54 taxa). To illustrate this, we present distribution maps for five taxa (Calluna vulgaris, Cerealia type (t)., Picea abies, deciduous Quercus t. and evergreen Quercus t.) and three land-cover types (open land, OL; evergreen trees, ETs; and summer-green trees, STs) for eight selected time windows. The reliability of the REVEALS reconstructions and issues related to the interpretation of the results in terms of landscape openness and human-induced vegetation change are discussed. This is followed by a review of the current use of this reconstruction and its future potential utility and development. REVEALS data quality are primarily determined by pollen count data (pollen count and sample, pollen identification, and chronology) and site type and number (lake or bog, large or small, one site vs. multiple sites) used for REVEALS analysis (for each grid cell). A large number of sites with high-quality pollen count data will produce more reliable land-cover estimates with lower standard errors compared to a low number of sites with lower-quality pollen count data. The REVEALS data presented here can be downloaded from https://doi.org/10.1594/PANGAEA.937075 (Fyfe et al., 2022).

Land-cover changes have a clear impact on local climates via biophysical effects. European land cover has been affected by human activities for at least 6000 years, but possibly longer. It is thus highly probable that humans altered climate before the industrial revolution (AD1750-1850). In this study, climate and vegetation 6000 years (6 ka) ago is investigated using one global climate model, two regional climate models, one dynamical vegetation model, pollen-based reconstruction of past vegetation cover using a model of the pollen-vegetation relationship and a statistical model for spatial interpolation of the reconstructed land cover. This approach enables us to study 6 ka climate with potential natural and reconstructed land cover, and to determine how differences in land cover impact upon simulated climate. The use of two regional climate models enables us to discuss the robustness of the results. This is the first experiment with two regional climate models of simulated palaeo-climate based on regional climate models. Different estimates of 6 ka vegetation are constructed: simulated potential vegetation and reconstructed vegetation. Potential vegetation is the natural climate-induced vegetation as simulated by a dynamical vegetation model driven by climate conditions from a climate model. Bayesian spatial model interpolated point estimates of pollen-based plant abundances combined with estimates of climate-induced potential un-vegetated land cover were used for reconstructed vegetation. The simulated potential vegetation is heavily dominated by forests: evergreen coniferous forests dominate in northern and eastern Europe, while deciduous broadleaved forests dominate central and western Europe. In contrast, the reconstructed vegetation cover has a large component of open land in most of Europe. The simulated 6 ka climate using reconstructed vegetation was 0-5 degrees C warmer than the pre-industrial (PI) climate, depending on season and region. The largest differences are seen in north-eastern Europe in winter with about 4-6 degrees C, and the smallest differences (close to zero) in southwestern Europe in winter. The simulated 6 ka climate had 10-20% more precipitation than PI climate in northern Europe and 10-20% less precipitation in southern Europe in summer. The results are in reasonable agreement with proxy-based climate reconstructions and previous similar climate modelling studies. As expected, the global model and regional models indicate relatively similar climates albeit with regional differences indicating that, models response to land-cover changes differently. The results indicate that the anthropogenic land-cover changes, as given by the reconstructed vegetation, in this study are large enough to have a significant impact on climate. It is likely that anthropogenic impact on European climate via land-use change was already taking place at 6 ka. Our results suggest that anthropogenic land-cover changes at 6 ka lead to around 0.5 degrees C warmer in southern Europe in summer due to biogeophysical forcing. (C) 2022 The Authors. Published by Elsevier Ltd.

Realistic and accurate reconstructions of past vegetation cover are necessary to study past environmental changes. This is important since the effects of human land-use changes (e.g. agriculture, deforestation and afforestation/reforestation) on biodiversity and climate are still under debate. Over the last decade, development, validation, and application of pollen-vegetation relationship models have made it possible to estimate plant abundance from fossil pollen data at both local and regional scales. In particular, the REVEALS model has been applied to produce datasets of past regional plant cover at 1 degrees spatial resolution at large subcontinental scales (North America, Europe, and China). However, such reconstructions are spatially discontinuous due to the discrete and irregular geographical distribution of sites (lakes and peat bogs) from which fossil pollen records have been produced. Therefore, spatial statistical models have been developed to create continuous maps of past plant cover using the REVEALS-based land cover estimates. In this paper, we present the first continuous time series of spatially complete maps of past plant cover across Europe during the Holocene (25 time windows covering the period from 11.7 k BP to present). We use a spatial-statistical model for compositional data to interpolate REVEALS-based estimates of three major land-cover types (LCTs), i.e., evergreen trees, summer-green trees and open land (grasses, herbs and low shrubs); producing spatially complete maps of the past coverage of these three LCTs. The spatial model uses four auxiliary data sets-latitude, longitude, elevation, and independent scenarios of past anthropogenic land-cover change based on per-capita land-use estimates ("standard" KK10 scenarios)-to improve model performance for areas with complex topography or few observations. We evaluate the resulting reconstructions for selected time windows using present day maps from the European Forest Institute, cross validate, and compare the results with earlier pollen-based spatially-continuous estimates for five selected time windows, i.e., 100 BP-present, 350-100 BP, 700-350 BP, 3.2-2.7 k BP, and 6.2-5.7 k BP. The evaluations suggest that the statistical model provides robust spatial reconstructions. From the maps we observe the broad change in the land-cover of Europe from dominance of naturally open land and persisting remnants of continental ice in the Early Holocene to a high fraction of forest cover in the Mid Holocene, and anthropogenic deforestation in the Late Holocene. The temporal and spatial continuity is relevant for land-use, land-cover, and climate research.

8000 years ago, prior to Neolithic agriculture, Europe was mostly a wooded continent. Since then, its forest cover has been progressively fragmented, so that today it covers less than half of Europe's land area, in many cases having been cleared to make way for fields and pasture-land. Establishing the origin of Europe's current, more open land-cover mosaic requires a long-term perspective, for which pollen analysis offers a key tool. In this study we utilise and compare three numerical approaches to transforming pollen data into past forest cover, drawing on >1000 C-14-dated site records. All reconstructions highlight the different histories of the mixed temperate and the northern boreal forests, with the former declining progressively since similar to 6000 years ago, linked to forest clearance for agriculture in later prehistory (especially in northwest Europe) and early historic times (e.g. in north central Europe). In contrast, extensive human impact on the needle-leaf forests of northern Europe only becomes detectable in the last two millennia and has left a larger area of forest in place. Forest loss has been a dominant feature of Europe's landscape ecology in the second half of the current interglacial, with consequences for carbon cycling, ecosystem functioning and biodiversity.

QuestionsWe investigated the changing role of climate, forest fires and human population size in the broad-scale compositional changes in Holocene vegetation dynamics before and after the onset of farming in Sweden (at 6,000cal yr BP) and in Finland (at 4,000calyr BP). LocationSouthern and central Sweden, SW and SE Finland. MethodsHolocene regional plant abundances were reconstructed using the REVEALS model on selected fossil pollen records from lakes. The relative importance of climate, fires and human population size on changes in vegetation composition was assessed using variation partitioning. Past climate variable was derived from the LOVECLIM climate model. Fire variable was reconstructed from sedimentary charcoal records. Estimated trend in human population size was based on the temporal distribution of archaeological radiocarbon dates. ResultsClimate explains the highest proportion of variation in vegetation composition during the whole study period in Sweden (10,000-4,000cal yr BP) and in Finland (10,000-1,000cal yr BP), and during the pre-agricultural period. In general, fires explain a relatively low proportion of variation. Human population size has significant effect on vegetation dynamics after the onset of farming and explains the highest variation in vegetation in S Sweden and SW Finland. ConclusionsMesolithic hunter-gatherer populations did not significantly affect vegetation composition in Fennoscandia, and climate was the main driver of changes at that time. Agricultural communities, however, had greater effect on vegetation dynamics, and the role of human population size became a more important factor during the late Holocene. Our results demonstrate that climate can be considered the main driver of long-term vegetation dynamics in Fennoscandia. However, in some regions the influence of human population size on Holocene vegetation changes exceeded that of climate and has a longevity dating to the early Neolithic.

Anthropogenic land cover change (ALCC) is the most important transformation of the Earth system that occurred in the preindustrial Holocene, with implications for carbon, water and sediment cycles, biodiversity and the provision of ecosystem services and regional and global climate. For example, anthropogenic deforestation in preindustrial Eurasia may have led to feedbacks to the climate system: both biogeophysical, regionally amplifying winter cold and summer warm temperatures, and biogeochemical, stabilizing atmospheric CO2 concentrations and thus influencing global climate. Quantification of these effects is difficult, however, because scenarios of anthropogenic land cover change over the Holocene vary widely, with increasing disagreement back in time. Because land cover change had such widespread ramifications for the Earth system, it is essential to assess current ALCC scenarios in light of observations and provide guidance on which models are most realistic. Here, we perform a systematic evaluation of two widely-used ALCC scenarios (KK10 and HYDE3.1) in northern and part of central Europe using an independent, pollen-based reconstruction of Holocene land cover (REVEALS). Considering that ALCC in Europe primarily resulted in deforestation, we comparemodeled land use with the cover of non-forest vegetation inferred from the pollen data. Though neither land cover change scenario matches the pollen-based reconstructions precisely, KK10 correlates well with REVEALS at the country scale, while HYDE systematically underestimates land use with increasing magnitude with time in the past. Discrepancies between modeled and reconstructed land use are caused by a number of factors, including assumptions of per-capita land use and socio-cultural factors that cannot be predicted on the basis of the characteristics of the physical environment, including dietary preferences, long-distance trade, the location of urban areas and social organization.

Early agriculture can be detected in palaeovegetation records, but quantification of the relative importance of climate and land use in influencing regional vegetation composition since the onset of agriculture is a topic that is rarely addressed. We present a novel approach that combines pollen-based REVEALS estimates of plant cover with climate, anthropogenic land-cover and dynamic vegetation modelling results. This is used to quantify the relative impacts of land use and climate on Holocene vegetation at a sub-continental scale, i.e. northern and western Europe north of the Alps. We use redundancy analysis and variation partitioning to quantify the percentage of variation in vegetation composition explained by the climate and land-use variables, and Monte Carlo permutation tests to assess the statistical significance of each variable. We further use a similarity index to combine pollen based REVEALS estimates with climate-driven dynamic vegetation modelling results. The overall results indicate that climate is the major driver of vegetation when the Holocene is considered as a whole and at the sub-continental scale, although land use is important regionally. Four critical phases of land-use effects on vegetation are identified. The first phase (from 7000 to 6500 BP) corresponds to the early impacts on vegetation of farming and Neolithic forest clearance and to the dominance of climate as a driver of vegetation change. During the second phase (from 4500 to 4000 BP), land use becomes a major control of vegetation. Climate is still the principal driver, although its influence decreases gradually. The third phase (from 2000 to 1500 BP) is characterised by the continued role of climate on vegetation as a consequence of late-Holocene climate shifts and specific climate events that influence vegetation as well as land use. The last phase (from 500 to 350 BP) shows an acceleration of vegetation changes, in particular during the last century, caused by new farming practices and forestry in response to population growth and industrialization. This is a unique signature of anthropogenic impact within the Holocene but European vegetation remains climatically sensitive and thus may continue to respond to ongoing climate change. (C) 2017 Elsevier Ltd. All rights reserved.

In this paper we test the performance of the Regional Estimates of VEgetation Abundance from Large Sites (REVEALS) model using pollen records from multiple small sites. We use Holocene pollen records from large and small sites in southern Sweden to identify what is/are the most significant variable(s) affecting the REVEALS-based reconstructions, i.e. type of site (lakes and/or bogs), number of sites, site size, site location in relation to vegetation zones, and/or distance between small sites and large sites. To achieve this objective we grouped the small sites according to (i) the two major modern vegetation zones of the study region, and (ii) the distance between the small sites and large lakes, i.e. small sites within 50, 100, 150, or 200 km of the large lakes. The REVEALS-based reconstructions were performed using 24 pollen taxa. Redundancy analysis was performed on the results from all REVEALS-model runs using the groups within (i) and (ii) separately, and on the results from all runs using the groups within (ii) together. The explanatory power and significance of the variables were identified using forward selection and Monte Carlo permutation tests. The results show that (a) although the REVEALS model was designed for pollen data from large lakes, it also performs well with pollen data from multiple small sites in reconstructing the percentage cover of groups of plant taxa (e.g. open land taxa, summer-green trees, evergreen trees) or individual plant taxa; however, in the case of this study area, the reconstruction of the percentage cover of Calluna vulgaris, Cyperaceae, and Betula may be problematic when using small bogs; (b) standard errors of multiple small-site REVEALS estimates will generally be larger than those obtained using pollen records from large lakes, and they will decrease with increasing size of pollen counts and increasing number of small sites; (c) small lakes are better to use than small bogs if the total number of small sites is low; and (d) the size of small sites and the distance between them do not play a major role, but the distance between the small sites and landscape/vegetation boundaries is a determinant factor for the accuracy of the vegetation reconstructions.

Anthropogenic land-cover change (ALCC) is one of the few climate forcings for which the net direction of the climate response over the last two centuries is still not known. The uncertainty is due to the often counteracting temperature responses to the many biogeophysical effects and to the biogeochemical versus biogeophysical effects. Palaeoecological studies show that the major transformation of the landscape by anthropogenic activities in the southern zone of the Baltic Sea basin occurred between 6000 and 3000/2500 cal year BP. The only modelling study of the biogeophysical effects of past ALCCs on regional climate in north-western Europe suggests that deforestation between 6000 and 200 cal year BP may have caused significant change in winter and summer temperature. There is no indication that deforestation in the Baltic Sea area since AD 1850 would have been a major cause of the recent climate warming in the region through a positive biogeochemical feedback. Several model studies suggest that boreal reforestation might not be an effective climate warming mitigation tool as it might lead to increased warming through biogeophysical processes.