The Landscape Reconstruction Algorithm (Sugita 2007a,b) includes two models, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites) that estimates vegetation abundance (% cover) within an area of ca. 100 km x 100 km, and LOVE (LOcal Vegetation Estimates) that estimates vegetation abundance at the local spatial scale, i.e. within the Relevant Source Area of Pollen (RSAP sensu Sugita, 2004) that is the smallest area around the study site for which the reconstruction is valid. The RSAP is estimated by the LOVE model and varies between sites and vegetation settings; so far, it was estimated to vary between < 1 - < 10 km in most ecological settings of the Holocene in NW Europe. We used the REVEALS model and over 600 pollen records from pollen data bases and individual researchers to reconstruct land-cover in NW Europe N of the Alps for key time windows of the Holocene in order to assess model-based reconstructions of anthropogenic land-cover change (ALCC) (e.g. Kaplan et al., 2009) and model (LPJ-GUESS) simulations of past potential (climate-induced vegetation), and to study past land cover – climate interactions using a regional climate model (RCA3). We used the REVEALS model and the complete LRA approach (REVEALS + LOVE models) along with two pollen records from large lakes and three pollen records from small bogs to reconstruct the local-scale land-cover in central Småland, southern Sweden, to study the relationship between vegetation composition, fire, climate and human impact at the regional and local spatial scales with the objective to discuss biodiversity issues. Our results suggest that i) past subcontinental to regional ALCC did influence regional climate through biogeophysical processes at the landatmosphere interface (Strandberg et al., submitted), and ii) local land-cover change, both natural and anthropogenic, govern environmental changes such as fire and biodiversity (Cui et al., 2013; Cui et al., submitted).

There is a long tradition of collaboration between palaeoecologists and archaeologists in many parts of the world with the purpose of reconstructing the environment of humans through time and the study of the interactions between humans and their environment. Vegetation (i.e. vegetated landscapes and plants) has long been one of the most important parts of the environment for humans’ resources. Thanks to the interpretation of palaeoecological data such as pollen and plant macrofossils, it is well known that humans have used plants for their subsistence and formed many landscapes of the Earth through their activities over many millennia. Pollen analysis in particular has been used to reconstruct the landscapes of humans in order i) to learn something on their use of the landscape for building material, grazing and food (e.g. woods, grazed land, cultivated fields), and ii) to understand their influence on the landscape through deforestation in particular. Pollen data as proxy records of vegetation have been very useful to provide qualitative descriptions of cultural landscapes through time in terms of the presence of major tree, shrub and herb species, and the character of the landscape, wooded, “half-wooded” (or partly wooded), and primarily open (poorly wooded) (1). Efforts to calibrate pollen onto land-use in the 1990ies has made possible to provide more precise and detailed interpretation of pollen records in terms of land-use type (2). However, when it came to questions related to the size of cultivated land or grazed land in relation to wooded land, interpretation of pollen records has been problematic until recently. The non-linear relationship between pollen and vegetation due to inter-taxonomic differences in pollen productivity and pollen dispersion and deposition characteristics of plant taxa has long hampered estimation of the percentage cover of plant taxa or landscape units in the past. Thanks torecent developments in pollen-vegetation modelling, a new approach - the Landscape Reconstruction Algorithm (LRA) (3, 4) - makes it possible to estimate the cover of plant taxa or landscape units at both regional and local spatial scales using pollen records. The LRA has been tested and applied in various types of studies in Europe in particular. Examples from Europe and Scandinavia show that pollen-based quantitative reconstructions of vegetation cover, in combination with other palaeoecological records such as insect and plant macroremains, show the great potential of such studies to provide new insights on the use of landscapes and vegetation by humans in the past and its environmental consequences at both regional and local spatial scales (5, 6). These results provide a new environmental framework for the discussion and testing of hypotheses based on archaeological data.

We reviewed the recent published scientific literature on land cover-climate interactions at the global and regional spatial scales with the aim to assess whether it is convincingly demonstrated that anthropogenic land-cover change (ALCC) has been (over the last centuries and millennia) a significant climate forcing at the global scale, and more specifically at the scale of the Baltic Sea catchment area. The conclusions from this review are as follows: i) anthropogenic land-cover change (ALCC) is one of the few climate forcings for which the net direction of the climate response in the past is still not known. The uncertainty is due to the often counteracting temperature responses to the many biogeophysical effects, and to the biogeochemical vs biogeophysical effects; ii) 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; iii) 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; iv) palaeoecological studies indicate a major transformation of the landscape by anthropogenic activities in the southern zone of the study region occurring between 6000 and 3000/2500 calendar years before present (cal. BP) (1) ; v) the only modelling study so far of the biogeophysical effects of past ALCCs on regional climate in Europe suggests that a deforestation of the magnitude of that reconstructed for the past (between 6000 and 200 cal BP) can produce changes in winter and summer temperatures of +/- 1, the sign of the change depending on the season and the region (2). Thus, if ALCC and their biogeophysical effects did matter in the past, they should matter today and in the future. A still prevailing idea is that planting trees will mitigate climate warming through biogeochemical effects. Therefore, there is still an urgent need to better understand the biogeophysical effects on regional and continental climate of afforestation in the hemiboreal and boreal regions, and their significance in relation to the biogeochemical effects.

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.

The LANDCLIM (LAND cover – CLIMate interactions in NW Europe during the Holocene) project has the overall aim to quantify human-induced changes in regional vegetation/land-cover in northwestern and western Europe North of the Alps during the Holocene (the last 11 500 years) with the purpose to evaluate and further refine the dynamic vegetation model LPJGUESS and the regional climate model RCA3, and to assess the possible effects on the climate development of two historical processes, i.e. climate-driven changes in vegetation and human-induced changes in land cover, via the influence of forested versus non-forested land cover on shortwave albedo, energy and water fluxes. Accounting for land surface changes may be particularly important for regional climate modeling, as the biophysical feedbacks operate at this scale. The aims of the LANDCLIM project are achieved by applying a model-data comparison scheme. The REVEALS model is used to estimate land cover from pollen data for 10 plant functional types (PFTs) and 5 time windows of the Holocene - modern time, 200 BP, 500 BP, 3000 BP and 6000 BP. The REVEALS estimates are then compared to the LPJGUESS simulations of potential vegetation and with the ALCC scenarios of Kaplan et al. (KK10) and Klein-Goldewijk et al. (HYDE). The alternative descriptions of past land-cover are then used in the regional climate model RCA3 to study the effect of anthropogenic land-cover on climate. The model-simulated climate is finally compared to palaeoclimate proxies other than pollen. The REVEALS estimates demonstrate that the study region was characterized by larger areas of human-induced openland than pollen percentages suggest, and that these areas were already very large by 3000 BP. The KK10 scenarios were found to be closer to the REVEALS estimates than the HYDE scenarios. LPJGUESS simulates potential climate-induced vegetation. The results from the RCA3 runs at 200 BP and 6000 BP using the LPJGUESS and KK10 land-cover descriptions indicate that past human-induced deforestation did produce a decrease in summer temperatures of >0 - 1.5°C due to biogeophysical processes, and that the degree of decrease differed between regions; the effect of human-induced deforestation on winter temperatures was shown to be more complex. The positive property of forests as CO2 sinks is well known. But afforestation (i.e. planting forest) may also have the opposite effect of warming the climate through biogeophysical processes. Careful studies on land cover-climate interactions are essential to understand the net result of all possible processes related to anthropogenic land-cover change so that relevant landscape management can be implemented for mitigation of climate warming.

The major objectives of this paper are: (1) to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC) developed during the last ten years, (2) to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites), to infer long-term records of past land-cover from pollen data, (3) to present a new project (LANDCLIM: LAND cover – CLIMate interactions in NW Europe during the Holocene) currently underway, and show preliminary results of REVEALS reconstructions of the regional land-cover in the Czech Republic for five selected time windows of the Holocene, and (4) to discuss the implications and future directions in climate and vegetation/land-cover modeling, and in the assessment of the effects of human-induced changes in land-cover on the regional climate through altered feedbacks. The existing ALCC scenarios show large discrepancies between them, and few cover time periods older than AD 800. When these scenarios are used to assess the impact of human land-use on climate, contrasting results are obtained. It emphasizes the need for methods such as the REVEALS model-based land-cover reconstructions. They might help to fine-tune descriptions of past land-cover and lead to a better understanding of how long-term changes in ALCC might have influenced climate. The REVEALS model is demonstrated to provide better estimates of the regional vegetation/landcover changes than the traditional use of pollen percentages. This will achieve a robust assessment of land cover at regional- to continental-spatial scale throughout the Holocene. We present maps of REVEALS estimates for the percentage cover of 10 plant functional types (PFTs) at 200 BP and 6000 BP, and of the two open-land PFTs “grassland” and “agricultural land” at five time-windows from 6000 BP to recent time. The LANDCLIM results are expected to provide crucial data to reassess ALCC estimates for a better understanding of the land suface-atmosphere interactions.

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).

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.

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.

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.

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.

We present pollen-based reconstructions of the spatio-temporal dynamics of northern European regional vegetation abundance through the Holocene. We apply the Regional Estimates of VEgetation Abundance from Large Sites (REVEALS) model using fossil pollen records from eighteen sites within five modern biomes in the region. The eighteen sites are classified into four time-trajectory types on the basis of principal components analysis of both the REVEALS-based vegetation estimates (RVs) and the pollen percentage (PPs). The four trajectory types are more clearly separated for RVs than PPs. Further, the timing of major Holocene shifts, rates of compositional change, and diversity indices (turnover and evenness) differ between RVs and PPs. The differences are due to the reduction by REVEALS of biases in fossil pollen assemblages caused by different basin size, and inter-taxonomic differences in pollen productivity and dispersal properties. For example, in comparison to the PPs, the RVs show an earlier increase in Corylus and Ulmus in the early-Holocene and a more pronounced increase in grassland and deforested areas since the mid-Holocene. The results suggest that the influence of deforestation and agricultural activities on plant composition and abundance from Neolithic times was stronger than previously inferred from PPs. Relative to PPs, RVs show a more rapid compositional change, a largest decrease in turnover, and less variable evenness in most of northern Europe since 5200 cal yr BP. All these changes are primarily related to the strong impact of human activities on the vegetation. This study demonstrates that RV-based estimates of diversity indices, timing of shifts, and rates of change in reconstructed vegetation provide new insights into the timing and magnitude of major human distribution on Holocene regional, vegetation, feature that are critical in the assessment of human impact on vegetation, land-cover, biodiversity, and climate in the past.

REVEALS-based quantitative reconstruction of Holocene vegetation cover (expressed in plant functional types. PFTs) is used in the LANDCLIM project to assess the effect of human-induced land-cover change on past climate in NW Europe. Using the Czech Quaternary Pollen Database, this case study evaluates the extent to which selection of data and input parameters for the REVEALS model applications would affect reconstruction outcomes. The REVEALS estimates of PFTs (grid-cell based REVEALS PET estimates, GB REVEALS PFT-s) are calculated for five time windows of the Holocene using fossil pollen records available in each 1 degrees x1 degrees grid cell of the Czech Republic. The input data and parameters selected for testing are: basin type and size, number of C-14 dates used to establish the chronology of the pollen records, number of taxa, and pollen productivity estimates (PPE). We used the Spearman correlation coefficient to test the hypothesis that there is no association between GB REVEALS PET-s using different data and parameter inputs. The results show that differences in the basin size and type, number of dates, number and type of taxa (entomophilous included or not), and PPE dataset do not affect the rank orders of the GB REVEALS PET-s significantly, except for the cases when entomophilous taxa are included. It implies that, given careful selection of data and parameter and interpretation of results, REVEALS applications can use pollen records from lakes and bogs of different sizes together for reconstruction of past land cover at the regional to sub-continental spatial scales for purposes such as the study of past land cover-climate interactions. Our study also provides useful criteria to set up protocols for data compilation REVEALS applications of this kind. (C) 2012 Elsevier B.V. All rights reserved.

Reliable estimates of past land cover are critical for assessing potential effects of anthropogenic land-cover changes on past earth surface-climate feedbacks and landscape complexity. Fossil pollen records from lakes and bogs have provided important information on past natural and human-induced vegetation cover. However, those records provide only point estimates of past land cover, and not the spatially continuous maps at regional and sub-continental scales needed for climate modelling. We propose a set of statistical models that create spatially continuous maps of past land cover by combining two data sets: 1) pollen-based point estimates of past land cover (from the REVEALS model) and 2) spatially continuous estimates of past land cover, obtained by combining simulated potential vegetation (from LPJ-GUESS) with an anthropogenic land-cover change scenario (KK10). The proposed models rely on statistical methodology for compositional data and use Gaussian Markov Random Fields to model spatial dependencies in the data. Land-cover reconstructions are presented for three time windows in Europe: 0.05, 0.2, and 6 ka years before present (BP). The models are evaluated through cross-validation, deviance information criteria and by comparing the reconstruction of the 0.05 ka time window to the present-day land-cover data compiled by the European Forest Institute (EFI). For 0.05 ka, the proposed models provide reconstructions that are closer to the EFI data than either the REVEALS- or LPJ-GUESS/KK10-based estimates; thus the statistical combination of the two estimates improves the reconstruction. The reconstruction by the proposed models for 0.2 ka is also good. For 6 ka, however, the large differences between the REVEALS- and LPJ-GUESS/KK10-based estimates reduce the reliability of the proposed models. Possible reasons for the increased differences between REVEALS and LPJ-GUESS/KK10 for older time periods and further improvement of the proposed models are discussed. (C) 2014 Elsevier B.V. All rights reserved.

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.

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.

This study aims to evaluate the direct effects of anthropogenic deforestation on simulated climate at two contrasting periods in the Holocene, ~6 k BP and ~0.2 k BP in Europe. We apply RCA3, a regional climate model with 50 km spatial resolution, for both time periods, considering three alternative descriptions of the past vegetation: (i) potential natural vegetation (V) simulated by the dynamic vegetation model LPJ-GUESS, (ii) potential vegetation with anthropogenic land cover (deforestation) as simulated by the HYDE model (V + H), and (iii) potential vegetation with anthropogenic land cover as simulated by the KK model (V + K). The KK model estimates are closer to a set of pollen-based reconstructions of vegetation cover than the HYDE model estimates. The climate-model results show that the simulated effects of deforestation depend on both local/regional climate and vegetation characteristics. At ~6 k BP the extent of simulated deforestation in Europe is generally small, but there are areas where deforestation is large enough to produce significant differences in summer temperatures of 0.5–1 °C. At ~0.2 k BP, simulated deforestation is much more extensive than previously assumed, in particular according to the KK model. This leads to significant temperature differences in large parts of Europe in both winter and summer. In winter, deforestation leads to lower temperatures because of the differences in albedo between forested and unforested areas, particularly in the snow-covered regions. In summer, deforestation leads to higher temperatures in central and eastern Europe since evapotranspiration from unforested areas is lower than from forests. Summer evaporation is already limited in the southernmost parts of Europe under potential vegetation conditions and, therefore, cannot become much lower. Accordingly, the albedo effect dominates also in summer, which implies that deforestation causes a decrease in temperatures. Differences in summer temperature due to deforestation range from −1 °C in south-western Europe to +1 °C in eastern Europe. The choice of anthropogenic land cover estimate has a significant influence on the simulated climate, but uncertainties in palaeoclimate proxy data for the two time periods do not allow for a thorough comparison with climate model results.

This study aims to evaluate the direct effects of anthropogenic deforestation on simulated climate at two contrasting periods in the Holocene, similar to 6 and similar to 0.2 k BP in Europe. We apply We apply the Rossby Centre regional climate model RCA3, a regional climate model with 50 km spatial resolution, for both time periods, considering three alternative descriptions of the past vegetation: (i) potential natural vegetation (V) simulated by the dynamic vegetation model LPJ-GUESS, (ii) potential vegetation with anthropogenic land use (deforestation) from the HYDE3.1 (History Database of the Global Environment) scenario (V + H3.1), and (iii) potential vegetation with anthropogenic land use from the KK10 scenario (V + KK10). The climate model results show that the simulated effects of deforestation depend on both local/regional climate and vegetation characteristics. At similar to 6 k BP the extent of simulated deforestation in Europe is generally small, but there are areas where deforestation is large enough to produce significant differences in summer temperatures of 0.5-1 degrees C. At similar to 0.2 k BP, extensive deforestation, particularly according to the KK10 model, leads to significant temperature differences in large parts of Europe in both winter and summer. In winter, deforestation leads to lower temperatures because of the differences in albedo between forested and unforested areas, particularly in the snow-covered regions. In summer, deforestation leads to higher temperatures in central and eastern Europe because evapotranspiration from unforested areas is lower than from forests. Summer evaporation is already limited in the southernmost parts of Europe under potential vegetation conditions and, therefore, cannot become much lower. Accordingly, the albedo effect dominates in southern Europe also in summer, which implies that deforestation causes a decrease in temperatures. Differences in summer temperature due to deforestation range from -1 degrees C in south-western Europe to +1 degrees C in eastern Europe. The choice of anthropogenic land-cover scenario has a significant influence on the simulated climate, but uncertainties in palaeoclimate proxy data for the two time periods do not allow for a definitive discrimination among climate model results.

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.

The major objective of this thesis was to produce descriptions of the land vegetation-cover in Europe for selected time windows of the Holocene (6000, 3000, 500, 200, and 50 calendar years before present (BP=1950)) that can be used in climate modelling. Land vegetation is part of the climate system; its changes influence climate through biogeophysical and biogeochemical processes. Land use such as deforestation is one of the external forcings of climate change.  Reliable descriptions of vegetation cover in the past are needed to study land cover-climate interactions and understand the possible effects of present and future land-use changes on future climate.

We tested and applied the REVEALS (Regional Estimates of VEgetation Abundance from Large Sites) model to estimate past vegetation in percentage cover over Europe using pollen records from lake sediments and peat bogs. The model corrects for the biases of pollen data due to intraspecific differences in pollen productivity and pollen dispersion and deposition in lakes and bogs. For the land-cover reconstructions in Europe and the Baltic Sea catchment we used 636 (grouped by 1˚x1˚ grid cells) and 339 (grouped by biogeographical regions) pollen records, respectively. The REVEALS reconstructions were performed for 25 tree, shrub and herb taxa. The grid-based REVEALS reconstructions were then interpolated using a set of statistical spatial models.

We show that the choice of input parameters for the REVEALS application does not affect the ranking of the REVEALS estimates significantly, except when entomophilous taxa are included. We demonstrate that pollen data from multiple small sites provide REVEALS estimates that are comparable to those obtained with pollen data from large lakes, however with larger error estimates. The distance between the small sites does not influence the results significantly as long as the sites are at a sufficient distance from vegetation zone boundaries. The REVEALS estimates of open land for Europe and the Baltic Sea catchment indicate that the degree of landscape openness during the Holocene was significantly higher than previously interpreted from pollen percentages. The relationship between Pinus and Picea and between evergreen and summer-green taxa may also differ strongly whether it is based on REVEALS percentage cover or pollen percentages. These results provide entirely new insights on Holocene vegetation history and help understanding questions related to resource management by humans and biodiversity in the past. The statistical spatial models provide for the first time pollen-based descriptions of past land cover that can be used in climate modelling and studies of land cover-climate interactions in the past.

We present quantitative reconstructions of regional vegetation cover in north-western Europe, western Europe north of the Alps, and eastern Europe for five time windows in the Holocene [around 6k, 3k, 0.5k, 0.2k, and 0.05k calendar years before present (bp)] at a 1 degrees x1 degrees spatial scale with the objective of producing vegetation descriptions suitable for climate modelling. The REVEALS model was applied on 636 pollen records from lakes and bogs to reconstruct the past cover of 25 plant taxa grouped into 10 plant-functional types and three land-cover types [evergreen trees, summer-green (deciduous) trees, and open land]. The model corrects for some of the biases in pollen percentages by using pollen productivity estimates and fall speeds of pollen, and by applying simple but robust models of pollen dispersal and deposition. The emerging patterns of tree migration and deforestation between 6k bp and modern time in the REVEALS estimates agree with our general understanding of the vegetation history of Europe based on pollen percentages. However, the degree of anthropogenic deforestation (i.e. cover of cultivated and grazing land) at 3k, 0.5k, and 0.2k bp is significantly higher than deduced from pollen percentages. This is also the case at 6k in some parts of Europe, in particular Britain and Ireland. Furthermore, the relationship between summer-green and evergreen trees, and between individual tree taxa, differs significantly when expressed as pollen percentages or as REVEALS estimates of tree cover. For instance, when Pinus is dominant over Picea as pollen percentages, Picea is dominant over Pinus as REVEALS estimates. These differences play a major role in the reconstruction of European landscapes and for the study of land cover-climate interactions, biodiversity and human resources.

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.