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We collected the available relative pollen productivity estimates (PPEs) for 27 major pollen taxa from Eurasia and applied them to estimate plant abundances during the last 40 ka cal BP (calibrated thousand years before present) using pollen counts from 203 fossil pollen records in northern Asia (north of 40∘ N). These pollen records were organized into 42 site groups and regional mean plant abundances calculated using the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. Time-series clustering, constrained hierarchical clustering, and detrended canonical correspondence analysis were performed to investigate the regional pattern, time, and strength of vegetation changes, respectively. Reconstructed regional plant functional type (PFT) components for each site group are generally consistent with modern vegetation in that vegetation changes within the regions are characterized by minor changes in the abundance of PFTs rather than by an increase in new PFTs, particularly during the Holocene. We argue that pollen-based REVEALS estimates of plant abundances should be a more reliable reflection of the vegetation as pollen may overestimate the turnover, particularly when a high pollen producer invades areas dominated by low pollen producers. Comparisons with vegetation-independent climate records show that climate change is the primary factor driving land-cover changes at broad spatial and temporal scales. Vegetation changes in certain regions or periods, however, could not be explained by direct climate change, e.g. inland Siberia, where a sharp increase in evergreen conifer tree abundance occurred at ca. 7–8 ka cal BP despite an unchanging climate, potentially reflecting their response to complex climate–permafrost–fire–vegetation interactions and thus a possible long-term lagged climate response.

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 CO 2 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 compare modeled 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.

Model-based quantitative reconstruction of past plant cover in Europe has shown great potential for: (i) testing hypotheses related to Holocene vegetation dynamics, biodiversity, and their relationships with climate and land use; (ii) studying long term interactions between climate and land use. Similar model-based quantitative reconstruction of plant cover in China has been restricted due to the lack of standardized datasets of existing estimates of relative pollen productivity (RPP). This study presents the first synthesis of all RPP values available to date for 39 major plant taxa from temperate China and proposes standardized RPP datasets that can be used for model-based quantitative reconstructions of past plant cover using fossil pollen records for the region. We review 11 RPP studies in temperate China based on modern pollen and related vegetation data around the pollen samples. The study areas include meadow, steppe and desert vegetation, various woodland types, and cultural landscapes. We evaluate the strategies of each study in terms of selection of study areas and distribution of study sites; pollen- and vegetation-data collection in field; vegetation-data collection from satellite images and vegetation maps; and data analysis. We compare all available RPP estimates, select values based on precise rules and calculate mean RPP estimates. We propose two standardized RPP datasets for 31 (Alt1) and 29 (Alt2) plant taxa. The ranking of mean RPPs (Alt-2) relative to Poaceae (= 1) for eight major taxa is: (21) > (18.4) > (12.5) > (11.5) > Elaeagnaceae (8.8) > (7.5) > Compositae (4.5) > Amaranthaceae/Chenopodiaceae (4). We conclude that although RPPs are comparable between Europe and China for some genera and families, they can differ very significantly, e.g., , Compositae, and Amaranthaceae/Chenopodiaceae. For some taxa, we present the first RPP estimates e.g. , Elaeagnaceae, and . The proposed standardized RPP datasets are essential for model-based reconstructions of past plant cover using fossil pollen records from temperate China.

We compare Holocene tree cover changes in Europe derived from a transient Earth system model simulation (Max Planck Institute Earth System Model – MPI-ESM1.2, including the land surface and dynamic vegetation model JSBACH) with high-spatial-resolution time slice simulations performed in the dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator) and pollen-based quantitative reconstructions of tree cover based on the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. The dynamic vegetation models and REVEALS agree with respect to the general temporal trends in tree cover for most parts of Europe, with a large tree cover during the mid-Holocene and a substantially smaller tree cover closer to the present time. However, the decrease in tree cover in REVEALS starts much earlier than in the models, indicating much earlier anthropogenic deforestation than the prescribed land use in the models. While LPJ-GUESS generally overestimates tree cover compared to the reconstructions, MPI-ESM indicates lower percentages of tree cover than REVEALS, particularly in central Europe and the British Isles. A comparison of the simulated climate with chironomid-based climate reconstructions reveals that model–data mismatches in tree cover are in most cases not driven by biases in the climate. Instead, sensitivity experiments indicate that the model results strongly depend on the tuning of the models regarding natural disturbance regimes (e.g. fire and wind throw). The frequency and strength of disturbances are – like most of the parameters in the vegetation models – static and calibrated to modern conditions. However, these parameter values may not be valid for past climate and vegetation states totally different from today's. In particular, the mid-Holocene natural forests were probably more stable and less sensitive to disturbances than present-day forests that are heavily altered by human interventions. Our analysis highlights the fact that such model settings are inappropriate for paleo-simulations and complicate model–data comparisons with additional challenges. Moreover, our study suggests that land use is the main driver of forest decline in Europe during the mid-Holocene and late Holocene.

The Landscape Reconstruction Algorithm (LRA) is regarded as the soundest approach for quantifying taxon-specific plant cover from pollen data. The reliability of relative pollen productivity (RPP) estimates is fundamental in the accuracy of quantitative vegetation reconstruction using the LRA approach. Inconsistent RPP estimates produced by different studies can cast doubt on the reliability and applicability of quantitative vegetation reconstruction. Therefore, it is crucial that the RPP estimates are evaluated before being applied for quantitative vegetation reconstruction. We have tested two alternative approaches, namely, a leave-one-out cross-validation (LOO) method and a splitting-by-subregion strategy, using surface pollen assemblages and the REVEALS model—the first step in the LRA—to evaluate the reliability of RPPs estimates of 10 target taxa obtained in the cultural landscape of Shandong. We compared the REVEALS estimates (RVs) with observations of regional vegetation abundance (OBVs) and pollen proportions (PPs). The RVs of all taxa are generally closer to OBVs than PPs, and the degree of similarity depends strongly on the abundance of individual taxa in plant and pollen; taxa dominant in the region show the highest similarity between RVs and OBVs, such as Artemisia , Poaceae, and Humulus . The RVs of all herb taxa except Humulus and Asteraceae SF Cichorioideae are slightly overrepresented, and the RVs of all tree taxa are underrepresented except for Castanea . The comparison of RVs with OBVs collected from different spatial extents shows that the RVs of all herb taxa are more similar to OBVs collected from shorter distances (100 km and 75 km for the entire region and the subregion, respectively), whereas the RVs of all tree taxa are more similar to OBVs collected from longer distances (150 km and 100 km for the entire region and the subregion, respectively). Furthermore, our findings highlight the importance to test different sizes of area for vegetation surveys for evaluation of the RVs given that the appropriate size of vegetation survey may vary between low pollen producers (mainly herbs) and high pollen producers (mainly trees). We consider that the LOO strategy is the best approach in this case study for evaluating the RPP estimates from surface moss polsters. The evaluation confirms the reliability of the obtained RPP estimates for their potential application in quantitative reconstruction of vegetation abundance in temperate China.

Land cover governs the biogeophysical and biogeochemical feedbacks between the land surface and atmosphere. Holocene vegetation–atmosphere interactions are of particular interest, both to understand the climate effects of intensifying human land use and as a possible explanation for the Holocene temperature conundrum, a widely studied mismatch between simulated and reconstructed temperatures. Progress has been limited by a lack of data-constrained, quantified, and consistently produced reconstructions of Holocene land cover change. As a contribution to the Past Global Changes (PAGES) LandCover6k Working Group, we present a new suite of land cover reconstructions with uncertainty for North America, based on a network of 1445 sedimentary pollen records and the REVEALS pollen–vegetation model (PVM) coupled with a Bayesian spatial model. These spatially comprehensive land cover maps are then used to determine the pattern and magnitude of North American land cover changes at continental to regional scales. Early Holocene afforestation in North America was driven by rising temperatures and deglaciation, and this afforestation likely amplified early Holocene warming via the albedo effect. A continental-scale mid-Holocene peak in summergreen trees and shrubs (8.5 to 4 ka) is hypothesized to represent a positive and understudied feedback loop among insolation, temperature, and phenology. A last-millennium decrease in summergreen trees and shrubs with corresponding increases in open land was likely driven by a spatially varying combination of intensifying land use and neoglacial cooling. Land cover trends vary within and across regions, due to individualistic taxon-level responses to environmental change. Major species-level events, such as the mid-Holocene decline in Tsuga canadensis (eastern hemlock), may have altered regional climates. The substantial land cover changes reconstructed here support the importance of biogeophysical and biogeochemical vegetation feedbacks to Holocene climate–carbon dynamics. However, recent model experiments that invoke vegetation feedbacks to explain the Holocene temperature conundrum may have overestimated land cover forcing by replacing Northern Hemisphere grasslands >30° N with forests, an ecosystem state that is not supported by these land cover reconstructions. These Holocene reconstructions for North America, along with similar LandCover6k products now available for other continents, serve the Earth system modeling community by providing better-constrained land cover scenarios and benchmarks for model evaluation, ultimately making it possible to better understand the regional- to global-scale processes driving Holocene land cover, carbon cycle, and climate dynamics.

In this study we estimate relative pollen productivity (RPP) for plant taxa characteristic of human-induced vegetation in ancient cultural landscapes of the low mountain ranges of Shandong province in eastern temperate China. RPP estimates are required to achieve pollen-based reconstructions of Holocene plant cover using modelling approaches based on Prentice’s and Sugita’s theoretical background and models (REVEALS and LOVE). Pollen counts in moss samples and vegetation data from 36 sites were used in the Extended R-Value (ERV) model to estimate the relevant source area of pollen (RSAP) of moss polsters and RPP of major plant taxa. The best results were obtained with the ERV sub-model 3 and Prentice’s taxon-specific method (using a Gaussian Plume dispersal model) to distance weight vegetation data. RSAP was estimated to 145 m using the maximum likelihood method. RPP was obtained for 18 taxa of which two taxa had unreliable RPP (Amaranthaceae/Chenopodiaceae and Vitex negundo). RPPs for Castanea, Cupressaceae, Robinia/Sophora, Aster/Anthemis-type, Cannabis/Humulus, Caryophyllaceae, Brassicaceae and Galium-type are the first ones for China. Trees, except Robinia/Sophora (RPP = 0.78 ± 0.03) have larger RPPs than herbs other than Artemisia (RPP = 24.7 ± 0.36). The RPPs for Quercus, Pinus and Artemisia are comparable with other RPPs obtained in China, the RPPs for Pinus, Quercus, Ulmus, Cyperaceae and Galium-type with the mean RPPs obtained in Europe, and RPP for Cupressaceae with that for Juniperus in Europe. The values for Aster/Anthemis-type, Caryophyllaceae, Asteraceae SF Cichorioideae and Juglans differ from the few RPPs available in China and/or Europe.

We review palaeoenvironmental proxies and combinations of these relevant for understanding hunter-gatherer niche construction activities in pre-agricultural Europe. Our approach consists of two steps: (1) identify the possible range of hunter-gatherer impacts on landscapes based on ethnographic studies; (2) evaluate proxies possibly reflecting these impacts for both the Eemian (Last Interglacial, Middle Palaeolithic) and the Early–Middle Holocene (Mesolithic). We found these paleoenvironmental proxies were not able to unequivocally establish clear-cut differences between specific anthropogenic, climatic and megafaunal impacts for either time period in this area. We discuss case studies for both periods and show that published evidence for Mesolithic manipulation of landscapes is based on the interpretation of comparable data as available for the Last Interglacial. If one applies the ‘Mesolithic’ interpretation schemes to the Neanderthal record, three common niche construction activities can be hypothesised: vegetation burning, plant manipulation and impact on animal species presence and abundance. Our review suggests that as strong a case can be made for a Neanderthal impact on landscapes as for anthropogenic landscape changes during the Mesolithic, even though the Neanderthal evidence comes from only one high-resolution site complex. Further research should include attempts (e.g. by means of modelling studies) to establish whether hunter-gatherer impact on landscapes played out at a local level only versus at a larger scale during both time periods, while we also need to obtain comparative data on the population sizes of Last Interglacial and Holocene hunter-gatherers, as these are usually inferred to have differed significantly.

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.

This paper studies the impact of land use and land cover change (LULCC) on the climate around 2500 years ago (2.5 ka), a period of rapid transitions across the European landscape. One global climate model was used to force two regional climate models (RCMs). The RCMs used two land cover descriptions. The first was from a dynamical vegetation model representing potential land cover, and the second was from a land cover description reconstructed from pollen data by statistical interpolation. The two different land covers enable us to study the impact of land cover on climate conditions. Since the difference in landscape openness between potential and reconstructed land cover is mostly due to LULCC, this can be taken as a measure of early anthropogenic effects on climate. Since the sensitivity to LULCC is dependent on the choice of climate model, we also use two RCMs. The results show that the simulated 2.5 ka climate was warmer than the simulated pre-industrial (PI, 1850 CE) climate. The largest differences are seen in northern Europe, where the 2.5 ka climate is 2–4 ∘C warmer than the PI period. In summer, the difference between the simulated 2.5 ka and PI climates is smaller (0–3 ∘C), with the smallest differences in southern Europe. Differences in seasonal precipitation are mostly within ±10 %. In parts of northern Europe, the 2.5 ka climate is up to 30 % wetter in winter than that of the PI climate. In summer there is a tendency for the 2.5 ka climate to be drier than the PI climate in the Mediterranean region. The results also suggest that LULCC at 2.5 ka impacted the climate in parts of Europe. Simulations including reconstructed LULCC (i.e. those using pollen-derived land cover descriptions) give up to 1 ∘C higher temperature in parts of northern Europe in winter and up to 1.5 ∘C warmer in southern Europe in summer than simulations with potential land cover. Although the results are model dependent, the relatively strong response implies that anthropogenic land cover changes that had occurred during the Neolithic and Bronze Age could have affected the European climate by 2.5 ka.