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The two major aims of this study are (1) To test the performance of the Landscape Reconstruction Algorithm (LRA) to quantify past landscape changes using historical maps and related written sources, and (2) to use the LRA and map reconstructions for a better understanding of the origin of landscape diversity and the recent loss of species diversity. Southern Sweden, hemiboreal vegetation zone. The LRA was applied on pollen records from three small bogs for four time windows between AD 1700 and 2010. The LRA estimates of % cover for woodland/forest, grassland, wetland, and cultivated land were compared with those extracted from historical maps within 3-km radius around each bog. Map-extracted land-use categories and pollen-based LRA estimates (in % cover) of the same land-use categories show a reasonable agreement in several cases; when they do not agree, the assumptions used in the data (maps)-model (LRA) comparison are a better explanation of the discrepancies between the two than possible biases of the LRA modeling approach. Both the LRA reconstructions and the historical maps reveal between-site differences in landscape characteristics through time, but they demonstrate comparable, profound transformations of the regional and local landscapes over time and space due to the agrarian reforms in southern Sweden during the 18th and 19th centuries. The LRA was found to be the most reasonable approach so far to reconstruct quantitatively past landscape changes from fossil pollen data. The existing landscape diversity in the region at the beginning of the 18th century had its origin in the long-term regional and local vegetation and land-use history over millennia. Agrarian reforms since the 18th century resulted in a dramatic loss of landscape diversity and evenness in both time and space over the last two centuries leading to a similarly dramatic loss of species (e.g., beetles).

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).

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) 2

We present a quantitative reconstruction of local forest history at two sites, Stavsakra (hemiboreal zone) and Storasjo (southern boreal zone), in southern Sweden (province of Smaland) to evaluate possible causes of contrasting Holocene fire histories in mid- and late Holocene. The Landscape Reconstruction Algorithm (LRA) is applied to evaluate between-site differences in the relative abundance of deciduous trees and Pinus (pine) and landscape/woodland openness during the Holocene. The LRA estimates of local vegetation abundance are compared with other proxies of local vegetation, that is, plant and beetle remains. The LRA results suggest that Pinus was a major tree taxon in the woodlands of Storasjo during mid- and late Holocene, while Tilia (linden) and Betula (birch) were dominant at Stavsakra. The contrasting fire histories are shown to be strongly related to between-site differences in tree composition during mid-Holocene, 4000-2000 bc in particular. The archaeological/historical and beetle data indicate contrasting land uses from c. 1000 bc (late Bronze Age/early Iron Age), grazing in open Calluna heaths at Stavsakra and woodland grazing at Storasjo. Between-site differences in fire history during late Holocene were likely due to different land-use practices. Between-site differences in tree composition in mid-Holocene are best explained by local climatic and geological/geomorphological differences between the hemiboreal and southern boreal zones of Smaland, which might also be the primary cause of between-site differences in land-use histories during late Holocene. Maintenance of biodiversity at the landscape scale in the study area requires that existing old pine woodlands and Calluna heath are managed with fire and cattle grazing. Further climate warming might lead to higher probabilities of climate-induces fire, in particular in pine-dominated woodlands.

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 ALC, NordForsk LANDCLIM, VR LANDCLIM, MERGE

VR LANDCLIM, NordForsk LANDCLIM, MERGE

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Quantitative reconstruction of the area cleared of forest in the past is essential to assess the possible indirect anthropogenic impacts on the past environment of Europe, including past climate. We apply asimulation model of pollen dispersal and deposition (1) to re-examine the relationship between pollenand landscape openness, often uncritically inferred from non-arboreal pollen (NAP) percentages done, and (2) to predict the relevant source area of pollen, the smallest spatial scale of vegetation that can be reconstructed from pollen records. The simulations use landscapes simplified from the modem open agricultural and semi-open forested regions in southern Sweden where traditional cultural landscapes still remain. The model is appropriate, because the simulated pollen assemblages resemble the pollenassemblages observed in each of the two landscape types, and because the simulated relationships between NAP percentages and percentage cover of open land within 1000 m agree with the empirical relationships. The simulated relevant source area of pollen is the area within 800-1000 m from both small hollows and 3-ha ponds. NAP percentages give only a rough first approximation of the percentage cover of open land. More comprehensive methods will be required to obtain quantitative estimates of open land from fossil pollen.