In this paper, we estimate the Relevant Source Area of Pollen (RSAP) in past hypothetical landscapes of the Middle and Late Holocene in southern Sweden, in order to explore the possible effects of past changes in vegetation composition, openness and structure in terms of patch size and spatial distribution. The RSAP of small basins (bogs or lakes) in the past has to be estimated if quantitative reconstruction of past vegetation at the local spatial scale is to be achieved using Sugita's Landscape Reconstruction Algorithm (LRA). In this study we apply a forward modelling approach to estimate past RSAP using the computer simulation model HUMPOL The landscape designs are based on past landscape maps produced using a combination of palaeobotanical, archaeological and historical data, and the area's geology and soil characteristics. Four time windows characterised by different landscape/land-use were selected, i.e. Early Neolithic, Late Bronze Age, Viking Age, and Middle Ages. We found that RSAP estimates for hypothetical past landscapes in Skane differ by ca. 600 m to 1200 m between the selected time periods, whatever the size of the basin (lake or bog, 25250 m radius). The most probable explanation for the differences in RSAP between time slices is variable patch size and spatial distribution of patches in the landscape. The RSAPs vary between ca. 1200 and 2300 m for small basins (25 m and 70 m radius), and between ca. 2000 and 3000 m for larger basins (250 m radius). These values are within the range of earlier estimates of modern and past RSAPs for southern Scandinavia obtained using simulated or empirical data. These results suggest that, given the type of setting of that region in terms of taxa composition and traditional land-use, the RSAP for small-size lakes (25-250 m radius) will generally be in the range ca. 1200-3000 m. The forward modelling approach is found to be useful to assess the possible effects on RSAP of changes in vegetation/landscape characteristics between different periods of the past. Moreover, comparison of RSAP estimates obtained using both the forward and backward modelling approaches will be important to identify the most credible RSAP estimates for the past. 

Using the HUMPOL simulation computer model we explored the effects of various factors characteristic of mosaic cultural landscapes on the Relevant Source Area of Pollen (RSAP sensu Sugita) of small lakes (50 m radius), and the representation of NAP and human-impact pollen indicators in small takes. The following aspects were tested: 1) effect of variations in the spatial distribution of taxa/patches and species diversity on RSAP, 2) effect of changes in the proportion of landscape openness and size of openings on the RSAP and the pollen signal, and 3) the value of low-abundance anthropogenic indicator species to detect openness in the landscape. Moreover, we examined a methodological aspect of the MOSAIC computer program, i.e. the variability in RSAP due to inherent variations between replicates of random landscape simulation scripts using the program MOSAIC. We found differences in the RSAP estimates between runs using replicates of the same landscape created in the program MOSAIC. Such differences need to be taken into account when interpreting results involving the use of MOSAIC replicates. The simulations suggest that, if the model assumptions are valid, the RSAP is sensitive to vegetation structure in terms of patch size, and taxa/patch diversity and spatial distribution, whatever the properties of the taxa modelled. The longer the distance from each sampling site to get a sufficient cover of all taxa within the landscape, the larger the RSAP. If the spatial distribution of patches is very uneven and/or some taxa/patches are characterised by low frequencies in the randomized landscape, this distance will become longer. Further analysis of the results and new modelling experiments are necessary to provide better means for testing the presented hypothesis on the effect of spatial vegetation/landscape evenness on RSAP. The simulations indicate that, in hypothetical mosaic tree/herb landscapes including common NW European taxa of traditional cultural landscapes, RSAP estimates are relatively robust, i.e. will seldom be smaller than 1000 m and larger than 2500 m in radius in the case of 50 m radius lakes. NAP percentage is not a reliable "measure" of landscape openness. A NAP percentage value may represent a large range of openness percentage cover depending on the size and spatial distribution of the openness patches. Common pollen indicators of human impact and landscape openness will be represented in a pollen assemblage from small lakes when the landscape is relatively open (>= 30%) and a minimum of 300-1000 grains is counted. Findings of pollen indicators of human impact may not be as reliable indicators of land use within the RSAP as has sometimes been assumed, especially when human activity is small scale. Moreover, it is important to realize that a small number of grains may indicate relatively large overall openness cover in the landscape, especially if the open areas consist of few large clearings rather than many small clearings. 

The need for quantification of land cover from pollen data has led to the development of a Landscape Reconstruction Algorithm (LRA). The LRA includes several models of which the REVEALS model estimates regional vegetation abundance using pollen assemblages from large sites (lakes or bogs). In this paper we explore the effects of selection and number of pollen samples, and choice of pollen productivity estimates on the REVEALS results. The effect of the size of vegetation surveys is also tested. The results suggest that the differences between two sizes of vegetation surveys have little effect on the model validation. The "characteristic radius" of regional vegetation in southern Sweden was estimated as 200 km. However, the vegetation composition in a 100 x 100 km(2) square matches well with that estimated by REVEALS. Whether 25, 20 (outliers excluded) or 4 pollen samples are used does not change the REVEALS reconstructions much although the error estimates are larger when outliers are included, and very large when only four samples are used. Therefore validation of the REVEALS model and REVEALS reconstructions of past vegetation can be performed using a limited number of pollen samples, although with caution. The use of many pollen samples from multiple sites is always better whenever possible. REVEALS reconstructions are closer to the actual vegetation when the Danish Pollen Productivity Estimates (PPEs) are used instead of the Swedish PPEs for Cereals, Rumex acetosa/acetosella, Plantago lanceolata and Calluna, indicating that the Danish PPEs are more reliable than the Swedish ones for those taxa. It is recommended to test more than one set of PPEs in validation and applications of the REVEALS model for a better evaluation of the results.

The REVEALS model was developed to reconstruct quantitatively regional vegetation abundance (in a 10⁴–10⁵ km² area) from pollen assemblages in large lakes (≥100–500 ha). This model corrects for biases in pollen percentages caused by inter-taxonomic differences in pollen productivity and dispersal. This paper presents the first case study to validate REVEALS, using empirical data from southern Sweden. Percentage cover of modern regional vegetation in Skåne and Småland, two contrasting vegetation regions, was predicted with REVEALS for 26 key taxa, using pollen assemblages from surface sediments in 10 large lakes, and compared to the actual vegetation within 10⁴ km² compiled from satellite data, forestry inventories, crop statistics, aerial photographs, and vegetation inventories. REVEALS works well in predicting the percentage cover of large vegetation units such as total trees (wooded land), total herbs (open land), total conifers and total broad-leaved trees, and it provides reasonable estimates for individual taxa, including Pinus, Picea, Betula, Corylus, Alnus, Tilia, Salix spp., Juniperus, Poaceae, Cyperaceae, Cerealia and Secale. The results show great potential for REVEALS applications, including (1) quantitative reconstructions of past regional land cover important for palaeoclimatology and nature conservation, and (2) local-scale reconstruction of vegetation (<1 km² up to ∼ 5 km² area) relevant for palaeoecology and archaeology.