Relative pollen productivity estimates of major anemophilous taxa and relevant source area of pollen in a cultural landscape of the hemi-boreal forest zone (Estonia)

Estimates of relevant source area of pollen (RSAP) and relative pollen productivity (PPE) are critical parameters for quantitative reconstructions of past vegetation and land cover. This study provides estimates for PPE relative to Poaceae for ten taxa, characterizing the cultural landscape of south Estonia and the RSAP for 40 lakes with an average radius of approximately 100 m (22-274 m, average 101 m) in the region. We evaluate the effects on those estimates of various combinations of factors, such as the analytical methods (i.e. three Extended R value (ERV) sub-models), the distance-weighting methods used to determine plant abundance, and alternative classification schemes of vegetation and land cover data around study sites. Different combinations of ERV sub-models and distance-weighting methods lead to estimates of RSAP varying between 1500 m and 2000 m. The differences in the estimated RSAP are strongly related to the patch size of the vegetation data. According to ERV sub-model 1, which shows the highest log-likelihood among the three sub-models, most of the taxa have PPE that are higher (Picea, Pin us, Quercus), slightly higher (Salix, Artemisia, Filipendula) or similar (Betula, Cerealia, Cypreraceae) to that of Poaceae. The three ERV sub-models produce only slightly different PPE. However, the selection of distance-weighting method for vegetation has considerable influence on the PPE values. The inverse distance-weighting methods, which do not consider inter-taxonomic differences in pollen dispersal, tend to underestimate PPE for taxa with heavy pollen grains and overestimate PPE for taxa with light pollen grains, compared to the results obtained using other methods that consider taxon specific pollen-dispersal. General land-cover data, based on the classification scheme similar to the CORINE (COoRdination of Information on the Environment) database, could be used for estimating the RSAP and PPE, although some potential problems remain when the classification is too simplified and consolidated. (C) 2011 Elsevier B.V. All rights reserved

The Verijarv area, South Estonia over the last millennium: A high resolution quantitative land-cover reconstruction based on pollen and historical data

Integration of palynological proxies with annual lamina counting, C-14, Pb-210, Cs-137 and Am-241 radiometric dating, historical documents and old cadastral maps enabled reconstruction of changes in the cultural landscape resulting from extensive forest clearance, arable farming and slash-and-burn practices in South Estonia over the last millennium. Changes in land-cover were quantitatively reconstructed using Landscape Reconstruction Algorithm (LRA) models. These reconstructions are in accordance with historical data from the last century, while reconstructions for the late 19th century time-slice exhibit a considerably more open landscape with a higher portion of cultivated land than that recorded on maps, and possible reasons for this discrepancy are discussed. Taxa represented in the pollen spectrum with values 70%) landscape resulting from extensive agrarian activities including slash-and-burn agriculture; AD 1870 to 1950, cultural landscape with variable openness (70-80%) and AD 1950 to 2000, modern overgrowing semi-open (<70%) landscape. (C) 2014 Elsevier B.V. All rights reserved

Long-term drivers of forest composition in a boreonemoral region: the relative importance of climate and human impact

Aim To assess statistically the relative importance of climate and human impact on forest composition in the late Holocene. Location Estonia, boreonemoral Europe. Methods Data on forest composition (10 most abundant tree and shrub taxa) for the late Holocene (5100-50 calibrated years before 1950) were derived from 18 pollen records and then transformed into land-cover estimates using the REVEALS vegetation reconstruction model. Human impact was quantified with palaeoecological estimates of openness, frequencies of hemerophilous pollen types (taxa growing in habitats influenced by human activities) and microscopic charcoal particles. Climate data generated with the ECBilt-CLIO-VECODE climate model provided summer and winter temperature data. The modelled data were supported by sedimentary stable oxygen isotope (O-18) records. Redundancy analysis (RDA), variation partitioning and linear mixed effects (LME) models were applied for statistical analyses. Results Both climate and human impact were statistically significant predictors of forest compositional change during the late Holocene. While climate exerted a dominant influence on forest composition in the beginning of the study period, human impact was the strongest driver of forest composition change in the middle of the study period, c.4000-2000years ago, when permanent agriculture became established and expanded. The late Holocene cooling negatively affected populations of nemoral deciduous taxa (Tilia, Corylus, Ulmus, Quercus, Alnus and Fraxinus), allowing boreal taxa (Betula, Salix, Picea and Pinus) to succeed. Whereas human impact has favoured populations of early-successional taxa that colonize abandoned agricultural fields (Betula, Salix, Alnus) or that can grow on less fertile soils (Pinus), it has limited taxa such as Picea that tend to grow on more mesic and fertile soils. Main conclusions Combining palaeoecological and palaeoclimatological data from multiple sources facilitates quantitative characterization of factors driving forest composition dynamics on millennial time-scales. Our results suggest that in addition to the climatic influence on forest composition, the relative abundance of individual forest taxa has been significantly influenced by human impact over the last four millennia