Pollen-based paleoclimate reconstructions of Beloslav Lake (Northeastern Bulgaria) during the last 6000 years using modern analog technique (MAT)

The aim of the present study is to reconstruct the palaeoclimate variables in the Beloslav Lake Region (Northeastern Bulgaria) during the last 6000 years, based on the pollen analysis from lacustrine core Bel-1 and using modern analog technique (MAT). Pollen data was used for reconstructions of four parameters: average annual temperature, average temperature of the warm and cold half-year and average annual precipitation.

Analysis of allergenic pollen data, focusing on a pollen load threshold statement

Airborne allergenic pollen affects a significant part of the population and the information on pollen load is a valuable tool for public health prevention. The messages should be provided in a form easily understandable for the population. The study provides new insight for the categorisation of pollen load by defining thresholds solely from aerobiological data. Using the long-term airborne pollen data of Corylus, Alnus, Betula, Poaceae, and Artemisia have been evaluated the regionality of pollen concentrations in Lithuania. SPIn and peak values of the main pollen season highlighted as regionality indicators. The largest differences between stations were found in the cases of Corylus and Artemisia.The principle enabling a group of pollen concentrations into levels has been analysed based on retrospective aerobiological data of five pollen types. Thresholds were determined by employing the lowest peak value of the pollen season and applying the 25% principle for selected pollen types. The results were verified by performing associations of defined thresholds with retrospective morbidity data of allergic rhinitis and allergic asthma in Lithuania. Determined pollen thresholds can be used in epidemiological studies requiring associations with pollen concentration. Thresholds could also complement air quality information by integrating pollen load data into public messages or contribute to the development of mHealth systems.

Pollen productivity estimates strongly depend on assumed pollen dispersal II: Extending the ERV model

Pollen productivity estimates (PPEs) are a key parameter for quantitative land-cover reconstructions from pollen data. PPEs are commonly estimated using modern pollen-vegetation data sets and the extended R-value (ERV) model. Prominent discrepancies in the existing studies question the reliability of the approach. We here propose an implementation of the ERV model in the R environment for statistical computing, which allows for simplified application and testing. Using simulated pollen-vegetation data sets, we explore sensitivity of ERV application to (1) number of sites, (2) vegetation structure, (3) basin size, (4) noise in the data, and (5) dispersal model selection. The simulations show that noise in the (pollen) data and dispersal model selection are critical factors in ERV application. Pollen count errors imply prominent PPE errors mainly for taxa with low counts, usually low pollen producers. Applied with an unsuited dispersal model, ERV tends to produce wrong PPEs for additional taxa. In a comparison of the still widely applied Prentice model and a Lagrangian stochastic model (LSM), errors are highest for taxa with high and low fall speed of pollen. The errors reflect the too high influence of fall speed in the Prentice model. ERV studies often use local scale pollen data from for example, moss polsters. Describing pollen dispersal on his local scale is particularly complex due to a range of disturbing factors, including differential release height. Considering the importance of the dispersal model in the approach, and the very large uncertainties in dispersal on short distance, we advise to carry out ERV studies with pollen data from open areas or basins that lack local pollen deposition of the taxa of interest.

Turfs and timbers

Viking Age ring fortresses were some of the largest construction projects in Danish prehistory. In this article we reconstruct the amount of turf and timber used in the construction of the Borgring ring fortress and estimate the resource area needed to supply the building materials. Using REVEALS pollen data modelling, we quantify the regional oak land cover and estimate the resource area. The results show that even though Borgring was built in an open cultural landscape, sufficient supply of oak for the construction would have been accessible within a few kilometres from the fortress.