Die Mikroflora der untermiozänen Fundstelle Altmittweida, Deutschland

Diese Arbeit berichtet über die Mikroflora der Pflanzenfundstelle Altmittweida (Sachsen, Deutschland). Altmittweida wird stratigraphisch in das Untermiozän gestellt. Bisherige Studien haben sich mit den Makrofossilien aus dieser und umliegenden Fundstellen beschäftigt. Darauf basierend wurden Wasser- und Sumpfpflanzengesellschaften, Bruch- und Auenwälder und mesophytische Wälder als Flora des Oberoligozäns und Untermiozäns rekonstruiert. Im Vergleich zu den bisher nachgewiesenen Makrofossilien zeigt die Mikrofloren-vergesellschaftung eine wesentlich höhere Diversität. Die Ergebnisse der Untersuchung der Mikroflora von Altmittweidaführte zu einer umfangreichen Florenliste bestehend aus: 57 Angiospermen und drei Gymnospermen Pollentaxa. Zusätzlich wurden fünf verschiedene Sporentypen verzeichnet, vier Farntaxa und eine Moosgattung. Im Makrofossilrekord umliegender Fundstellen treten einige Pflanzen auf, die zuvor aus der Fundstelle Altmittweida unbekannt waren, sich nun aber im Mikrofossilbefund nachweisen lassen. Zusätzlich treten einige Taxa auf, die nur im Mikrofossilrekord nachweisbar sind. Interessant ist der Nachweis einer Cucurbitaceae aus dem Untermiozän Europas. Frühe Nachweise der Gattung Fagus sind nun auch im Mikrofossilrekord Altmittweidas bestätigt. Es bestätigt sich erneut, dass durch eine zusätzliche, detaillierte Analyse der Mikroflora eines Fundortes, die Kenntnis der damals vorherrschende Vegetation erweitert und vervollständigt werden kann.This thesis is about the microflora of the fossil plant bearing site of Altmittweida (Saxony, Germany). Altmittweida was stratigraphically dated and is of Lower Miocene age. Hitherto studies focused on the macrofossil record of this and surrounding sites. Up to now, the reconstruction of the flora of the Upper Oligocene and the Lower Miocene consists of lacustrine and marsh plant assemblages, riparian and fen woods as well as mesophytic forests. The microfossil assemblage shows much greater diversity in comparison to the macrofossil record. The results of this study lead to a comprehensive checklist of the flora, which is composed of: 57 angiosperm and and three gymnosperm pollen taxa. Additionally, five spore types were found, four belonging to ferns and one moss determined on genus-level. The macrofossil record of surrounding sites includes taxa, that were unknown from Altmittweida. Now, they could be detected in the microfossil assemblage. Further, there is evidence for taxa hitherto unknown from the macrofossil record. Surprisingly, a finding indicates the presence of Cucurbitaceae in the Lower Miocene of Europe. Early proves for the genus Fagus are now also known from the microflora of Altmittweida. The results confirm, that the analysis of the microfossil record of a site enriches and adds to the knowledge of the vegetation at that time

Journal of Medical Internet Research / Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service

Background: Pollen forecasts are highly valuable for allergen avoidance and thus raising the quality of life of persons concerned by pollen allergies. They are considered as valuable free services for the public. Careful scientific evaluation of pollen forecasts in terms of accurateness and reliability has not been available till date. Objective: The aim of this study was to analyze 9 mobile apps, which deliver pollen information and pollen forecasts, with a focus on their accurateness regarding the prediction of the pollen load in the grass pollen season 2016 to assess their usefulness for pollen allergy sufferers. Methods: The following number of apps was evaluated for each location: 3 apps for Vienna (Austria), 4 apps for Berlin (Germany), and 1 app each for Basel (Switzerland) and London (United Kingdom). All mobile apps were freely available. Todays grass pollen forecast was compared throughout the defined grass pollen season at each respective location with measured grass pollen concentrations. Hit rates were calculated for the exact performance and for a tolerance in a range of 2 and 4 pollen per cubic meter. Results: In general, for most apps, hit rates score around 50% (6 apps). It was found that 1 app showed better results, whereas 3 apps performed less well. Hit rates increased when calculated with tolerances for most apps. In contrast, the forecast for the “readiness to flower” for grasses was performed at a sufficiently accurate level, although only two apps provided such a forecast. The last of those forecasts coincided with the first moderate grass pollen load on the predicted day or 3 days after and performed even from about a month before well within the range of 3 days. Advertisement was present in 3 of the 9 analyzed apps, whereas an imprint mentioning institutions with experience in pollen forecasting was present in only three other apps. Conclusions: The quality of pollen forecasts is in need of improvement, and quality control for pollen forecasts is recommended to avoid potential harm to pollen allergy sufferers due to inadequate forecasts. The inclusion of information on reliability of provided forecasts and a similar handling regarding probabilistic weather forecasts should be considered.(VLID)486420

Defining Pollen Seasons : Background and Recommendations

Purpose of Review The definition of a pollen season determines the start and the end of the time period with a certain amount of pollen in the ambient air. Different pollen season definitions were used for a long time including the use of different terms for data and methods used to define a pollen season. Recently suggested pollen season definitions for clinical trials were tested and applied for the first time to more aeroallergens. Recent Findings This is a review on pollen season definitions and the latest recommendations. Recently, proposed terminology in aerobiology is promoted here in order to support reproducibility and repeatability in research. Two pollen season definitions, one based on percentages and one based on pollen concentrations, were tested. Summary Percentage definitions can be recommended for standard aerobiological routines and for retrospective applications, whereas pollen concentrations definitions can be recommended for prospective applications such as clinical trials.(VLID)361609

The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna

Abstract Background Online pollen diaries and mobile applications nowadays allow easy and fast documentation of pollen allergy symptoms. Such crowd-sourced symptom data provides insights into the development and the onset of a pollen allergy. Hitherto studies of the symptom load index (SLI) showed a discrepancy between the SLI and the total pollen amount of a season, but did not analyze the daily data. Methods The Patient’s Hayfever Diary (PHD) was used as data pool for symptom data. Symptom data of Vienna (Austria) was chosen as a large and local sample size within the study period of 2013 until 2017. The city was divided into three different areas based on equal population densities and different environmental factors. Correlation factors, regression lines, locally weighted smoothing (LOESS) curves and line plots were calculated to examine the data. Results Daily SLI and pollen concentration data correlates well and the progress of the SLI within a pollen season is mirrored by the pollen concentrations. The LOESS curves do not deviate much from the regression line and support the linearity of the symptom-pollen correlation on a daily basis. Seasonal SLI data does not follow the same pattern as the respective seasonal pollen indices. Results did not vary in the three areas within Vienna or when compared with the Eastern region of Austria showing no significant spatial variation of the SLI. Discussion Results indicate a linear relationship of the SLI and pollen concentrations/seasonal polllen index (SPIn) on a daily basis for both in general and throughout the season, but not on a seasonal basis. These findings clarify the frequent misinterpretation of the SLI as index that is tightly connected to pollen concentrations, but reflects as well the seasonal variation of the burden of pollen allergy sufferers. Conclusion More than just the seasonal pollen index has to be considered when the SLI of a selected pollen season has to be explained. Cross-reactivity to other pollen types, allergen content and air pollution could play a considerable role. The similar behavior of the SLI in Vienna and a whole region indicate the feasibility of a possible symptom forecast in future and justifies the use of a single pollen monitoring station within a city of the size of Vienna