A Method For Producing Airborne Pollen Source Inventories: An Example of Ambrosia (Ragweed) on the Pannonian Plain

We present here a simple methodology for calculating species inventories for allergenic pollen that can be used by atmospheric transport models. Ragweed (Ambrosia) species distribution or infection level on the Pannonian Plain has been used as an example of how the methodology can be used. The Pannonian Plain is one of the three main regions in Europe recognized as being polluted by Ambrosia. The methodology relies on spatial variations in annual Ambrosia pollen counts, knowledge on ragweed ecology and detailed land cover information. The results of this analysis showed that some of the highest mean annual ragweed pollen concentrations were witnessed around Kecskemét in central Hungary and Novi Sad in northern Serbia. These areas are also the areas with the highest density of Ambrosia habitats. The resulting inventory can be entered into atmospheric transport models in combination with other components such as a phenological model and a model for daily pollen release, in order to simulate the movement of ragweed pollen from the Pannonian Plain. The methodology is likely to be generally applicable for creating inventories of species distribution of allergenic plants. The main requirement is availability of: detailed land cover information; pollen indexes; a list of the most important habitats; and a region of interest that is mainly influenced by local sources.

Risk Perception Influences Athletic Pacing Strategy.

PURPOSE: To examine risk-taking and risk-perception associations with perceived exertion, pacing and performance in athletes. METHODS: Two experiments were conducted in which risk-perception was assessed using the domain-specific risk-taking (DOSPERT) scale in 20 novice cyclists (Experiment 1) and 32 experienced ultra-marathon runners (Experiment 2). In Experiment 1, participants predicted their pace and then performed a 5 km maximum effort cycling time-trial on a calibrated KingCycle mounted bicycle. Split-times and perceived exertion were recorded every kilometer. In experiment 2, each participant predicted their split times before running a 100 km ultra-marathon. Split-times and perceived exertion were recorded at 7 check-points. In both experiments, higher and lower risk-perception groups were created using median split of DOSPERT scores. RESULTS: In experiment 1, pace during the first km was faster among lower compared to higher risk-perceivers, t(18)=2.0 P=0.03, and faster among higher compared lower risk-takers, t(18)=2.2 P=0.02. Actual pace was slower than predicted pace during the first km in both the higher risk perceivers, t(9)=-4.2 P=0.001, and lower risk-perceivers, t(9)=-1.8 P=0.049. In experiment 2, pace during the first 36 km was faster among lower compared to higher risk-perceivers, t(16)=2.0 P=0.03. Irrespective of risk-perception group, actual pace was slower than predicted pace during the first 18 km, t(16)=8.9 P<0.001, and from 18 to 36 km, t(16)=4.0 P<0.001. In both experiments there was no difference in performance between higher and lower risk-perception groups. CONCLUSIONS: Initial pace is associated with an individual's perception of risk, with low perceptions of risk being associated with a faster starting pace. Large differences between predicted and actual pace suggests the performance template lacks accuracy, perhaps indicating greater reliance on momentary pacing decisions rather than pre-planned strategy.