Effects of future climate change on birch abundance and their pollen load.

Climate change impacts on the structure and function of ecosystems will worsen public health issues like allergic diseases. Birch trees (Betula spp.) are important sources of aeroallergens in Central and Northern Europe. Birches are vulnerable to climate change as these trees are sensitive to increased temperatures and summer droughts. This study aims to examine the effect of climate change on airborne birch pollen concentrations in Central Europe using Bavaria in Southern Germany as a case study. Pollen data from 28 monitoring stations in Bavaria were used in this study, with time series of up 30 years long. An integrative approach was used to model airborne birch pollen concentrations taking into account drivers influencing birch tree abundance and birch pollen production and projections made according to different climate change and socioeconomic scenarios. Birch tree abundance is projected to decrease in parts of Bavaria at different rates, depending on the climate scenario, particularly in current centres of the species distribution. Climate change is expected to result in initial increases in pollen load but, due to the reduction in birch trees, the amount of airborne birch pollen will decrease at lower altitudes. Conversely, higher altitude areas will experience expansions in birch tree distribution and subsequent increases in airborne birch pollen in the future. Even considering restrictions for migration rates, increases in pollen load are likely in Southwestern areas, where positive trends have already been detected during the last three decades. Integrating models for the distribution and abundance of pollen sources and the drivers that control birch pollen production allowed us to model airborne birch pollen concentrations in the future. The magnitude of changes depends on location and climate change scenario.

Numerical ragweed pollen forecasts using different source maps: a comparison for France.

One of the key input parameters for numerical pollen forecasts is the distribution of pollen sources. Generally, three different methodologies exist to assemble such distribution maps: (1) plant inventories, (2) land use data in combination with annual pollen counts, and (3) ecological modeling. We have used six exemplary maps for all of these methodologies to study their applicability and usefulness in numerical pollen forecasts. The ragweed pollen season of 2012 in France has been simulated with the numerical weather prediction model COSMO-ART using each of the distribution maps in turn. The simulated pollen concentrations were statistically compared to measured values to derive a ranking of the maps with respect to their performance. Overall, approach (2) resulted in the best correspondence between observed and simulated pollen concentrations for the year 2012. It is shown that maps resulting from ecological modeling that does not include a sophisticated estimation of the plant density have a very low predictive skill. For inventory maps and the maps based on land use data and pollen counts, the results depend very much on the observational site. The use of pollen counts to calibrate the map enhances the performance of the model considerably.

Modeling the dispersion of Ambrosia artemisiifolia L. pollen with the model system COSMO-ART.

Common ragweed (Ambrosia artemisiifolia L.) is a highly allergenic plant that is spreading throughout Europe. Ragweed pollen can be transported over large distances by the wind. Even low pollen concentrations of less than 10 pollen m(-3) can lead to health problems in sensitive persons. Therefore, forecasting the airborne concentrations of ragweed pollen is becoming more and more important for public health. The question remains whether distant pollen sources need to be considered in reliable forecasts. We used the extended numerical weather prediction system COSMO-ART to simulate the release and transport of ragweed pollen in central Europe. A pollen episode (September 12-16, 2006) in north-eastern Germany was modeled in order to find out where the pollen originated. For this purpose, several different source regions were taken into account and their individual impact on the daily mean pollen concentration and the performance of the forecast were studied with the means of a 2 × 2 contingency table and skill scores. It was found that the majority of the pollen originated in local areas, but up to 20% of the total pollen load came from distant sources in Hungary. It is concluded that long-distance transport should not be neglected when predicting pollen concentrations.