Department of Plant Taxonomy and Phytogeography, University of Szczecin, Wąska 13, 71-415, Szczecin, Poland.
Int J Biometeorol. 2011 Mar;55(2):235-41. doi: 10.1007/s00484-010-0329-x. Epub 2010 May 29.
Ganoderma sp. is an airborne fungal spore type known to trigger respiratory allergy symptoms in sensitive patients. Aiming to reduce the risk for allergic individuals, we analysed fungal spore circulation in Szczecin, Poland, and its dependence on meteorological conditions. Statistical models for the airborne spore concentrations of Ganoderma sp.-one of the most abundant fungal taxa in the area-were developed. Aerobiological sampling was conducted over 2004-2008 using a volumetric Lanzoni trap. Simultaneously, the following meteorological parameters were recorded: daily level of precipitation, maximum and average wind speed, relative humidity and maximum, minimum, average and dew point temperatures. These data were used as the explaining variables. Due to the non-linearity and non-normality of the data set, the applied modelling techniques were artificial neural networks (ANN) and mutlivariate regression trees (MRT). The obtained classification and MRT models predicted threshold conditions above which Ganoderma sp. appeared in the air. It turned out that dew point temperature was the main factor influencing the presence or absence of Ganoderma sp. spores. Further analysis of spore seasons revealed that the airborne fungal spore concentration depended only slightly on meteorological factors.
灵芝属真菌孢子是一种已知会引发敏感患者呼吸道过敏症状的空气传播真菌孢子类型。为了降低过敏个体的风险，我们分析了波兰什切青的真菌孢子循环及其对气象条件的依赖关系。针对该地区最丰富的真菌类群之一灵芝属真菌孢子的空气传播孢子浓度建立了统计模型。采用容积式 Lanzoni 捕集器在 2004-2008 年期间进行了空气生物学采样。同时，记录了以下气象参数：日降水量、最大和平均风速、相对湿度以及最高、最低、平均和露点温度。这些数据被用作解释变量。由于数据集的非线性和非正态性，应用的建模技术是人工神经网络 (ANN) 和多元回归树 (MRT)。获得的分类和 MRT 模型预测了灵芝属真菌孢子出现在空气中的阈值条件。结果表明，露点温度是影响灵芝属真菌孢子存在与否的主要因素。对孢子季节的进一步分析表明，空气传播真菌孢子浓度仅略微依赖于气象因素。
