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Gamma Gaussian and logistic distribution models for airborne pollen grains and fungal spore season dynamics

机译:空中花粉粒和真菌孢子季节动态的Gamma高斯和逻辑分布模型

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摘要

The characteristics of a pollen season, such as timing and magnitude, depend on a number of factors such as the biology of the plant and environmental conditions. The main aim of this study was to develop mathematical models that explain dynamics in atmospheric concentrations of pollen and fungal spores recorded in Rzeszów (SE Poland) in 2000–2002. Plant taxa with different characteristics in the timing, duration and curve of their pollen seasons, as well as several fungal taxa were selected for this analysis. Gaussian, gamma and logistic distribution models were examined, and their effectiveness in describing the occurrence of airborne pollen and fungal spores was compared. The Gaussian and differential logistic models were very good at describing pollen seasons with just one peak. These are typically for pollen types with just one dominant species in the flora and when the weather, in particular temperature, is stable during the pollination period. Based on s parameter of the Gaussian function, the dates of the main pollen season can be defined. In spite of the fact that seasonal curves are often characterised by positive skewness, the model based on the gamma distribution proved not to be very effective.
机译:花粉季节的特征(例如时间和大小)取决于许多因素,例如植物的生物学和环境条件。这项研究的主要目的是建立一个数学模型,用以解释2000-2002年热舒夫(波兰东南部)记录的大气中花粉和真菌孢子浓度的动态变化。本研究选择了在花粉季节的时间,持续时间和曲线上具有不同特征的植物分类单元,以及几种真菌分类单元。检查了高斯,伽马和逻辑分布模型,并比较了它们在描述空中花粉和真菌孢子的发生中的有效性。高斯和差分逻辑模型非常擅长描述只有一个高峰的花粉季节。这些通常适用于在植物区系中只有一种优势种的花粉类型,并且在授粉期间天气(尤其是温度)稳定时。根据高斯函数的s参数,可以定义主要花粉季节的日期。尽管季节性曲线通常以正偏度为特征,但事实证明,基于伽玛分布的模型不是非常有效。

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