Air sampling was conducted in Szczecin (Poland) throughout April–September 2013. The final data set included 177 daily and 4248 hourly samples. The total of 21 types of spores, which occurred in a number >10 in the season, were taken into account. The following meteorological parameters were analyzed: air temperature, relative humidity, precipitation and wind speed. Effects of individual weather parameters on hourly and daily concentrations of different fungal spore types were examined using Spearman’s rank association test, whereas effects of complex of meteorological factors on hourly and daily compositions of spore were assessed using detrended correspondence analysis (DCA) and redundancy analysis (RDA). Airborne fungal spore distribution patterns in relation to meteorological variables were determined by RDA, after DCA results detected a linear structure of the spore data. The RDA results obtained indicated that all the applied variables accounted for 20 and 22% of the total variance in the hourly and daily spore data, respectively. The results of stepwise forward selection of variables revealed all included hourly and daily meteorological variables were statistically significant. The largest amount of the total variance in the spore composition was explained by the air temperature in both cases (16%). Multivariate ordination did not show large differences between the hourly and daily relationships (with exception of wind speed impact), while the differences between simple hourly and daily correlations were more clear. Correlations between daily values of variables were in most cases higher than between hourly values of variables.

中文翻译：

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所选气象参数与空气中真菌孢子组成之间每小时和每日关系的比较研究

2013 年 4 月至 9 月期间在什切青（波兰）进行了空气采样。最终数据集包括 177 个每日样本和 4248 个每小时样本。总共考虑了 21 种类型的孢子，这些孢子在本季节出现的数量 > 10。分析了以下气象参数：气温、相对湿度、降水和风速。个别天气参数对不同真菌孢子类型每小时和每天浓度的影响使用 Spearman 等级关联检验进行检查，而气象因素复合物对每小时和每天孢子组成的影响使用去趋势对应分析 (DCA) 和冗余分析进行评估。 RDA）。与气象变量相关的空气真菌孢子分布模式由 RDA 确定，DCA结果检测到孢子数据的线性结构后。获得的 RDA 结果表明，所有应用变量分别占每小时和每日孢子数据总方差的 20% 和 22%。逐步向前选择变量的结果显示，所有包括的每小时和每天的气象变量都具有统计学意义。在这两种情况下，孢子组成的最大总变化量是由空气温度解释的 (16%)。多元排序没有显示每小时和每日关系之间的大差异（风速影响除外），而简单的每小时和每日相关性之间的差异更加明显。在大多数情况下，变量每日值之间的相关性高于变量每小时值之间的相关性。