Department of Plant Biology, Faculty of Sciences, University of Malaga, Campus of Teatinos, Malaga, Spain.
Int J Biometeorol. 2012 Nov;56(6):983-91. doi: 10.1007/s00484-011-0509-3. Epub 2011 Nov 17.
Alternaria and Cladosporium are two fungal taxa whose spores (conidia) are included frequently in aerobiological studies of outdoor environments. Both spore types are present in the atmosphere of Malaga (Spain) throughout almost the entire year, although they reach their highest concentrations during spring and autumn. To establish predicting variables for daily and weekly fluctuations, Spearman's correlations and stepwise multiple regressions between spore concentrations (measured using a volumetric 7-day recorder) and meteorological variables were made with results obtained for both spore types in 1996 and 1997. Correlations and regressions were also made between the different taxa and their concentrations in different years. Significant and positive correlation coefficients were always obtained between spore concentrations of both taxa, followed by temperature, their concentrations in different years, sunshine hours and relative humidity (this last in a negative sense). For the two spore types we obtained higher correlation and regression coefficients using weekly data. We showed different regression models using weekly values. From the results and a practical point of view, it was concluded that weekly values of the atmospheric concentration of Alternaria spores can be predicted from the maximum temperature expected and its concentrations in the years sampled. As regards the atmospheric concentration of Cladoposrium spores, the weekly values can be predicted based on the concentration of Alternaria spores, thus saving the time and effort that would otherwise be employed in counting them by optical microscopy.
交链孢霉和枝孢霉是两种真菌分类群,其孢子(分生孢子)经常包含在户外环境的空气生物学研究中。这两种孢子类型都存在于马拉加(西班牙)的大气中,几乎全年都有,但在春季和秋季达到最高浓度。为了建立预测变量,以了解每日和每周的波动情况,对 1996 年和 1997 年两种孢子类型的孢子浓度(使用体积 7 天记录器测量)与气象变量之间进行了 Spearman 相关性和逐步多元回归分析。还对不同分类群及其在不同年份的浓度之间进行了相关性和回归分析。两种孢子的浓度之间总是得到显著的正相关系数,其次是温度、不同年份的浓度、日照时数和相对湿度(后者呈负相关)。对于这两种孢子类型,使用每周数据可获得更高的相关性和回归系数。我们使用每周值得到了不同的回归模型。从结果和实际角度来看,我们得出结论,从预期的最高温度及其在采样年份的浓度可以预测大气中交链孢霉孢子的浓度。至于枝孢霉孢子的大气浓度,可以根据交链孢霉孢子的浓度来预测,从而节省了用光学显微镜计数的时间和精力。