Soil properties, drought, and the interaction between the two are significant, if unclear, driver of radial growth variations. We observed that, soil properties exert a stronger effect on pedunculate oak (Quercus robur L.; QURO) radial growth sensitivity to drought (interpreted via Standardized Precipitation Evapotranspiration Index; SPEI), than on radial increment and its variations. Soils that are strongly affected by soil water (typical and haplic gleysol) provide the most suitable substrates for QURO radial growth during drought events because they provide more continuous water sources. In contrast, QURO growing on chernozem (with sand) and solonetz (highly saline soils) are more drought-sensitive and have smaller radial increments. The influence of soil type is clearly evident in the pattern of QURO decline that has occurred across Europe (2014) and Serbia (2011–2012): QURO growing on gelysols (characterized by high soil water content) were not strongly affected, whereas marked mortality occurred in QURO forests growing on chernozem and solonetz. Based on the findings yielded by the Generalized Additive Mixed Model (GAMM) and the Linear Mixed Effects Model (LMM), the above-ground (precipitation and temperature) and below-ground (river water level and soil moisture) drought sources affect radial growth equally and its sensitivity to drought. Overall, GAMM better fitted with analyzed radial growth properties, than LMM. Likewise, based on the GAMM and LMM outputs, stronger associations between QURO radial growth sensitivity to drought and nine climate parameters were obtained compared with raw as well as detrended radial growth series.

土壤特性，干旱以及二者之间的相互作用（如果不清楚的话）是径向生长变化的重要驱动力。我们观察到，土壤特性对带花梗的橡树（栎木L .; QURO）对干旱的径向敏感性（通过标准降水蒸散指数； SPEI解释），而不是对径向增量及其变化的敏感性。受土壤水（典型的和触觉的二甘醇）强烈影响的土壤为干旱期间QURO径向生长提供了最合适的基质，因为它们提供了更多的连续水源。相比之下，在黑钙土（含沙）和solonetz（高盐渍土）上生长的QURO对干旱更敏感，径向增量较小。在欧洲（2014年）和塞尔维亚（2011-2012年）发生的QURO下降模式中，显然可以明显看出土壤类型的影响：在凝胶状凝胶上生长的QURO（以高土壤含水量为特征）并未受到严重影响，而死亡率却显着发生在生长在黑钙锌和索诺兹上的QURO森林中。根据广义加性混合模型（GAMM）和线性混合效应模型（LMM）得出的结果，地上（降水和温度）和地下（河流水位和土壤湿度）干旱源影响径向生长同样，其对干旱的敏感性。总体而言，与LMM相比，GAMM更适合分析径向生长特性。同样，基于GAMM和LMM的输出，与原始和趋势下降的径向生长序列相比，QURO径向生长对干旱的敏感性与9个气候参数之间的关联更强。地上（降水和温度）和地下（河流水位和土壤湿度）干旱源均会影响径向生长及其对干旱的敏感性。总体而言，与LMM相比，GAMM更适合分析径向生长特性。同样，基于GAMM和LMM的输出，与原始和趋势下降的径向生长序列相比，QURO径向生长对干旱的敏感性与9个气候参数之间的关联更强。地上（降水和温度）和地下（河流水位和土壤湿度）干旱源均会影响径向生长及其对干旱的敏感性。总体而言，与LMM相比，GAMM更适合分析径向生长特性。同样，基于GAMM和LMM的输出，与原始和趋势下降的径向生长序列相比，QURO径向生长对干旱的敏感性与9个气候参数之间的关联更强。