Frequencies of Multivariate Air Masses Drive Tree Growth
Frequencies of Multivariate Air Masses Drive Tree Growth
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DOI：
10.1029/2022jg007064
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发表时间：
2023-03
期刊：
影响因子：
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通讯作者：
Cameron C. Lee;M. Dannenberg
中科院分区：
文献类型：
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作者：
Cameron C. Lee;M. Dannenberg
中纬度地面气象条件嵌入在天气尺度系统中并受其影响，包括空气质量（AM）的移动和持续性。在过去的几十年中，AM频率（每天发生的次数）的变化可能会对生态系统产生巨大的影响：每个生物体都暴露在整个大气变量的协同效应中，这是一个固有的多变量环境，最好使用AM捕获。利用全球规模的AM分类系统和大型树轮年表网络，我们研究了AM频率的变化如何影响900多个地点的树木生长。我们发现AM频率与树木生长密切相关，特别是在从生长前一年的7月到生长年的6月的12个月期间。最具影响力的AM是干热AM和湿冷AM，对于某些树种，它们与树木生长的平均相关性分别为ρ = −0.4和ρ = +0.4，在某些季节，某些地点的相关性超过ρ = ±0.8。与仅基于温度和降水的经验模型相比，仅使用AM频率的建模在近60%的站点和超过80%的良好采样（n ≥ 10）物种中被证明具有上级优势。这些结果应提供一个基础，使用AM，以提高预测树木生长，树木压力和野火的潜力。使用树木年轮数据对几个世纪前的AM频率进行长期重建也是可行的，这将有助于利用这些空气质量对气候变化的多变量观点进行背景化和时间扩展。
Midlatitude surface meteorological conditions are embedded within—and affected by—synoptic‐scale systems, including the movement and persistence of air masses (AMs). Changes in AM frequencies (number of daily occurrences) over the past several decades could have large effects on ecosystems: each organism is exposed to the synergistic effects of the entire suite of atmospheric variables acting upon it—an inherently multivariate environment—which is best captured using AMs. Utilizing a global‐scale AM classification system and a large network of tree‐ring chronologies, we investigate how variation in AM frequency impacts tree growth at over 900 locations. We find that AM frequencies are well‐correlated with tree growth, especially in the 12‐month period from July in the year prior to growth through June in the year of growth. The most impactful AMs are Dry‐Warm and Humid‐Cool AMs, which exhibit average correlations of ρ = −0.4 and ρ = +0.4 with tree growth, respectively, for certain tree species, with correlations at some sites exceeding ρ = ±0.8 in some seasons. Compared to empirical models based solely on temperature and precipitation, modeling using only AM frequencies proved superior at nearly 60% of the sites and for over 80% of the well‐sampled (n ≥ 10) species. These results should provide a foundation for using AMs to improve forecasts of tree growth, tree stress and wildfire potential. Long‐term reconstructions of AM frequencies back several centuries may also be feasible using tree‐ring data, which will help contextualize and temporally extend multivariate perspectives of climate change that utilize such air masses.