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意大利的臭氧污染不会导致欧洲山毛榉的五年体积生长。

Five-year volume growth of European beech does not respond to ozone pollution in Italy.

机构信息

CNR, Via Madonna del Piano, Sesto Fiorentino, Italy.

ENEA Casaccia, Via Anguillarese 301, Rome, Italy.

出版信息

Environ Sci Pollut Res Int. 2018 Mar;25(9):8233-8239. doi: 10.1007/s11356-017-9264-2. Epub 2017 May 24.

DOI:10.1007/s11356-017-9264-2
PMID:28540544
Abstract

A unique database of stand volume growth, estimated as periodic annual volume increment (in m ha per year over the period 2001-2005) from 728 European beech (Fagus sylvatica L.) sites distributed across Italy, was used to assess the effects of ambient ozone (O), expressed as annual average (M24), accumulated exposure above a 40 ppb hourly threshold (AOT40), and total stomatal ozone flux (POD0). Growth data were from the National forest inventory of Italy, while climate data and ozone concentrations were computed by the WRF and CHIMERE models, respectively. Results show that the growth increased with increasing solar radiation and air temperature and decreased with increasing number of cold days, while effects of soil water content and O were not significant. In contrast, the literature results suggest that European beech is sensitive to both drought and O. Ozone levels resulted to be very high (48 ppb M24, 51,200 ppb h AOT40, 21.08 mmol m POD0, on average) and thus able to potentially affect European beech growth. We hypothesize that the high-frequency signals of soil water and O got lost when averaged over 5 years and recommended finer time-resolution investigations and inclusion of other factors of variability, e.g., thinning, tree age, and size.

摘要

一个独特的立木材积生长数据库,通过 728 个分布在意大利的欧洲山毛榉(Fagus sylvatica L.)站点,估计为定期的年体积增量(2001-2005 年期间每年每公顷 m3),用于评估环境臭氧(O)的影响,臭氧表示为年平均(M24),40ppb 小时阈值以上的累积暴露量(AOT40)和总气孔臭氧通量(POD0)。生长数据来自意大利国家森林清查,而气候数据和臭氧浓度分别由 WRF 和 CHIMERE 模型计算得出。结果表明,生长随太阳辐射和空气温度的增加而增加,随冷天数的增加而减少,而土壤水分含量和 O 的影响不显著。相比之下,文献结果表明,欧洲山毛榉对干旱和 O 都很敏感。臭氧水平非常高(M24 为 48ppb,AOT40 为 51,200ppb h,POD0 为 21.08mmol m),因此可能会影响欧洲山毛榉的生长。我们假设土壤水分和 O 的高频信号在平均 5 年内丢失,并建议进行更精细的时间分辨率研究,并纳入其他变异性因素,例如间伐、树龄和大小。

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