Wang Hui-Mei, Sun Wei, Zu Yuan-Gang, Wang Wen-Jie
Ministry of Education Key Laboratory of Forest Plant Ecology, Northeast Forestry University, Harbin 150040, China.
Ying Yong Sheng Tai Xue Bao. 2011 Dec;22(12):3109-16.
Based on the one-year (2005) observations with a frequency of half hour on the stem sap flow of Larix gmelinii plantation trees planted in 1969 and the related environmental factors air humidity (RH), air temperature (T(air)), photosynthetic components active radiation (PAR), soil temperature (T(soil)), and soil moisture (TDR), principal analysis (PCA) and correction analysis were made on the time lag effect of the stem flow in different seasons (26 days of each season) and in a year via dislocation analysis, with the complexity and its integrative effects of the time lags of environment factors affecting the stem sap flow approached. The results showed that in different seasons and for different environmental factors, the time lag effect varied obviously. In general, the time lag of PAR was 0.5-1 hour ahead of sap flow, that of T(air) and RH was 0-2 hours ahead of or behind the sap flow, and the time lags of T(soil) and TDR were much longer or sometimes undetectable. Because of the complexity of the time lags, no evident improvements were observed in the linear correlations (R2, slope, and intercept) when the time lags based on short-term (20 days) data were used to correct the time lags based on whole year data. However, obvious improvements were found in the standardized and non-standardized correlation coefficients in stepwise multiple regressions, i.e., the time lag corrections could improve the effects of RH, but decreased the effects of PAR, T(air), and T(soil). PCA could be used to simplify the complexity. The first and the second principal components could stand for over 75% information of all the environmental factors in different seasons and in whole year. The time lags of both the first and the second principal components were 1-1.5 hours in advance of the sap flow, except in winter (no time lag effect).
基于2005年对1969年种植的兴安落叶松人工林树木树干液流进行的为期一年、半小时一次的观测以及相关环境因子(空气湿度(RH)、气温(T(air))、光合有效辐射(PAR)、土壤温度(T(soil))和土壤湿度(TDR)),通过错位分析对不同季节(每个季节26天)和一年中树干液流的时间滞后效应进行了主成分分析(PCA)和校正分析,探讨了影响树干液流的环境因子时间滞后的复杂性及其综合效应。结果表明,在不同季节以及不同环境因子下,时间滞后效应差异明显。总体而言,PAR的时间滞后比液流提前0.5 - 1小时,T(air)和RH的时间滞后比液流提前或滞后0 - 2小时,T(soil)和TDR的时间滞后则长得多,有时甚至无法检测到。由于时间滞后的复杂性,当使用基于短期(20天)数据的时间滞后校正全年数据的时间滞后时,线性相关性(R2、斜率和截距)没有明显改善。然而,在逐步多元回归中标准化和非标准化相关系数有明显改善,即时间滞后校正可以提高RH的效应,但降低了PAR、T(air)和T(soil)的效应。PCA可用于简化复杂性。第一和第二主成分可代表不同季节和全年所有环境因子超过75%的信息。第一和第二主成分的时间滞后均比液流提前1 - 1.5小时,但冬季除外(无时间滞后效应)。