长江流域资源与环境 >> 2014, Vol. 23 >> Issue (02): 267-.doi: 10.11870/cjlyzyyhj201402016

• 生态环境 • 上一篇    下一篇

江西千烟洲木荷液流特征及其与气象因子的关系

涂洁|刘琪璟|王辉民|廖迎春|李燕燕   

  1. (1.南昌工程学院生态与环境科学研究所|江西 南昌 330099;2.北京林业大学林学院|北京 100083;3.中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室千烟洲生态站|北京 |100101
  • 出版日期:2014-02-20

DYNAMICS OF SAP FLOW VELOCITIES AND ITS RELATIONSHIP WITH METEOROLOGICAL FACTORS OF SCHIMA SUPERBA FOREST IN QIANYANZHOU EXPERIMENTAL STATION

TU Jie1,LIU Qijing2,WANG Huiming3, LIAO Yingchun1,LI Yanyan1   

  1. (1. Research Institute of Ecology &|Environmental Sciences, Nanchang Institute of Technology, Nanchang 330099,China;2. Department of Forest Sciences, Beijing Forestry University, Beijing 100083, China|3. Qianyanzhou Ecological Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • Online:2014-02-20

摘要:

采用Granier热扩散式探针对江西千烟洲木荷(Schima superba)树干液流速率进行连续监测,并对气象因子进行同步测定。结果表明:不同天气条件下木荷树干液流速率日变化规律存在差异,晴天为宽峰型曲线,阴天为单峰型曲线,雨天无明显的变化规律。不同月份木荷树干液流速率大小以及液流启动、达到峰值的时间不同。各月平均液流速率(cm/s)大小关系依次为7月(0001 663)>8月(0001 56)>6月(0.001 472)>9月(0.001 314)>5月(0.001 216)>4月(0001 101)>10月(0000 847)。6月液流启动时间最早, 5、7、8、9月均推迟 05~1 h,4、10月最迟。7月液流最早达到峰值,5、6、8月次之,9、10月最迟。液流启动和达到峰值均滞后太阳辐射1 h,而与冠层温度、相对湿度不存在明显的时滞效应。包含与不包含时滞效应的方差分析结果表明,液流速率与相对湿度呈显著负相关,与平均净辐射呈显著正相关,与冠层温度相关性较弱。气象因子对木荷液流速率的影响程度依次为平均净辐射(0677*〖KG-*2〗*)>冠层相对湿度(-0417*〖KG-*2〗*)>冠层温度(0088)和平均净辐射(0752*〖KG-*2〗*)>冠层相对湿度(-0325*〖KG-*2〗*)>冠层温度(0158)。建立液流速率与气象因子的多元线性回归方程,回归方程和回归系数的相关性检验均达到极显著水平。回归方程的拟合效果均良好,决定系数分别达到093和095

Abstract:

Sap flow velocity (Js,cm/s) of Schima superba was measured using Granier’s thermal dissipation probe with meteorological factors monitored simultaneously by automatic weather station in Qianyanzhou ecological station. The results showed that significant difference existed in the diurnal fluctuations of sap flow under three typical weather conditions. Diurnal variations of sap flow displayed widepeaked curves on sunny days with starting time at 6:30 and peaking time at 12∶30. Diurnal variations of sap flow displayed singlepeaked curves on overcast days with starting time at 7∶30 and peaking time at 14∶30. While on rainy days, no distinct diurnal variations of sap flow occurred during the daytime. On the whole, sap flow velocity on sunny days were obviously higher than those on overcast days and rainy days due to obviously higher solar radiation strength,air temperature and lower relative humidity. Patterns of diurnal variations of sap flow varied among different growing seasons, mainly in the average level of sap flow velocity, the initiating time in the early morning and the declining time in the late afternoon. The average sap flow velocity followed the 〖JP2〗order of July (0001 663) > August (0001 56) > June (0001 472) > September (0001 314)〖JP〗 > May (0001 216) > April (0001 101) > October(0000 847). Sap flow velocity peaked in June, followed by July and August. The starting time of sap flow in June was 0.5-1 hours earlier than that in May, July, August and September. The initiation of sap flow was the latest in April and October. Sap flow peaked earliest in July, followed by May, June and August and latest in September and October. The initiation and peak of sap flow lagged behind average net radiation (ANR) but synchroised with canopy relative humidity (CRH) and canopy air temperature (CT). The variance analysis results showed that in the cases with and without the time lag effect, there existed significantly positive correlations between Js and ANR, while significantly negative correlations between sap flow velocity and average net radiation. There was no significant correlation between sap flow velocity and CT in both cases. The correlation strength between meteorological factors and Js were ANR (0677*〖KG-*2〗*) > CRH (-0417*〖KG-*2〗*) > CT (0088) and ANR (0752*〖KG-*2〗*) > CRH (-0325*〖KG-*2〗*) > CT (0158), respectively, indicating that when the time lag effect was considered, sap flow velocity was more dependent on average net radiation and canopy relative humidity. Multivariate linear model were used to quanitfy the integrated effects of three meteorological factors on sap flow velocity. The regression models and all parameters were significant at 1% level. The determination coefficients between comprehensive meteorological factors and sap flow velocity were 093 and 095, respectively

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