乌兰布和沙漠沙枣树干液流与环境因子关系

The relationship between the stem sap flow of Elaeagnus angustifolia Linn.and environmental factors in Ulan Buh Desert

沙枣(Elaeagnus angustifolia Linn.)是乌兰布和沙漠最重要的阔叶乔木乡土树种,研究其水分利用规律对于乌兰布和沙漠的保护和利用及荒漠化治理具有重要意义,为此采用包裹式茎流仪、土壤水分观测系统和自动气象站分别对沙枣液流、土壤水分含量及其周围环境因子的变化规律进行了长期连续定位观测,对液流与气象因子进行相关性分析并进行逐步回归分析,研究结果表明:1)小时尺度下,影响液流速率的因子分别为PAR、Ts、Ta、Ws、RH,逐步分析后入选的五个因子能够解释70.4%的变异。2)在日尺度下,沙枣液流与PAR、Ws、T极显著正相关(P<0.01),与RH显著负相关,逐步分析后入选的因子能够解释80.1%的变异。3)在月尺度下液流与相对湿度极显著正相关,与饱和水汽压差极显著负相关,与风速显著相关(P<0.01),逐步分析后入选的因子能够解释90.4%的变异。4)不同时间尺度下影响沙枣液流速率的因子不同;随着时间尺度的增大,回归方程所能解释的变异也增加。

Stem flow meter,soil moisture observation system and automatic weather station were applied respectively to carry out long-term and continuous positioning observations on the change law of sap flow in Elaeagnus angustifolia Linn.soil moisture content and surrounding environmental factors,and the correlations between sap flow and meteorological factors were analyzed through step by step regression analysis.Results show that:1)In the hourly scale,the factors affecting the flow rate are photosyn thetically active radiation,soil temperature,air temperature,wind speed,relative humidity.The five factors selected after stepwise analysis can explain 70.4%of the variation.2)On the daily scale,the sap flow is extremely significantly positively correlated with photosyn thetically active radiation,soil temperature,and temperature(P<0.01),and significantly negatively correlated with relative humidity.After stepwise analysis,the selected factors can explain 80.1%of the variation.3)On the monthly scale,downstream flow is extremely significantly positively correlated with relative humidity,extremely significantly negatively correlated with saturated vapor pressure difference,and significantly correlated with wind speed(P<0.01).The selected factors after stepwise analysis can explain 90.4%of the variation.4)The factors that affect the flow rate of E.angustifolia serrata are different under different time scales.As the time scale increases,the variation that can be explained by the regression equation also increases.