柴达木盆地沙棘茎流速率与环境因子的关系

Relationships between Sap Flow Velocity of Hippophae rhamnoides Linn. and Meteorological Factors in the Qaidam Basin

采用热扩散flow-32包裹式茎流计,于2014年6—9月对柴达木盆地的沙棘茎流速率进行连续观测,并应用Vantage Pro 2小型气象站对林地的太阳辐射、大气温度、相对湿度主要气象因子进行同步采集,对不同天气条件下沙棘茎流速率的变化规律以及茎流速率与主要气象因子的相关关系进行研究。结果表明:典型晴天下沙棘茎流日变化呈双峰型,典型阴天下沙棘茎流呈单峰型,晴天的平均茎流速率是阴天的2.87倍;生长季各月的平均茎流速率为:8月>7月>9月>6月;6—9月沙棘茎流速率与温度、太阳辐射呈极显著正相关(P<0.01),与湿度呈极显著负相关(P<0.01),各气象因子相关系数绝对值为:太阳辐射(0.811)>大气温度(0.594)>湿度(-0.571),太阳辐射是主导环境要素;用SPSS软件针对上述3种环境因子进行多元线性逐步回归,得回归模型Fs=19.268-0.221Ta-0.055RH+0.036Rs(R2=0.82),能够对柴达木盆地的沙棘蒸腾耗水量进行预测。

A flow-32 packaged stem sap flow gauge was used to continually measure the sap flow dynamics of Hip- pophae rhamnoides Linn. in the Qaidam Basin during the period from June to September 2014. At the same time, the meteorological factors including solar radiation, air temperature and relative humidity in forest land were detected using a Vantage Pro 2 automatic weather station. The daily variation of sap flow velocity under different weather conditions and the correlations between sap flow rate and main meteorological factors were analyzed. The results showed that the daily variation curves of stem flow velocity were bimodal on typical sunny days but unimodal on typ- ical cloudy days, and the average stem flow rate on sunny days was 2.87 times of that on cloudy days. The average stem flow rate in growing season was in an order of August 〉 July 〉 September 〉 June. During the period from June to September, there were the extremely significant positive correlations between the sap flow velocity and the temper- ature and solar radiation, but there was an extremely significant negative correlation between the sap flow velocity and the humidity. The absolute values of the correlation coefficients of all the meteorological factors were in an or- der of total radiation （0. 811 ） 〉 air temperature （0. 594 ） 〉 relative humidity （ - 0.571 ）, and solar radiation was the dominant meteorological factor. The SPSS software was used to carry out the multivariate linear stepwise re- gression for the meteorological factors, the regression model was expressed as： Fs = 19. 268 - O. 221Ta - O. 055 Rtt ＋ O. 036R （ R2 = 0. 82 ）, and it could be used to predict the water consumption by transpiration of H. rh- amnoides Linn. in the Qaidam Basin.