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油松边材液流时空变化及其影响因子研究
引用本文:马履一,王华田.油松边材液流时空变化及其影响因子研究[J].北京林业大学学报,2002,24(3):23-27.
作者姓名:马履一  王华田
作者单位:北京林业大学资源与环境学院
基金项目:高等学校博士学科点专项科研项目;;
摘    要:2000~2001年,利用热扩散式边材液流探针及微型自动气象站对北京林业大学西山实习林场低山阴坡45年生人工油松林单木边材液流速率进行了连续观测.持续的春季干旱导致油松边材液流速率时空变化特征发生很大变化.油松边材液流速率日变化呈现"早晨启动并迅速上升-中午前后出现峰值-峰值后缓慢下降-夜间进入低谷"典型的液流波形特征.树干上位液流波峰值明显大于下位,且峰值和低谷出现时间较早,但二者周期相同.随着时间推移和春季干旱胁迫的加剧,边材液流启动和峰值出现时间提前至17:50和6:00, 峰值进一步减小.灌水后树干液流启动时间和峰值出现时间明显提前,树干边材液流速率显著提高,连续两日树干上位液流峰平均值较灌水前提高40.1%,树干下位液流速率提高95.1%.油松边材液流速率与林内太阳辐射、空气温湿度、土壤温度、风速等环境因子密切相关,其多元线性回归模型达到极显著水平.

关 键 词:油松  边材液流速率  时空变化  影响因子

Spatial and chronic fluctuation of sapwood flow and its relevant variables of Pinus tabulaeformis
Abstract:By means of TDP (Thermal Dissipation Sapwood Flow Velocity Probe) and Portable Meteorological Station, single tree sapwood flow velocity (SFV) at different trunk heights of \%Pinus tabulaeformis,\% and meteorological and soil factors were measured in a 45 year old stand on the north hill slope, in the forest research station of Beijing Forestry University in the West Mountain of Beijing (N39°54′, E116°28′) during the years of 2000 and 2001. Spatial and chronic fluctuation of SFV was affected by spring drought, and typical daily fluctuation of SFV presented as \!ascend promptly in the morning and get to the peak around noon, then descend slowly and reach the valley in the next early morning\". The peak of SFV in the upper trunk was higher than that in the lower trunk apparently, and the peak and valley appearing time in the upper trunk were much more early than that in the lower trunk, too. But their fluctuation cycles were the same. SFV starting time and peak appearing time were getting earlier to 17:15 and 6:00, and the peak became smaller day by day as the spring drought became seriously. SFV starting time and the peak appearing time were late apparently after being watered, and the peak height in the upper and lower trunks increased by 41.1% and 95 1%, respectively, after the specimen being watered. SFV was related to environmental factors in stand, such as solar irradiation intensity, soil and air temperature, air humidity, soil temperature and wind speed. Regression model between SFV and environmental factors was significant at 1% safety.
Keywords:Pinus tabulaeformis    sap flow velocity  spatial and chronic fluctuation  relative variables
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