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晋西黄土区主要树种蒸腾特性研究
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摘要
针对黄土高原干旱半干旱区植被重建的耗水问题和水资源利用状况,采用快速称重法和TDP (Thermal Dissipation Probe)热扩散探针技术,选择生长季典型天气,根据SPAC理论对山西省吉县蔡家川流域主要水土保持灌木树种绣线菊(Spiraea trilobata)、荚迷(Viburnum rhytidophyllum)、虎榛子(Ostryopsis davidiana)、丁香(Syringa oblata)、连翘(Forsythia suspens)、忍冬(Lonicera japonica)、山楂叶悬钩子(Rubus.crataegifolius)和红瑞木(Cornus alba)和经济树种杏树(Prunus sibirica)、梨树(Pear tree)、枣树(Jujube tree)、李子树(Prunus cerasifera)、杜梨(Pyrus betulaefolia)、和苹果树(Malus pumila)(国光、富士、乔纳金)以及刺槐(Robinia pseudoacacia)、油松(Pinus tabulaeformis)、辽东栎(Quercus liaotungensis)和山杨(Populus davidiana)等树种的蒸腾耗水、液流速率的日变化、季节变化规律及影响因子进行了探讨,建立了主要气象因子与各树种的蒸腾速率、液流速率的预测模型,推算出生长季林分林木总蒸腾耗水量以及影响液流速率的主导环境因子。
     主要研究结果如下:
     1.各灌木树种和经济树种叶片含水量和叶水势日变化呈波浪型,早晚的含水量高于中午,全天叶水势最低值出现在10:00到15:00之间。各树种的叶鲜重与叶面积可用指数曲线来拟合,而叶鲜重与地径的函数关系对于不同树种拟合的曲线不同。
     2.各灌木树种和经济树种蒸腾速率日变化曲线可分为单峰和双峰型。典型天气下各灌木树种日平均蒸腾速率大小为:荚迷>山楂叶悬钩子>丁香>绣线菊>红瑞木>虎榛子>忍冬>连翘。
     3.叶水势与蒸腾速率负相关,可用对数曲线拟合。各树种回归系数不同,回归系数绝对值越大,蒸腾失水速率越快,抗旱性越弱。
     4.刺槐、油松、辽东栎和山杨的树干液流速率呈明显的昼夜变化,曲线呈单峰或“准”单峰型。不同天气条件下液流速率到达峰值时间不同。
     5.生长季内林木总蒸腾耗水量对刺槐林为272.89mm,油松林为266.46mm,辽东栎林为131.26mm,对山杨林为311.31mm,刺槐林为油松林的1.02倍,山杨林为辽东栎林的2.37倍。
     6.影响各树种树干液流速率的主导因子分别为:刺槐是土壤含水量和空气饱和水汽压差;油松是太阳辐射和土壤含水量;辽东栎是大气温度和太阳辐射;山杨是太阳辐射和空气饱和水汽压差。
Aiming at water consumption of trees construction and the using of water resources, daily and seasonal changes of transpiration rate of 8 kinds of shurb trees and 9 kinds of economic trees species, sap flow velocity of 4 kinds of trees species for soil protecting in Semi-arid Area and the major determinant factors were studied by using the method of rapid weighting and Thermal Dissipation Probe considering planting-configuration and water using and the SPAC theory of Semi- arid Area in Loess Plateau of west Shanxi. Fitting models of transpiration rate and meteorological factors、the estimated total water consumption used for tree transpiration and the dominant environmental factors influencing sap flow velocity were concluded.
     1. The diurnal variation of leaf water content and leaf water potential were a waveform curve and the former was higher in the morning and evening than at noon, the minimum lowest point of the latter was between 10:00 and 14:00 for shurb and economic trees. The relationship between leaf fresh weight and leaf area can be fitted by exponential curve, and the relationship between leaf fresh weight and diameter can be fitted by different fuction of tree species.
     2. Diurnal changes of transpiration rate of different species could taked on " single peak" and " double peak" curves; The tree species had the average transpiration rate in the following orde: V. Rhytidophyllum>R.crataegifolius>S.oblata>S. trilobata> O. davidiana> C. alba> L. japonica> F. suspens.
     3. Leaf water potential and transpiration were negatively related, and their relationships can be fitted by logarithmic curve. The bigger of absolute value of regression coefficient for Logarithmic function, the more lossing water transpiration rate,the weaker trees drought.
     4. Sap flow velocity (SFV) of R. pseudoacacia、P. tabulaeformis、Q. liaotungensis and P.davidiana exhibited diurnal patterns and the curves take on single peak and Quasi-single peak; the time of daily SFV maximum values was different in different days.
     5. The forecast suggests that the estimated total water consumption used for tree transpiration for R. pseudoacacia was much higher than that of other tree species over the whole growing season (272.89 mm、266.46 mm、131.26 mm and 311.31mm, respectively).
     6. Diurnal changes in sap flow were closely related to changes in environmental variables, but the dominant environmental factors differed between the species. Soil moisture and water vapor pressure deficit were the governing factors for Robinia pseudoacacia, solar radiation and soil moisture were mastering factors in Pinus tabulaeformis SFV, air temperature and solar radiation were the main factors influencing diurnal changes in Q. liaotungensis SFV, whereas solar radiation and water vapor pressure deficit were the principal factors for P. davidiana. A statistical model to calculate SFV from micrometeorological data is provided.
引文
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