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生态学杂志 ›› 2011, Vol. 30 ›› Issue (10): 2122-2128.

• 研究报告 • 上一篇    下一篇

华北落叶松冠层平均气孔导度模拟及其对环境因子的响应

孙林,管伟,王彦辉**,徐丽宏,熊伟   

  1. 中国林业科学研究院森林生态环境与保护研究所, 北京 100091
  • 出版日期:2011-10-08 发布日期:2011-10-08

Simulations of Larix principis-rupprechtii stand mean canopy stomatal conductance and its responses to environmental factors.

SUN Lin, GUAN Wei, WANG Yan-hui**, XU Li-hong, XIONG Wei   

  1. Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China
  • Online:2011-10-08 Published:2011-10-08

摘要: 冠层气孔导度是生态水文学研究中的一个重要参数,研究其对环境因子的响应,能为建立机理性的森林蒸腾模型提供理论依据。本文利用热扩散探针,于2005年5—9月,测定了六盘山叠叠沟小流域华北落叶松人工林树干液流及其同步的环境因子,计算了林分冠层平均气孔导度(gc)并构建了Jarvis形式的冠层平均气孔导度模型,分析了gc对光合有效辐射(PAR)、空气水汽压亏缺(DVP)和土壤相对有效含水率(REW)的响应。结果表明:该模型能有效地计算gc的日变化特征,计算与观测的gc决定系数R2为0.76 (n= 952)。gc对各环境因子有不同响应关系,并表现为非线性特征。其中PARgc的驱动因子,当PAR<0.35mmol·m-2·s-1时驱动作用明显,大于此值则驱动作用变小;DVPgc的限制因子,随着DVP的增加gc降低;REW=41%是gc对土壤水分响应的一个关键阈值,当REW>41%时,土壤水分对gc的影响较小,当REW<41%时,土壤水分则成为gc的限制因子。

关键词: 水稻, 冠层, 光谱特征

Abstract: Canopy stomatal conductance is an important parameter in eco-hydrological studies. To understand its responses to environmental factors can offer theoretical basis for developing mechanism-based models of forest transpiration. In this paper, Granier’s probe was adopted to measure the sap flow of a Larix princips-rupprechtii stand in a small watershed of Diediegou in northern part of Liupan Mountains from May to September 2005, and the related environmental factors were simultaneously observed. The canopy transpiration (Ec) and mean canopy stomatal conductance (gc) were calculated, and the observed data were fitted by the Jarivs-type model of canopy stomatal conductance. Then, the responses of gc to environmental factors such as photosynthetically active radiation (PAR), vapor pressure deficit (DVP), and relative extractable soil water (REW) were analyzed. The results showed that Jarivs-type model could accurately simulate the diurnal variation patterns of gc. The coefficient of determination (R2) between calculated and simulated gc was 0.76 (n= 952). The gc had different responses to environmental factors in a non-linear way. PAR was the driving factor for gc, with the driving effect being stronger when the PAR was <0.35mmol·m-2·s-1 while weaker when the PAR was above this threshold. DVP was a limiting factor for gc which decreased with increasing DVP. The response of gc to REW varied. When the REW was less than 41%, it was a key restricting factor to gc; when the REW was higher than 41%, its restricting effect became weaker.

Key words: Rice, Canopy, Spectral characteristics