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毛乌素沙地油蒿群落冠层导度及影响因素

王珊 查天山 贾昕 吴雅娟 白玉洁 冯薇

王珊, 查天山, 贾昕, 吴雅娟, 白玉洁, 冯薇. 毛乌素沙地油蒿群落冠层导度及影响因素[J]. 北京林业大学学报, 2017, 39(3): 65-73. doi: 10.13332/j.1000-1522.20160409
引用本文: 王珊, 查天山, 贾昕, 吴雅娟, 白玉洁, 冯薇. 毛乌素沙地油蒿群落冠层导度及影响因素[J]. 北京林业大学学报, 2017, 39(3): 65-73. doi: 10.13332/j.1000-1522.20160409
WANG Shan, ZHA Tian-shan, JIA Xin, WU Ya-juan, BAI Yu-jie, FENG Wei. Temporal variation and controlling factors of canopy conductance in Artemisia ordosica community[J]. Journal of Beijing Forestry University, 2017, 39(3): 65-73. doi: 10.13332/j.1000-1522.20160409
Citation: WANG Shan, ZHA Tian-shan, JIA Xin, WU Ya-juan, BAI Yu-jie, FENG Wei. Temporal variation and controlling factors of canopy conductance in Artemisia ordosica community[J]. Journal of Beijing Forestry University, 2017, 39(3): 65-73. doi: 10.13332/j.1000-1522.20160409

毛乌素沙地油蒿群落冠层导度及影响因素

doi: 10.13332/j.1000-1522.20160409
基金项目: 

国家自然科学基金项目 31670708

国家自然科学基金项目 31670710

国家自然科学基金项目 31270755

中央高校基本科研业务费专项资金 2015ZCQ-SB-02

详细信息
    作者简介:

    王珊。主要研究方向:沙地植被光合特性研究。Email:shanwang@bjfu.edu.cn  地址:100083  北京市海淀区清华东路35号北京林业大学水土保持学院

    责任作者:

    贾昕,博士,副教授。主要研究方向:干旱半干旱区植被动态与生态系统碳水循环。Email: xinjia@bjfu.edu.cn  地址:同上

  • 中图分类号: S717.19+3

Temporal variation and controlling factors of canopy conductance in Artemisia ordosica community

  • 摘要: 冠层导度(gc)是影响植物蒸腾和光合作用的重要参数,对环境变化敏感。本研究利用涡度相关法于2015年5—10月对毛乌素沙地油蒿群落的潜热和显热通量进行连续观测,并同步观测空气温度(Ta)、相对湿度(RH)、光合有效辐射(PAR)、土壤含水量(VWC)、降雨(PP)等气象因子,结合Penman-Monteith的冠层导度逆转方程,了解gc时间动态与变异机制。结果表明:研究区油蒿群落gc日变化具有明显的季节差异,夏季(5—8月)gc达到峰值的时间比秋季(9—10月)早约2 h,约在10:00左右达到峰值,比水汽压亏缺(VPD)和PAR的峰值分别提前3~4 h和1~2 h,秋季gc在中午12:00达到峰值后直接下降。PAR、VPD均对gc有显著的调控作用,PAR和VPD对gc的调控阈值分别是1 200 μmol/(m2·s)和1.5 kPa,小于阈值呈正相关,大于阈值呈负相关。30 cm土壤含水量(VWC_30)是调控gc的重要因子,当VWC_30大于0.16 m3/m3时,gc与VWC_30呈正线性关系。在高的土壤含水量条件(VWC_30≥0.16 m3/m3)下,gc对PAR和VPD的敏感性高于低土壤含水量(VWC_30 < 0.16 m3/m3)条件。结果表明,土壤水分是调节荒漠生态系统冠层导度的关键因子,研究结果为荒漠生态系统水文过程模型的建立提供重要参考。

     

  • 图  1  冠层导度、光合有效辐射和水汽压亏缺的日变化

    Figure  1.  Diurnal variation in canopy conductance (gc), photosynthetic active radiation (PAR) and vapor pressure deficit (VPD)

    图  2  冠层导度和环境因子的季节变化

    VWC_10表示10 cm土壤含水量;VWC_30表示30 cm土壤含水量。

    Figure  2.  Seasonal variations in gc and environmental factors

    VWC_10, VWC at 10 cm depth; VWC_30, VWC at 30 cm depth.

    图  3  2015年5到10月冠层导度的月平均值

    Figure  3.  Monthly means of gc from May to October in 2015

    图  4  冠层导度与光合有效辐射和水汽压亏缺的相关关系

    Figure  4.  Correlations between environmental factors PAR, VPD and gc

    图  5  不同水汽压亏缺条件下冠层导度对光合有效辐射的响应和不同PAR条件下gc对VPD的响应

    Figure  5.  Response of gc to PAR under different VPD and response of gc to VPD under different PAR

    图  6  30 cm土壤含水量对冠层导度和对gc与环境因子响应方式的影响

    a.冠层导度(gc)对30 cm土壤含水量的响应;b.不同水分条件下gc对光合有效辐射(PAR)的响应;c.不同水分条件下gc对水汽压亏缺(VPD)的响应。

    Figure  6.  Effects of VWC at 30 cm depth (VWC_30) on gc and the way of gc responded to environment factors

    a, response of canopy conductance (gc) to soil volumetric water content at 30 cm depth (VWC_30); b, response of gc to photosynthetic active radiation (PAR) under high and low VWC; c, response of gc to vapor pressure deficit (VPD) under high and low VWC.

    图  7  6—8月不同时刻(06:00—18:00)冠层导度(gc)与环境因子的敏感性

    Figure  7.  Sensitivity of canopy conductance (gc) to environment factors for each hour from 06:00-18:00 from June to August

    表  1  不同30 cm土壤含水量冠层导度(gc)对光合有效辐射(PAR)和水汽压亏缺(VPD)的回归分析

    Table  1.   Regressions between canopy conductance (gc) and photosynthetic active radiation (PAR) and regressions between gc and vapor pressure deficit (VPD) under high and low soil volumetric water content at 30 cm depth (VWC_30)

    PAR<1 200 μmol/(m2·s)PAR≥1 200 μmol/(m2·s)VPD<1.5 kPaVPD≥1.5 kPa
    VWC_30<0.16m3/m3VWC_30≥0.16m3/m3VWC_30<0.16m3/m3VWC_30≥0.16m3/m3VWC_30<0.16m3/m3VWC_30≥0.16m3/m3VWC_30<0.16m3/m3VWC_30≥0.16m3/m2
    a0.001 30.001 7-0.000 6-0.001 80.560.810.670.95
    b0.430.462.434.660.570.731.952.31
    R20.920.890.490.940.820.900.750.68
    注:gc与PAR的拟合方程为:gc=a·PAR+bab为线性回归分析得出的系数,R2为相关系数。当VPD<1.5 kPa,gc与VPD的拟合方程为:gc=a·VPD+bab为线性回归分析得出的系数。当VPD≥1.5 kPa,gc与VPD的拟合方程为:gc=-alnVPD+bab为非线性回归分析得出的系数。Notes:the a and b in fitting equation of gc and PAR are coefficients obtained by linear regression analysis as the following equation form:gc=a·PAR+b, the letter R2 stands for the correlation coefficient. When VPD<1.5 kPa, the a and b in fitting equation of gc and VPD are coefficients obtained by linear regression analysis as the following equation form:gc=a·VPD+b, the letter R2 stands for the correlation coefficient. When VPD≥1.5 kPa, the a and b in fitting equation of gc and VPD are coefficients obtained by non-linear regression analysis as the following equation form:gc=-alnVPD+b, the letter R2 stands for the correlation coefficient.
    下载: 导出CSV
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  • 收稿日期:  2016-12-14
  • 修回日期:  2017-01-30
  • 刊出日期:  2017-03-01

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