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毛乌素沙地油蒿光合电子传递速率生长季动态及其对环境因子的响应

雒宇 马莉 靳川 李鑫豪 李成 贾昕 查天山

雒宇, 马莉, 靳川, 李鑫豪, 李成, 贾昕, 查天山. 毛乌素沙地油蒿光合电子传递速率生长季动态及其对环境因子的响应[J]. 北京林业大学学报, 2021, 43(2): 54-62. doi: 10.12171/j.1000-1522.20200154
引用本文: 雒宇, 马莉, 靳川, 李鑫豪, 李成, 贾昕, 查天山. 毛乌素沙地油蒿光合电子传递速率生长季动态及其对环境因子的响应[J]. 北京林业大学学报, 2021, 43(2): 54-62. doi: 10.12171/j.1000-1522.20200154
Luo Yu, Ma Li, Jin Chuan, Li Xinhao, Li Cheng, Jia Xin, Zha Tianshan. Temporal dynamics in photosynthetic electron transfer rate of Artemisia ordosica in growing season and its response to environmental factors in Mu Us Sandy Land of northwestern China[J]. Journal of Beijing Forestry University, 2021, 43(2): 54-62. doi: 10.12171/j.1000-1522.20200154
Citation: Luo Yu, Ma Li, Jin Chuan, Li Xinhao, Li Cheng, Jia Xin, Zha Tianshan. Temporal dynamics in photosynthetic electron transfer rate of Artemisia ordosica in growing season and its response to environmental factors in Mu Us Sandy Land of northwestern China[J]. Journal of Beijing Forestry University, 2021, 43(2): 54-62. doi: 10.12171/j.1000-1522.20200154

毛乌素沙地油蒿光合电子传递速率生长季动态及其对环境因子的响应

doi: 10.12171/j.1000-1522.20200154
基金项目: 国家自然科学基金项目(31670710、31670708)
详细信息
    作者简介:

    雒宇。主要研究方向:干旱半干旱区生态系统碳水循环。Email:704987951@qq.com 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:

    查天山,博士,博士生导师。主要研究方向:生态系统碳水循环,植物生理生态。Email:tianshanzha@bjfu.edu.cn 地址:同上

  • 中图分类号: Q945.11 Q945.17

Temporal dynamics in photosynthetic electron transfer rate of Artemisia ordosica in growing season and its response to environmental factors in Mu Us Sandy Land of northwestern China

  • 摘要:   目的  探究干旱半干旱地区植被光合生理在生长季动态变化及其对各个影响因子的响应机制,对进一步了解该区植被对波动环境的适应性具有重要意义。  方法  该研究于2019年5—9月,对典型沙生植被油蒿的光合电子传递速率(ETR)进行长期原位连续监测,同步观测光合有效辐射(PAR)、空气温度(Ta)、相对湿度(RH)和土壤含水量(SWC)等环境因子,同时测定叶绿素含量(SPAD)。分析ETR的动态变化规律及其对主要影响因子的响应。  结果  ETR与PAR、Ta、SPAD显著相关(P < 0.05),ETR月均值7月份达到最大,9月份最小。ETR随光强的变化呈上升趋势,且在弱光条件下(PAR ≤ 800 μmol/(m2·s))对光照响应强度大于强光。ETR随Ta的变化呈先上升后下降的趋势,5月(展叶期)和9月(落叶期)的高低温胁迫阈值分别为5和20 ℃,6—8月(成熟期)为10和25 ℃。ETR与SPAD呈线性正相关关系。成熟期ETR的稳定性小于展叶期和落叶期。  结论  通过以上研究发现PAR、Ta、SPAD是影响ETR的3个主要因子。在展叶期ETR主要受SPAD的影响,成熟期主要受温度和光强的影响,落叶期主要受植物生理的影响。油蒿在不同环境因子的交替作用下均体现出了良好的适应性。此外适当的升温能够促进光合电子的传递,增强植物光合能力。该研究结果可以为全球气候变暖下植物光合生理对环境响应的研究提供一定的理论指导,同时也为荒漠植被的恢复提供参考。

     

  • 图  1  2019年5—9月油蒿环境因子在生长季的动态变化

    PAR. 光合有效辐射;Ta. 空气温度;RH. 相对湿度;P. 降雨量;SWC. 土壤含水量;SWC10. 10 cm 处土壤含水量;SWC30. 30 cm 处土壤含水量。下同。PAR, photosynthetically active radiation; Ta, air temperature; RH, relative humidity; P, precipitation; SWC, soil water content; SWC10, soil water content in 10 cm; SWC30, soil water content in 30 cm. Same as below.

    Figure  1.  Dynamics in environmental factors in Artemisia ordosica from May to September in 2019

    图  2  2019年5—9月油蒿叶绿素含量在生长季的动态变化

    SPAD. 叶绿素相对含量。下同。SPAD, relative chlorophyll content. Same as below.

    Figure  2.  Dynamics of chlorophyll content (SPAD) in Artemisia ordosica from May to September in 2019

    图  3  2019年5—9月油蒿光合电子传递速率在生长季的动态变化

    ETR. 光合电子传递速率。下同。ETR, photosynthetic electron transfer rate. The same below.

    Figure  3.  Seasonal changes in ETR in Artemisia ordosica from May to September in 2019

    图  4  2019年5—9月油蒿光合电子传递速率与光合有效辐射的关系

    Figure  4.  Relationship between ETR and PAR for Artemisia ordosica from May to September in 2019

    图  5  2019年5—9月油蒿光合电子传递速率与空气温度的关系

    Figure  5.  Relationship between ETR and air temperature (Ta) for Artemisia ordosica from May to September in 2019

    图  6  2019年5—9月油蒿光合电子传递速率与叶绿素含量的关系

    Figure  6.  Relationship between ETR and chlorophyll content for Artemisia ordosica from May to September in 2019

    表  1  油蒿光合电子传递速率与影响因子相关性

    Table  1.   Correlations between ETR and influencing factors in Artemisia ordosica

    相关指标 Relevant indexETRPARTaRHPPTSWC10SWC30SPAD
    ETR 1
    PAR 0.646** 1
    Ta 0.376** 0.422** 1
    RH −0.321 −0.684** −0.310** 1
    PPT 0.345 −0.486 0.179* 0.488** 1
    SWC10 0.001 0.200* 0.183* −0.010 −0.046 1
    SWC30 0.077 0.280** 0.310** −0.113 −0.086 0.588** 1
    SPAD 0.818** 0.125* 0.417* 0.351 0.032 0.397 0.597** 1
    注:**表示在0.01水平(双侧)上极显著相关;*表示在0.05水平(双侧)上显著相关。Notes: ** means a very significant correlation at 0.01 level (bilateral); * means a significant correlation at 0.05 level (bilateral).
    下载: 导出CSV

    表  2  2019年5—9月油蒿光合电子传递速率与光合有效辐射回归模型

    Table  2.   Regression models between ETR and PAR for Artemisia ordosica from May to September in 2019

    月份
    Month
    回归拟合模型 Regression fitting model
    (PAR ≤ 800 μmol/(m2·s))
    R1 2回归拟合模型 Regression fitting model
    (PAR > 800 μmol/(m2·s))
    R2 2
    5y = −0.678 + 0.200x0.95y = 118.474 + 0.061x0.96
    6y = 4.209 + 0.209x0.97y = 138.194 + 0.052x0.95
    7y = 1.500 + 0.218x0.96y = 136.220 + 0.051x0.93
    8y = 2.563 + 0.215x0.95y = 135.831 + 0.049x0.95
    9y = −0.065 + 0.197x0.96y = 115.271 + 0.053x0.95
    下载: 导出CSV

    表  3  2019年5—9月油蒿光合电子传递速率与空气温度回归模型

    Table  3.   Regression models between ETR and Ta for Artemisia ordosica from May to September in 2019

    月份
    Month
    温度变化区间
    Temperature changing interval
    回归拟合模型
    Regression fitting model
    R2
    5 5 ℃ < Ta ≤ 11 ℃ y = 0.273 + 1.833x 0.95
    11 ℃ < Ta ≤ 21 ℃ y = 0.266 + 9.265x 0.96
    22 ℃ < Ta < ≤ 25 ℃ y = 1.134 − 3.410x 0.95
    6 10 ℃ < Ta ≤ 15 ℃ y = 0.121 + 1.835x 0.92
    15 ℃ < Ta ≤ 24 ℃ y = 0.415 + 12.648x 0.95
    24 ℃ < Ta ≤ 29 ℃ y = 0.701 − 5.620x 0.81
    7 9 ℃ < Ta ≤ 16 ℃ y = 0.136 + 1.855x 0.94
    16 ℃ < Ta ≤ 26 ℃ y = 0.579 + 12.250x 0.96
    26 ℃ < Ta ≤ 29 ℃ y = −1.241 − 7.534x 0.92
    8 9 ℃ < Ta ≤ 15 ℃ y = 0.135 + 1.832x 0.91
    15 ℃ < Ta ≤ 5 ℃ y = 0.456 + 12.159x 0.93
    25 ℃ < Ta ≤ 29 ℃  y = 1.135 − 6.523x 0.79
    9 6 ℃ < Ta ≤ 10 ℃ y = 0.108 + 1.813x 0.94
    10 ℃ < Ta ≤ 20 ℃ y = 0.410 + 9.639x 0.96
    20 ℃ < Ta ≤ 25 ℃ y = 0.109 − 4.015x 0.94
    下载: 导出CSV
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  • 收稿日期:  2020-05-20
  • 修回日期:  2020-09-04
  • 网络出版日期:  2021-01-28
  • 刊出日期:  2021-02-24

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