Landscape Tree Selection for Waterlogging Resistance in Response to Climate Change in Shanghai
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1.College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China;2.Sichuan Provincial Institute of Land and Space Planning, Chengdu 610036, China;3.Dresden University of Technology, Tharandt 01735, Germany

Clc Number:

TU986

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    Abstract:

    Twenty-five popular landscape trees in Shanghai were selected and seven indicators of victimization, chlorophyll, electrical conductivity, specific leaf mass, net photosynthetic rate, malondialdehyde and proline content were measured in the flood simulation experiments. Then, the resistance spectrums of the 25 landscape trees were scheduled. Finally, a method for predicting the resistance of landscape trees via the level of photosynthesis was put forward, giving priority to chlorophyll, specific leaf mass and net photosynthetic rate indicators. According to the level of waterlogging resistance, 25 tree species were divided into four types: strong waterlogging resistance, relatively waterlogging resistance, general waterlogging resistance and weak-waterlogging resistance.

    Table 6
    Table 2
    Table 4
    Table 3
    Fig.1 Variation coefficient of morphology among trees under flooding stress
    Fig.2 Variation coefficient of chlorophyll among trees under flooding stress
    Fig.3 Variation coefficient of electrical conductivity among trees under flooding stress
    Fig.4 Variation coefficient of specific leaf mass among trees under flooding stress
    Fig.5 Variation coefficient of net photosynthetic rate among trees under flooding stress
    Fig.6 Variation coefficient of malondialdehyde content among trees under flooding stress
    Fig.7 Variation coefficient of proline content among trees under flooding stress
    Table 1
    Table 5
    Reference
    [1] 丁一汇, 任国玉, 石广玉, 等. 气候变化国家评估报告(Ⅰ):中国气候变化的历史和未来趋势[J]. 气候变化研究进展, 2006, 2(1): 3.
    [2] 贺芳芳, 徐家良. 20世纪90年代以来上海地区降水资源变化研究[J]. 自然资源学报, 2006, 21(4): 210.
    [3] 李巧萍, 丁一汇, 董文杰. SRES A2情景下未来30年我国东部夏季降水变化趋势[J]. 应用气象学报, 2008, 19(6): 770.
    [4] 江志红, 李杨. 中国东部不同区域城市化对降水变化影响的对比研究[J]. 热带气象学报, 2014, 30(4): 601.
    [5] 房国良, 高原, 徐连军, 等. 上海市降雨变化与灾害性降雨特征分析[J]. 长江流域资源与环境, 2012, 21(10): 1270.
    [6] 陆敏, 刘敏, 权瑞松, 等. 上海暴雨灾害的系统特征与脆弱性分析[J]. 华东师范大学学报:自然科学版, 2010(2): 9.
    [7] 梁萍, 丁一汇, 何金海, 等. 上海地区城市化速度与降水空间分布变化的关系研究[J]. 热带气象学报, 2011, 27(4): 475.
    [8] 王寒梅, 焦珣. 海平面上升影响下的上海地面沉降防治策略[J]. 气候变化研究进展, 2015, 11(4): 256.
    [9] 韩玉洁, 孙海菁, 朱春玲, 等. 上海沿海防护林树种适应性评价[J]. 南京林业大学学报:自然科学版, 2010, 34(4): 165.
    [10] 卓仁英, 陈益泰. 木本植物抗涝性研究进展[J]. 林业科学研究, 2001, 14(2): 215.
    [11] 衣英华, 樊大勇, 谢宗强, 等. 模拟淹水对枫杨和栓皮栎气体交换、叶绿素荧光和水势的影响[J]. 植物生态学报, 2006, 30(6): 960.
    [12] 曹福亮, 蔡金峰, 汪贵斌,等. 淹水胁迫对乌桕生长及光合作用的影响[J]. 林业科学, 2010, 46(10): 57.
    [13] 黄香兰, 郭淑红, 薛立,等. 淹水胁迫对华南地区3种园林树种生理特征的影响[J]. 中国农学通报, 2012, 28(13): 24.
    [14] 汪贵斌, 曹福亮, 张晓燕, 等. 涝渍胁迫对不同树种生长和能量代谢酶活性的影响[J]. 应用生态学报, 2010, 21(3): 590.
    [15] 杨东, 万福绪, 李盟. 水盐胁迫对上海4个防护林树种生长和生理特性的影响[J]. 水土保持研究, 2014, 21(1): 254.
    [16] 张虎, 曹福亮, 范俊俊, 等. 淹水胁迫对湖北海棠生长及叶绿素荧光动力学的影响[J]. 南京林业大学学报:自然科学版, 2018, 42(1): 35.
    [17] 潘向艳, 季孔庶, 方彦. 淹水胁迫下杂交鹅掌楸无性系叶片内源激素含量的变化[J]. 南京林业大学学报:自然科学版, 2008, 32(1): 29.
    [18] IRFAN M, HAYAT S, HAYAT Q, et al. Physiological and biochemical changes in plants under waterlogging [J]. Protoplasma, 2010, 241(1): 3.
    [19] AHMED S, NAWATA E, HOSOKAWA M, et al. Alterations in photosynthesis and some antioxidant enzymatic activities of mungbean subjected to waterlogging [J]. Plant Science, 2002, 163(1): 117.
    [20] 蔡金峰, 曹福亮, 张往祥. 淹水胁迫对乌桕幼苗生长及根系无氧呼吸酶活性的影响[J]. 中南林业科技大学学报, 2013, 33(9): 5.
    [21] 汪贵斌, 曹福亮, 王媛. 涝渍对3个树种生长、组织孔隙度和渗漏氧的影响[J]. 植物生态学报, 2012, 36(9): 982.
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ZHANG Deshun, CHEN Luqiyao, LUO Jingru, LIU Ming, YAO Chiyuan. Landscape Tree Selection for Waterlogging Resistance in Response to Climate Change in Shanghai[J].同济大学学报(自然科学版),2021,49(2):264~271

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  • Received:February 14,2020
  • Online: March 18,2021
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