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庐山日本柳杉径向生长对气候响应的边际效应

郑永宏 张芸毓 王丹 于佳禾 汪嘉霖

郑永宏, 张芸毓, 王丹, 于佳禾, 汪嘉霖. 庐山日本柳杉径向生长对气候响应的边际效应[J]. 北京林业大学学报, 2021, 43(7): 63-69. doi: 10.12171/j.1000-1522.20200372
引用本文: 郑永宏, 张芸毓, 王丹, 于佳禾, 汪嘉霖. 庐山日本柳杉径向生长对气候响应的边际效应[J]. 北京林业大学学报, 2021, 43(7): 63-69. doi: 10.12171/j.1000-1522.20200372
Zheng Yonghong, Zhang Yunyu, Wang Dan, Yu Jiahe, Wang Jialin. Marginal effect of radial growth of Cryptomeria japonica to climate in Lushan Mountain of southwestern China[J]. Journal of Beijing Forestry University, 2021, 43(7): 63-69. doi: 10.12171/j.1000-1522.20200372
Citation: Zheng Yonghong, Zhang Yunyu, Wang Dan, Yu Jiahe, Wang Jialin. Marginal effect of radial growth of Cryptomeria japonica to climate in Lushan Mountain of southwestern China[J]. Journal of Beijing Forestry University, 2021, 43(7): 63-69. doi: 10.12171/j.1000-1522.20200372

庐山日本柳杉径向生长对气候响应的边际效应

doi: 10.12171/j.1000-1522.20200372
基金项目: 国家自然科学基金面上项目(41771227)
详细信息
    作者简介:

    郑永宏,博士,副教授。主要研究方向:树轮气候学。Email:zhengyh@whu.edu.cn 地址:430079 湖北省武汉市珞喻路129号武汉大学资源与环境科学学院

  • 中图分类号: S718.45

Marginal effect of radial growth of Cryptomeria japonica to climate in Lushan Mountain of southwestern China

  • 摘要:   目的  深入认知树轮−气候要素之间的关系,揭示树木径向生长的主要限制性因素的相对贡献率及边际效应,以提升树轮在树轮生态学、树轮气候学研究中的应用价值。  方法  基于庐山地区日本柳杉树轮宽度资料和庐山气象站气象资料,采用树轮气候学方法研制树轮宽度年表,基于相关分析方法初步识别树木径向生长的主要限制性因素,进而利用增强回归树分析方法揭示了庐山日本柳杉径向生长的主要影响因素相对贡献及边际效应。  结果  正向影响庐山日本柳杉径向生长的因素按重要程度从大到小依次为当年1—3月平均最低气温(20.66%)、上年2—11月相对湿度(15.4%)、当年2—3月平均水汽压(9.47%),负向影响庐山日本柳杉径向生长的因素按重要程度从大到小依次为上年11月日照时数(20.81%)、上年5月最大日降水量(20.54%)、当年7月平均气温(13.11%);树轮−气候之间的关系在阈值范围之内具有较好的线性关系,阈值范围外则不具有线性关系。  结论  庐山日本柳杉径向生长受多种气候要素的综合影响,任一要素的影响均不是简单的线性关系,均存在明显的阈值效应。在分析树木径向生长对气候要素响应及进行树轮气候重建时,对边际效应问题应予以重视,以增强树轮−气候间关系的可信度及气候重建的可靠性。

     

  • 图  1  采样点位置图

    Figure  1.  Location of sampling sites

    图  2  年表及样本量

    Figure  2.  Chronologies and sample size

    图  3  差值年表与气候要素相关关系

    TMINC1-C3为 当年1—3月平均最低气温;TEMC7为当年7月平均气温;SUNP11为上年11月日照时数;WVPC2-C3为当年2—3月平均水汽压;RHP2-P11为上年2—11月相对湿度;PREP5为上年5月最大日降水量。下同。TMINC1-C3, average minimum temperature from January to March of the current year; TEMC7, average temperature in July of the current year; SUNP11, sunshine hours in November of the previous year; WVPC2-C3, average water vapor pressure from February to March of the current year; RHP2-P11, relative humidity from February to November of the previous year; PREP5, maximum daily precipitation in May of the previous year. The same below.

    Figure  3.  Relationship between difference chronology and climate factors

    图  4  各气候变量相对重要性

    Figure  4.  Relative importance of climate variables

    图  5  边际效应结果

    Figure  5.  Results of marginal effect

    表  1  年表统计特征及公共区间分析结果

    Table  1.   Descriptive statistics of tree ring width chronology and the results of common interval analysis

    年表统计量
    Chronological statistics (1932—2018)
    公共区间统计量
    Common interval statistics (1950—2016)
    平均敏感度
    Mean
    sensitivity
    标准差
    Standard
    deviation
    一阶自相关系数
    First-order
    autocorrelation
    coefficient
    平均相关系数
    Mean
    correlation
    coefficient
    树内相关系数
    Within-tree
    correlation
    coefficient
    树间相关系数
    Between-trees
    correlation
    coefficient
    信噪比
    Signal-to-noise
    ratio
    样本总体代表性
    Total
    representativeness
    of sample
    第1主成分
    解释方差量
    Variance explained
    by the first
    principal component
    0.1330.1750.4740.3630.5570.35924.460.96139.3%
    下载: 导出CSV
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  • 收稿日期:  2020-11-27
  • 修回日期:  2021-03-15
  • 网络出版日期:  2021-06-05
  • 刊出日期:  2021-07-25

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