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干旱胁迫环境中黄栌幼苗叶功能性状变异与产地地理−气候因子的关系

李金航 朱济友 Catherine MhaeB. Jandug 赵凯 徐程扬

李金航, 朱济友, Catherine MhaeB. Jandug, 赵凯, 徐程扬. 干旱胁迫环境中黄栌幼苗叶功能性状变异与产地地理−气候因子的关系[J]. 北京林业大学学报, 2020, 42(2): 68-78. doi: 10.12171/j.1000-1522.20190079
引用本文: 李金航, 朱济友, Catherine MhaeB. Jandug, 赵凯, 徐程扬. 干旱胁迫环境中黄栌幼苗叶功能性状变异与产地地理−气候因子的关系[J]. 北京林业大学学报, 2020, 42(2): 68-78. doi: 10.12171/j.1000-1522.20190079
Li Jinhang, Zhu Jiyou, Catherine Mhae B. Jandug, Zhao Kai, Xu Chengyang. Relationship between leaf functional trait variation of Cotinus coggygria seedling and location geographical-climatic factors under drought stress[J]. Journal of Beijing Forestry University, 2020, 42(2): 68-78. doi: 10.12171/j.1000-1522.20190079
Citation: Li Jinhang, Zhu Jiyou, Catherine Mhae B. Jandug, Zhao Kai, Xu Chengyang. Relationship between leaf functional trait variation of Cotinus coggygria seedling and location geographical-climatic factors under drought stress[J]. Journal of Beijing Forestry University, 2020, 42(2): 68-78. doi: 10.12171/j.1000-1522.20190079

干旱胁迫环境中黄栌幼苗叶功能性状变异与产地地理−气候因子的关系

doi: 10.12171/j.1000-1522.20190079
基金项目: 北京市教委科学研究与研究生培养共建项目
详细信息
    作者简介:

    李金航。主要研究方向:树木生理生态。Email:ljhbjfu@163.com 地址:100083 北京市海淀区清华东路35号北京林业大学林学院

    责任作者:

    徐程扬,教授,博士生导师。主要研究方向:城市林业,生态林与城市森林培育理论与技术。Email:cyxu@bjfu.edu.cn 地址:同上

Relationship between leaf functional trait variation of Cotinus coggygria seedling and location geographical-climatic factors under drought stress

  • 摘要: 目的分析持续干旱胁迫环境中不同产地黄栌幼苗叶功能性状的变异规律及差异,并探究产地地理−气候因子对叶功能性状变异的影响。方法采用田间模拟试验方法,选取来自5个产地的黄栌1年生幼苗作为供试材料,设置对照(CK,土壤田间持水量的75% ~ 80%)、中度胁迫(MS,土壤田间持水量的55% ~ 65%)和重度胁迫(SS,土壤田间持水量的35% ~ 45%)3个土壤水分含量梯度,分析干旱胁迫、产地及其二者的交互作用对叶功能性状的影响,并结合主成分分析(PCA)和冗余分析(RDA)分别研究产地分布与地理−气候因子的关系以及产地地理−气候因子对叶功能性状变异程度(TVD)的影响。结果(1)干旱胁迫对幼苗叶功能性状均具有显著影响。其中,SS环境中,叶绿素含量(LChl)、叶相对含水量(RWC)、比叶面积(SLA)和叶片面积比例(LAR)分别比对照低17.61%(P < 0.001)、3.71%(P < 0.001)、10.89%(P = 0.002)和17.22%(P = 0.001),叶干物质含量(LDMC)、叶组织密度(LD)分别比对照高9.04%(P < 0.001)和14.52%(P = 0.009)。(2)黄栌叶功能性状之间的相关性在干旱胁迫环境中具有增强的趋势。其中,SLA与LDMC和LD均呈极显著(P < 0.01)的负相关关系,LDMC和LD之间具有极显著(P < 0.01)的正相关关系,RWC与LChl(P < 0.01)、SLA(P < 0.01)和LAR(P < 0.05)呈极显著或显著的正相关关系。(3)干旱胁迫环境中不同产地叶功能性状具有显著差异。MS处理时,SLA(P = 0.002)、LChl(P = 0.025)和LD(P = 0.026)在产地间具有显著差异;SS处理时,LChl(P < 0.001)、LAR(P < 0.001)和RWC(P = 0.005)存在显著的产地差异。(4)来自北京延庆区幼苗的叶功能性状平均变异程度(所有性状变异程度的平均值)最大,为17.57%,而来自山西运城绛县幼苗的最小,为6.97%。(5)经RDA筛选,最干燥月份降水量(DMP,P = 0.002)、生长季月降水量平均差(GSPD,P = 0.008)、最热月份的最高气温(WMT,P = 0.016)和年平均降水量(ANP,P = 0.036)对幼苗TVD影响显著。其中,DMP与所有性状的变异程度之间均具有不同程度的负相关关系,但与LDMC和LD变异程度之间的负相关性更为显著,GSPD和ANP与SLA和LAR变异程度的负相关性较为显著,WMT与LChl变异程度的正相关性极为密切。结论黄栌叶功能性状在不同干旱胁迫环境中、不同产地间均具有显著差异。产地气候 (尤其是DMP、GSPD、WMT和ANP)是导致干旱逆境中不同产地黄栌叶功能性状发生遗传变异的重要原因。5产地中,山西运城绛县的DMP最高,GSPD和ANP较为适宜,WMT较低,且来自该产地的黄栌叶功能性状在干旱胁迫中的平均变异程度最小,因此较适合引种至华北地区的干旱区域。

     

  • 图  1  不同产地黄栌幼苗叶功能性状对持续干旱胁迫的响应

    CK. 对照;MS. 中度胁迫;SS. 重度胁迫。采用LSD检验,在α = 0.05水平上执行单因素方差分析,误差棒代表标准差。大写字母表示同一产地不同水分 处理之间的差异显著性,小写字母则表示同一水分处理时产地之间的差异显著性。CK, control; MS, moderate stress; SS, severe stress. One-way ANOVA was performed with Fisher LSD-test at α = 0.05 level. The error bars represent error of means. The capital letters indicate differences between water treatments in one location and the lowercase letters indicate differences among locations under the same treatment.

    Figure  1.  Responses of leaf functional traits of C. coggygria seedlings from different locations to continuous drought stress

    图  2  产地分布与地理−气候因子的关系

    Lat. 纬度Latitude;Lng. 经度Longitude;ANP. 年平均降水量Average annual precipitation;GSP. 生长季平均降水量Growing season precipitation;WMP. 最湿润月份降水量Precipitation of the wettest month;DMP. 最干燥月份降水量Precipitation of the driest month;GSPD. 生长季月降水量平均差Growing season mean monthly precipitation difference;RH. 平均相对湿度Mean relative humidity;ANT. 年平均气温Average annual temperature;GST. 生长季平均气温Mean temperature in growing season;GSTD. 生长季平均气温日较差 Mean daily temperature difference in growing season;WMT. 最热月份的最高气温Max. temperature of the warmest month;CMT. 最冷月份的最低气温Min. temperature of the coldest month

    Figure  2.  Relationship between location distribution and geographical-climatic factors

    图  3  黄栌幼苗叶功能性状在持续干旱胁迫环境中的平均变异程度

    Figure  3.  Average variation degree of leaf functional traits of C. coggygria seedlings under continuous drought stress

    图  4  不同产地黄栌幼苗叶功能性状在持续干旱胁迫环境中的变异程度

    Figure  4.  Variation degree of leaf functional traits of different C. coggygria locations under continuous drought stress

    图  5  叶功能性状的变异程度(TVD)与黄栌产地地理−气候因子之间关系的RDA分析

    Figure  5.  RDA analysis of the relationships between leaf functional trait variation degree (TVD) and geographical-climatic factors of C. coggygria locations

    表  1  黄栌5产地地理位置及气候特征

    Table  1.   Geographic locations and climatic characteristics of the five C. coggygria seedling collection counties

    产地
    Location
    产地
    编号
    Location
    code
    纬度
    Latitude
    经度
    Longitude
    年平均
    降水量
    Average
    annual
    precipitation/
    mm
    生长季平均
    降水量
    Mean precipitation
    in growing
    season/mm
    最湿润月份
    降水量
    Precipitation of the wettest month/mm
    最干燥月份
    降水量
    Precipitation of the driest month/mm
    生长季月降水
    量平均差
    Mean monthly precipitation difference in growing season/mm
    北京延庆区
    Yanqing District in Beijing
    L1 40°21′00″N 116°01′12″E 435 427.6 122.5 2.0 19.2
    河北石家庄赞皇县
    Zanhuang County of Shijiazhuang City in Hebei Province
    L2 37°39′00″N 114°22′48″E 508.9 497.6 123.2 2.6 28.8
    山东泰安高新区
    Gaoxin District of Tai’an City in Shandong Province
    L3 30°04′12″N 117°10′12″E 686.5 664 205.9 5.3 37.6
    山西运城绛县
    Jiang County of Yuncheng City in Shanxi Province
    L4 35°28′48″N 111°34′12″E 573.5 550.5 108.6 6.3 28.3
    河南三门峡陕州区
    Shanzhou District of Sanmenxia City in Henan Province
    L5 34°43′12″N 111°06′00″E 549.6 532.1 107.2 4.8 27.0
    产地
    Location
    产地
    编号
    Location
    code
    平均相
    对湿度
    Mean relative
    humidity/%
    年平均气温
    Average annual temperature/℃
    生长季平
    均气温
    Mean temperature in growing season/℃
    生长季平均
    气温日较差
    Mean daily temperature difference in growing season/℃
    最热月份的
    最高气温
    Max. temperature of the warmest month/℃
    最冷月份的
    最低气温
    Min. temperature of the coldest month/℃
    北京延庆区
    Yanqing District in Beijing
    L1 55 9.7 14.7 11.9 39.2 − 26.2
    河北石家庄赞皇县
    Zanhuang County of Shijiazhuang City in Hebei Province
    L2 60 13.6 18.2 11.1 43.4 − 16.2
    山东泰安高新区
    Gaoxin District of Tai’an City in Shandong Province
    L3 66 13.3 17.7 11.2 42.1 − 20.7
    山西运城绛县
    Jiang County of Yuncheng City in Shanxi Province
    L4 61 11.9 16.3 10.2 39.4 − 20.5
    河南三门峡陕州区
    Shanzhou District of Sanmenxia City in Henan Province
    L5 61 14.4 18.6 10.3 41.4 − 12.8
    下载: 导出CSV

    表  2  干旱胁迫、产地及其交互作用对黄栌幼苗叶功能性状影响的方差分析

    Table  2.   ANOVA of the influences of drought stress and location on the leaf functional traits of C. coggygria seedlings

    变异来源 Source of variationdf叶绿素含量
    Leaf chlorophyll content (LChl)
    叶相对含水量
    Leaf relative water content (RWC)
    叶干物质含量
    Leaf dry matter content (LDMC)
    FPFPFP
    干旱胁迫 Drought stress232.43 0.00026.10 0.00030.53 0.000
    产地 Location422.64 0.0005.830.0011.820.152
    干旱胁迫 × 产地
    Drought stress × location
    81.010.4495.340.0031.350.258
    变异来源 Source of variationdf叶组织密度
    Leaf tissue density (LD)
    比叶面积
    Specific leaf area (SLA)
    叶面积比例
    Leaf area ratio (LAR)
    FPFPFP
    干旱胁迫 Drought stress23.790.0347.010.0027.980.000
    产地 Location42.620.0553.010.0255.170.001
    干旱胁迫 × 产地
    Drought stress × location
    81.220.3462.470.0223.040.006
    下载: 导出CSV

    表  3  水分充足环境和干旱胁迫环境中黄栌幼苗叶功能性状之间的Pearson相关系数

    Table  3.   Pearson’s correlation coefficients among leaf functional traits of C. coggygria in well-irrigated and drought stress environments

    叶功能性状 Leaf functional trait叶绿素含量 LChl叶相对含水量 RWC叶干物质含量 LDMC叶组织密度 LD比叶面积 SLA
    对照处理 CK
     叶相对含水量 RWC0.353
     叶干物质含量 LDMC− 0.037− 0.102
     叶组织密度 LD− 0.357− 0.3120.286
     比叶面积 SLA0.1400.017− 0.080− 0.227
     叶面积比例 LAR0.1850.220− 0.111− 0.0190.194
    干旱胁迫 Drought stress
     叶相对含水量 RWC0.316**
     叶干物质含量 LDMC− 0.424**− 0.455**
     叶组织密度 LD− 0.481**− 0.321**0.467**
     比叶面积 SLA0.1020.337**− 0.398**− 0.325**
     叶面积比例 LAR0.1020.280*− 0.320**− 0.330**0.371**
    注:**表示P < 0.01,*表示P < 0.05。Notes: ** and * represent P < 0.01 and P < 0.05, respectively.
    下载: 导出CSV

    表  4  RDA筛选出的地理−气候因子对叶片功能性状变异程度解释的贡献率(从大到小)

    Table  4.   Contribution of the explanation of the selected geographical-climatic factors in RDA analysis to leaf functional trait variation degree (from high to low)

    地理−气候因子 Geographical-climatic factors贡献率 Contribution/%FP
    最干燥月份降水量 Precipitation of the driest month (DMP)41.319.80.002
    生长季月降水量平均差 Growing season mean monthly precipitation difference (GSPD)38.712.10.008
    最热月份的最高气温 Max. temperature of the warmest month (WMT)17.4 6.30.016
    年平均降水量 Average annual precipitation (ANP) 2.6 2.10.036
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-02-25
  • 修回日期:  2019-05-05
  • 网络出版日期:  2019-12-02
  • 刊出日期:  2020-03-03

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