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浙江天童常绿植物当年生与往年生叶片性状的变异与关联
引用本文:黄海侠,杨晓东,孙宝伟,张志浩,阎恩荣. 浙江天童常绿植物当年生与往年生叶片性状的变异与关联[J]. 植物生态学报, 2013, 37(10): 912-921. DOI: 10.3724/SP.J.1258.2013.00094
作者姓名:黄海侠  杨晓东  孙宝伟  张志浩  阎恩荣
作者单位:华东师范大学环境科学系, 上海 200062
浙江天童森林生态系统国家野外科学观测研究站, 浙江宁波 315114
基金项目:国家自然科学基金(31070383);国家自然科学基金(31270-475)
摘    要:植物叶片性状随叶龄的变化是植物生活史策略的体现, 反映了植物叶片的物质投资和分配方式。该研究通过在个体和物种2个水平, 比较浙江天童1 hm 2样地内常绿阔叶树种的平均叶面积(MLA)、比叶面积(SLA)和叶片干物质含量(LDMC)在当年生和往年生叶片间的差异和关联, 探究叶片物质分配策略在异龄叶间的变化, 并分析叶龄对植物叶片性状, 特别是叶片面积建成消耗的影响。结果显示: 1)在个体和物种水平上, MLA变异系数最大(个体: 79.5%; 物种: 66.5%), SLA次之(个体: 28.1%; 物种: 24.7%), LDMC较低(个体: 17.0%, 物种: 14.1%); 当年生叶片MLA、LDMCSLA的变异系数均高于往年生叶片; 2)往年生叶MLA显著大于当年生叶(t = -38.53, p < 0.001), 往年生叶SLA显著小于当年生叶(t = 45.30, p < 0.001), 往年生叶LDMC显著大于当年生叶(t = -9.71, p < 0.001); 3)在个体水平, 当年生叶片MLA、SLALDMC值分别解释了往年生叶片MLA、SLALDMC变异的86%、48%和41%; 在物种水平, 当年生叶片MLA、SLALDMC值分别解释了往年生叶片MLA、SLALDMC变异的97%、83%和85%; 4) SLA在异龄叶间的变化表明, 与往年生叶片相比, 投资相同干物质, 当年生叶片可形成较大的叶面积, 其叶片面积建成消耗较小。研究认为, 植物叶性状在异龄叶间具有较大的变异性和关联性, 叶面积形成过程中生物量建成与消耗的协调可能影响植物叶片的发育。

关 键 词:叶龄  叶建成消耗  干物质含量  平均叶面积  资源分配策略  比叶面积  
收稿时间:2013-04-15

Variability and association of leaf traits between current-year and former-year leaves in evergreen trees in Tiantong,Zhejiang, China
HUANG Hai-Xia,YANG Xiao-Dong,SUN Bao-Wei,ZHANG Zhi-Hao,YAN En-Rong. Variability and association of leaf traits between current-year and former-year leaves in evergreen trees in Tiantong,Zhejiang, China[J]. Acta Phytoecologica Sinica, 2013, 37(10): 912-921. DOI: 10.3724/SP.J.1258.2013.00094
Authors:HUANG Hai-Xia  YANG Xiao-Dong  SUN Bao-Wei  ZHANG Zhi-Hao  YAN En-Rong
Affiliation:Department of Environment Science, East China Normal University, Shanghai 200062, China
Tiantong National Forest Ecosystem Observation and Research Station, Ningbo, Zhejiang 315114, China
Abstract:Aims Variation in leaf traits with changing leaf age denotes plant life history strategy and reflects biomass allocation pattern in plant leaves. Our objective was to explore variability and correlation of leaf traits between current-year and former-year leaves for evergreen broad-leaved trees, in order to reveal effects of leaf age on the pattern of construction and cost during development of leaf area.
Methods Our one hectare study site is located in Tiantong National Forest Park (29°52′ N, 121°39′ E), Zhejiang Province. Three key functional traits (mean leaf area (MLA), specific leaf area (SLA) and leaf dry matter content (LDMC)) in each of current-year leaves and former-year leaves were measured for 2277 evergreen trees belonging to 41 species. Variability and correlations for each of three leaf traits were compared between current-year and former-year leaves at both individual and species levels.
Important findings At both individual and species levels, variability coefficients (i.e., CV) were highest in MLA (individual: 79.5%; species: 66.5%), intermediate in SLA (individual: 28.1%; species: 24.7%) and lowest in LDMC (individual: 17.0%; species: 14.1%). Variability coefficients among the three leaf traits were greater in current-year leaves than in former-year leaves. Former-year leaves had significantly greater MLA (t = -38.53, p < 0.001) and LDMC (t = -9.71, p < 0.001), but lower SLA (t = 45.30, p < 0.001) than current-year leaves. At the individual level, the values for MLA, SLA and LDMC in current-year leaves explained 86%, 48% and 41% of the total variation for MLA, SLA and LDMC in former-year leaves. More significantly, at the species level 97%, 83% and 85% of the total variation in each of MLA, SLA and LDMC for former-year leaves resulted from variability of MLA, SLA and LDMC from current-year leaves. Variation in SLA between differently aged leaves demonstrated that, at a given unit investment of biomass, a relatively larger leaf area can be structured by current-year leaves than by former-year leaves, thus having a low cost in constructing leaf area for current-year leaves. In conclusion, plant leaf traits vary and connect significantly with change of leaf age. Trade-offs between biomass construction and cost in leaf area production might affect plant leaf development.
Keywords:leaf age,  leaf construction cost,  leaf dry mass content,  mean leaf area,  resource allocation strategy,  specific leaf area
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