论文部分内容阅读
我们通过采集中国东部南北样带(NSTEC)上112个样点的102种植物叶片样品,分析了植物叶片氮浓度对植被功能型(PFTs)以及环境因素的响应特征。研究结果表明:(1)植物叶片氮浓度均值为17.7mgg-1,最大值和最小值分别出现在落叶阔叶植物和常绿针叶植物中。对乔木而言,叶片氮浓度表现为落叶植物>常绿植物,阔叶植物>针叶植物;乔木和灌木的叶片氮浓度显著高于草本植物,而乔木和灌木之间则无显著差异。(2)叶片氮浓度与年均温度(MAT)呈现凸型二次曲线关系,与年均降水量(MAP)则呈现显著的线性负相关关系,与土壤氮素浓度(Nsoil)则线性正相关,并且这种关系并不随着植被功能型的改变而改变。(3)PFTs,气候和Nsoil共同解释植物叶片氮浓度空间格局变异的46.1%,其中PFTs,气候和Nsoil可分别独立解释植物叶片氮浓度空间格局变异的15.6%,2.3%,4.7%。该研究结果表明,气候和土壤氮素对植物叶片氮浓度的影响主要是通过作用于生态系统中的物种组成,而非直接作用实现的。这种基于较大区域尺度上的野外观测分析有助于我们准确的理解植被功能型和环境因素对叶片氮浓度变异的影响机制。
We collected 102 plant leaf samples from 112 sampling sites in the NSTEC to analyze the response characteristics of plant leaf nitrogen concentration to vegetation functional types (PFTs) and environmental factors. The results showed that: (1) The average nitrogen concentration of plant leaves was 17.7mgg-1, the maximum and minimum values appeared in deciduous broad-leaved and evergreen coniferous plants respectively. For arbor, the leaf nitrogen concentration showed deciduous> evergreen> broadleaf> coniferous; the leaf nitrogen concentrations of trees and shrubs were significantly higher than those of herbaceous plants, but there was no significant difference between trees and shrubs. (2) The leaf nitrogen concentration showed a convex conic relationship with the annual average temperature (MAT), showing a significant linear negative correlation with annual mean precipitation (MAP) and a linear positive correlation with soil nitrogen concentration (Nsoil) , And this relationship does not change with vegetation functional changes. (3) PFTs, climate and Nsoil jointly explained 46.1% of the variation of spatial pattern of nitrogen concentration in plant leaves. PFTs, climate and Nsoil could independently explain 15.6%, 2.3% and 4.7% of spatial variability of plant leaf nitrogen concentration. The results of this study indicate that the effects of climate and soil nitrogen on plant leaf nitrogen concentration are mainly caused by the species composition acting on the ecosystem rather than by direct action. This field-based analysis based on large regional scales helps us to understand accurately the mechanism of vegetation functional and environmental factors on leaf nitrogen concentration variation.