Publication
 

小兴安岭2种阔叶树种叶面积和叶干重经验模型的构建 / Construction of empirical models for leaf area and leaf dry mass of two broadleaf species in Xiaoxing'an Mountains, China

 快捷、准确地测定植被的叶面积(LA)和叶干质量(LM)是叶型几何学和植物功能学的基础工作之一,不仅对研究叶形态学和生物量估计有重要意义,而且对深入了解植被对气候变化的响应机制至关重要.本研究以温带落叶阔叶树种裂叶榆和青楷槭为研究对象,分别构建叶面积、叶干质量与叶片结构参数(如叶长L,叶宽W)间的经验模型,阐明经验模型的类型(线性或非线性)及最优自变量的选择是否存在种间差异,最后评估经验模型的预测精度.结果表明:预测裂叶榆和青楷槭叶面积的最优经验模型分别为LA=0.614L1.468W0.464和LA=0.865(LW)0.933;预测叶干质量的最优经验模型分别为LM=0.003L1.537W0.365和LM=0.001L2.318.利用最优经验模型预测裂叶榆和青楷槭叶面积的精度分别为88%和96%,预测叶干质量的精度分别为73%和83%.基于预测叶面积和叶干质量的经验模型,可在非破坏性条件下间接地测定2种树种的比叶面积,预测精度分别为83%和90%.研究结果可为高效测定叶片水平上的叶性状及其动态变化提供技术支持

Rapid and accurate measurement of leaf area (LA) and leaf dry mass (LM) is one of the basic requirement for leaf geometry and plant functional studies. It is important not only for studying leaf morphology and biomass estimation, but also for understanding the response mechanism of vegetation to climate change. In this study, we took two temperate deciduous broad-leaved tree species, Ulmus laciniata and Acer tegmentosum, as the study objects, constructed empirical models between LA or LM and leaf structure parameters (e.g., leaf length, L; leaf width, W) to reveal the interspecific variability in the selection of empirical model formats (linear or non-linear) and independent variables. We evaluated the forecast accuracy of these empirical models in predicting LA and LM for each species. The results showed that the optimal empirical models for predicting LA were LA=0.614L1.468W0.464 and LA=0.865(LW)0.933, and for predicting LM were LM=0.003L1.537W0.365and LM=0.001L2.318 for U. laciniata and A. tegmentosum, respectively. The forecast accuracies of empirical models in predicting LA were 88% and 96%, and for LM were 73% and 83% for U. laciniata and A. tegmentosum, respectively. In addition, based on the empirical models for predicting LA and LM, the specific leaf area also could be indirectly measured under non-destructive conditions, with the forecast accuracies being 83% and 90% for U. laciniata and A. tegmentosum, respectively. These results provide a technical support for the efficient measurement of leaf traits and their dynamics.

Authors: 
王彦君, 金光泽, 刘志理 / Y.J. Wang, G.Z. Jin, & Z.L. Liu
Journal: 
应用生态学报 / Journal of Applied Ecology
Year: 
2018
Volume: 
29
Issue: 
6
Pages: 
1745-1752
DOI: 
10.13287/j.1001-9332.201806.014