杉木叶形态特征与叶面积估算模型
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摘要
植物叶片是碳水交换和能量平衡过程最重要的场所,是农林生产经营中的模型估算以及物种结构变异-功能适应机制分析的关键参考量。采用游标卡尺和手持叶面积仪,测量杉木(Cunninghamia lanceolata)单叶叶长(LL)、最大叶宽(LW_(max))、最大叶厚(LT_(max))3个直测指标,和叶面积(LA)、平均叶宽(LW_(mean))、平均叶厚(LT_(mean))、叶延长率(LE)和叶周长(LP)5个间接转算指标。分析8个形态学指标的统计分布及其相关性,用多变量线性回归模型和非线性回归指数模型对7个形态学指标和杉木单叶叶面积进行拟合,结果表明:杉木单叶面积大部分值(95%CI)分布在0.758—0.836 cm~2,其叶面积的变异程度最大(CV=0.513),叶长、叶宽与叶面积相关性达到极显著(r=0.896,0.682)。拟合LA的多元线性模型为:Y=-0.388+0.165X_1-0.023X_2+1.453X_3(R~2=0.981,SE=0.053),X_1—X_3分别为LP、LE、LW_(mean)。从简便性上考虑,LL的单变量指数模型适合对LA进行估算:LA=0.1×(1+LL)~(1.398)(R~2=0.77,!~2=0.39)。研究结果为准确估测其他叶片功能性状指标提供了方法,为杉木叶面积估算模型提供了基础数据。
Leaves are considered a significant site of carbon-water exchange and the energy-balance process. The characteristics of leaf response to the external environment,functional traits,coordination mechanisms,and trade-off strategies,as well as the structure and variation of leaves,have recently attracted huge interest. Further,leaf size could directly affect their capacity for light interception and carbon acquisition. Leaf area( LA) and related leaf traits such as specific leaf area( SLA),leaf area index( LAI),and normalized difference vegetation index( NDVI) are the key indicators in crop breeding,agroforestry production and management,model estimation,and species structure variation and functional adaptation mechanisms. The leaf traits are based on leaf area and influenced by leaf morphology and size,and determination of leaf area is the basis to discuss plant photosynthetic production and the physiological-ecological process.However,the uncertainty of needle leaf area,which is due to the difficulty of measurement,could be a hindrance toefficient production and management,effective risk assessment,and development of correlational research. Thus,it is significant to explore the appropriate measurement methods to obtain accurate values of leaf area. There is lack of comparative studies between different methods of measuring leaf area,resulting in inconsistency of associated concepts and definitions. Presently,instrument-based measurement methods of LA are pervasive and prevalent,but lack calibration by artificial measurements. Additionally,studies with regression estimation models based on plant leaf area and morphometric characteristics are concentrated on agronomy products such as crops and fruit and some broadleaf species. Research that centers on needle leaf area estimation models based on leaf morphological characteristics is still lacking. This study used Cunninghamia lanceolata,a common pioneer tree species in southern China,to measure 3 leaf morphometric characteristics( leaf length,leaf maximum width,leaf maximum thickness) and indirectly calculate 5 indicators( leaf mean width,leaf mean thickness,leaf area,leaf elongation,leaf perimeter) using Vernier calipers and portable leaf area meter. We present the statistical distribution and correlation analysis of the 8 morphological characteristics,fitting the leaf area with the 7 other indicators in multivariate linear regression models and nonlinear regression index models. We find that( 1) by manual measurement,the credible simple leaf area of Chinese fir ranges from 0. 758 cm~2 to 0. 836 cm~2,and shows a maximum coefficient of variation( CV = 0.513);( 2) leaf area significantly correlates with leaf length and width( r = 0.896,0.682);( 3) the multivariate linear regression model of leaf length and width that is most accurate: Y=-0.388 + 0.165 X_1-0.023 X_2+ 1.453 X~3( R~2= 0.981,SE = 0.053),where X_1,X_2,and X_3 are leaf perimeter,leaf elongation,and leaf mean width,respectively. From the point of view of simplicity,leaf length( LL) of a single variable index model is more suited for a leaf area estimation model: LA = 0.1 ×( 1 + LL)~(1.398)( R~2= 0.77),X~2= 0.39. The results demonstrated that this is a method of instrument calibration and accurate estimation of other leaf traits of Chinese fir,providing data about single leaf area and improving the model accuracy and stability for Chinese fir leaf area estimation. Moreover,this approach is effective in providing data to support advice to plantation management,and for verification and improvement of leaf morphology and leaf functional traits of other species.
Leaves are considered a significant site of carbon-water exchange and the energy-balance process. The characteristics of leaf response to the external environment,functional traits,coordination mechanisms,and trade-off strategies,as well as the structure and variation of leaves,have recently attracted huge interest. Further,leaf size could directly affect their capacity for light interception and carbon acquisition. Leaf area( LA) and related leaf traits such as specific leaf area( SLA),leaf area index( LAI),and normalized difference vegetation index( NDVI) are the key indicators in crop breeding,agroforestry production and management,model estimation,and species structure variation and functional adaptation mechanisms. The leaf traits are based on leaf area and influenced by leaf morphology and size,and determination of leaf area is the basis to discuss plant photosynthetic production and the physiological-ecological process.However,the uncertainty of needle leaf area,which is due to the difficulty of measurement,could be a hindrance toefficient production and management,effective risk assessment,and development of correlational research. Thus,it is significant to explore the appropriate measurement methods to obtain accurate values of leaf area. There is lack of comparative studies between different methods of measuring leaf area,resulting in inconsistency of associated concepts and definitions. Presently,instrument-based measurement methods of LA are pervasive and prevalent,but lack calibration by artificial measurements. Additionally,studies with regression estimation models based on plant leaf area and morphometric characteristics are concentrated on agronomy products such as crops and fruit and some broadleaf species. Research that centers on needle leaf area estimation models based on leaf morphological characteristics is still lacking. This study used Cunninghamia lanceolata,a common pioneer tree species in southern China,to measure 3 leaf morphometric characteristics( leaf length,leaf maximum width,leaf maximum thickness) and indirectly calculate 5 indicators( leaf mean width,leaf mean thickness,leaf area,leaf elongation,leaf perimeter) using Vernier calipers and portable leaf area meter. We present the statistical distribution and correlation analysis of the 8 morphological characteristics,fitting the leaf area with the 7 other indicators in multivariate linear regression models and nonlinear regression index models. We find that( 1) by manual measurement,the credible simple leaf area of Chinese fir ranges from 0. 758 cm~2 to 0. 836 cm~2,and shows a maximum coefficient of variation( CV = 0.513);( 2) leaf area significantly correlates with leaf length and width( r = 0.896,0.682);( 3) the multivariate linear regression model of leaf length and width that is most accurate: Y=-0.388 + 0.165 X_1-0.023 X_2+ 1.453 X~3( R~2= 0.981,SE = 0.053),where X_1,X_2,and X_3 are leaf perimeter,leaf elongation,and leaf mean width,respectively. From the point of view of simplicity,leaf length( LL) of a single variable index model is more suited for a leaf area estimation model: LA = 0.1 ×( 1 + LL)~(1.398)( R~2= 0.77),X~2= 0.39. The results demonstrated that this is a method of instrument calibration and accurate estimation of other leaf traits of Chinese fir,providing data about single leaf area and improving the model accuracy and stability for Chinese fir leaf area estimation. Moreover,this approach is effective in providing data to support advice to plantation management,and for verification and improvement of leaf morphology and leaf functional traits of other species.
引文
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