杉木叶形态特征与叶面积估算模型

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。     

Specific leaf area estimation model building based on leaf dry matter content of Cunninghamia lanceolata

随着叶片功能性状研究的不断深入, 通过简单易测量的叶片指标, 同时探究植物生活史权衡对策和估算林分生产力的研究需求日益增长, 例如叶干质量比(LDMC)和比叶面积(SLA)的相互转换。杉木(Cunninghamia lanceolata)是亚热带重要的常绿针叶树种, 基于LDMC对杉木SLA进行估算, 能够为核算SLA提供途径, 为机理解释和生产估算构建连接途径, 为小区域到大尺度、精算到估算搭建桥梁。该研究在湖南会同和河南信阳两个杉木生长区, 对处于不同小生境(坡向、坡位和冠层深度)以及不同生活史(林龄和叶龄)的叶片进行抽样和采集, 通过测得不同叶龄的单叶LDMC和SLA, 初步探究在不同因子下两个性状值的分布差异, 进一步基于LDMC构建SLA估算模型并讨论以叶龄为差分因子对模型的影响。结果表明: 1)杉木SLA平均值为(103.15 ± 69.54) cm ²·g ^-1, LDMC为0.39 ± 0.11; 2)杉木LDMC和SLA可用非线性模型进行估算, 模型符合估算要求; 3)其中一年生叶的拟合效果最好, 老叶(大于二年生叶)的拟合优度较低, 老叶较低的SLA (52.28-75.74 cm ²·g ^-1)可能暗示LDMC的变化保持相对独立性。该研究基于杉木LDMC的SLA估算模型可信且有效, 且不同叶龄对LDMC和SLA的影响可能预示着杉木叶片的响应敏感性和生活史权衡策略。     

千烟洲针叶林的比叶面积及叶面积指数

根据实测数据计算了湿地松(Pinus elliotii)、马尾松(P. massoniana) 和杉木(Cunninghamia lanceolata)不同年龄、不同类型叶片的生物量和比叶面积,并结合样地调查数据和相对生长方程计算了中国科学院千烟洲试验站20年生湿地松林、马尾松林、杉木林和针叶混交林的叶面积指数。根据拟合结果,选择如下方程计算3个树种的叶生物量:湿地松W=12.074 1D^{2.151 5}、马尾松W=6.972 7D^{2.197 3}和杉木W=5.261 9D^{2.302 7}。湿地松林的叶生物量(0.822 kg·m^-2)最大,其次为针叶混交林(0.679 kg·m^-2),马尾松林和杉木林相差不大(分别为林0.528和0.572 kg·m^-2)。不同树种、不同年龄、不同类型叶片的比叶面积比较发现,新叶的比叶面积大于老叶,三针一束叶的比叶面积略大于两针一束叶,马尾松的平均半比表面积(8.62 m²·kg^-1)大于湿地松(6.04 m²·kg^-1)和杉木(7.91 m²·kg^-1)。胸径与单木叶片半表面积之间的经验方程为:湿地松LA=0.073D^{2.151 5}、马尾松LA=0.060D^{2.197 3}和杉木LA=0.042D^{2.302 7}。据此计算湿地松林的叶面积指数为5.03,马尾松林和杉木林为4.31,针叶混交林为4.77,该结果比利用CI-110植被冠层数字图像仪测得的结果偏大。     

中国温带典型森林植物比叶面积的空间格局及其影响因素

比叶面积(SLA)能够反映植物自身生长对策、对光能的捕获能力、对外界环境变化的适应和对可利用资源的分配策略,对植物的生境适应状况和群落的自然演替程度也起到重要的指示作用。为了深入了解温带森林植物SLA随空间变化的变异特征及其影响因素,跨越1200 km选取中国东北部12个典型温带森林(寒温带兴安落叶松林、温带红松针阔混交林和暖温带落叶阔叶栎林),通过对样地内物种进行系统性的调查,分析了植物SLA在空间上的变化规律及环境因素的影响效应。结果显示：中国温带森林植物SLA范围为2.02—99.65 m~2/kg(均值为34.18 m~2/kg),其中乔木SLA范围为2.02—58.74 m~2/kg(均值为21.32 m~2/kg),灌木SLA范围为2.88—99.65 m~2/kg(均值为31.60 m~2/kg),草本SLA范围为4.66—98.53 m~2/kg(均值为38.75 m~2/kg)。SLA在不同森林类型之间差异显著,具体表现为：温带红松针阔混交林>暖温带落叶阔叶栎林>寒温带兴安落叶松林。SLA受到气候因素和土壤因素的影响,其中随着年均降水、土壤碳氮含量的增加显...     

基于地理种源的刨花楠苗木比叶面积与叶片化学计量学关系

探讨植物比叶面积(SLA)与叶片碳(C)、氮(N)、磷(P)化学计量学关系,能够反映植物为获取最大光合生产所采取的内部调控机制,共同体现植物的适应策略。利用生长于同一土壤与气候环境中培育的刨花楠(Machilus pauhoi)1年生苗木,对其SLA与叶片C、N、P含量进行测定,并对SLA与叶片C、N、P化学计量学特征及其与种源地环境因子的关系进行分析。结果表明:(1)叶片养分含量的变异系数大小排序为CNP;SLA与叶片N、P含量呈显著的正相关,与叶片C∶N及C∶P呈极显著的负相关。(2)SLA与经度、年均温、年降水量呈显著负相关;叶片C、N、P含量也受种源地环境因子影响,其中以海拔最为重要。研究结果有助于理解刨花楠苗木的生存适应对策,对探究刨花楠对养分的资源利用效率等具有重要意义。     

桂北岩溶区青冈栎-青檀群落植物叶片比叶面积研究

为揭示岩溶地区植物叶片比叶面积变化规律和叶片形态之间的相关关系,研究了桂北岩溶区青冈栎-青檀群落的叶片长/宽(LL/LW)、叶片厚度(LT)和比叶面积(SLA)及其之间的关系。结果表明:群落中常绿树种的LL/LW和LT显著高于落叶树种,而常绿树种的SLA显著低于落叶树种;乔木和灌木之间的LL/LW存在显著差异,但SLA和LT不存在显著差异。总体上看,SLA与LL/LW、LT之间是显著负相关关系,SLA随着LL/LW、LT的变大而逐渐减小。但LT与SLA负相关趋势比LL/LW与SLA的明显。因此,LT比LL/LW对叶片SLA的影响大,其明显影响了叶片的SLA。SLA的大小是衡量叶片获取光照能力的指标,因此岩溶区植物较厚的叶片对光照的获取能力具有较大的影响,并可导致光合作用效率的降低。     

三江平原湿地植被叶面积指数遥感估算模型

利用中巴资源卫星CBERS-02影像提取的归一化植被指数(NDVI)和同期野外实测的叶面积指数(LAI)数据,分析了三江平原洪河自然保护区草甸、沼泽植被、灌丛和岛状林4种湿地植被及样本总体的NDVI与LAI之间的相关关系,建立了NDVI与不同湿地植被类型叶面积指数间的线性和非线性回归模型,并制作完成洪河自然保护区LAI空间分布图.结果表明,整个研究区样本总体的LAI估算效果不太理想,其NDVI与LAI的相关性仅为0.523;将研究区分为草甸、沼泽、灌丛和岛状林4种湿地植被类型,NDVI与各植被型LAI的相关性和估算效果均有很大程度的提高,所建立的LAI遥感反演模型以三次曲线回归方程拟合精度最高,R2分别达到0.723、0.588、0.837、0.720.以上结果表明,结合地面实测数据并基于遥感植被分类的基础上,CBERS-02遥感影像可用于较大区域内湿地植被生理参数的反演研究.     

杉木人工林生物量估算模型的选择

采用11种形式的生物量模型,分别对杉木幼龄林（7年生）、中龄林(16年生)、成熟林(28年生)和不分林龄的单木各器官和全株生物量进行拟合,共得到生物量估算模型308个.结果表明: 11种生物量模型均能较好地模拟杉木单木生物量,其中幂函数模型的拟合效果最优,其次为指数模型,然后为多项式模型;共选出估算杉木幼龄林、中龄林和成熟林各器官和全株生物量的最优模型21个（包括18个器官模型、3个全株模型）,不分林龄的杉木单木各生物量的最优模型7个（包括6个器官模型、1个全株模型）,均为幂函数模型;不同林龄的杉木单木生物量最优模型的通用性较差,而不分龄林的杉木单木生物量最优模型具有一定的通用性,精度较高,可用于估算不同林龄的杉木单木生物量.应用福建邵武杉木单木生物量模型对江西28年生的杉木成熟林单木各生物量的预测结果显示,不分林龄的大样本生物量模型精度较高,可在较大范围内应用,而区域小样本模型仅限于在区域小范围内应用.     

小兴安岭2种阔叶树种叶面积和叶干质量经验模型的构建

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=0.614L^1.468W^0.464和LA=0.865(LW)^0.933;预测叶干质量的最优经验模型分别为LM=0.003L^1.537W^0.365和LM=0.001L^2.318.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.     

河北固城夏玉米比叶面积对水分梯度的响应

基于河北固城农试站2013-2015年夏玉米田间水分控制试验,研究了夏玉米比叶面积(SLA)随发育期的变化趋势,并分主要发育时段探讨了SLA与水分梯度的定量关系。结果表明,从七叶期开始夏玉米SLA随发育进程的推进总体呈下降趋势,七叶期至成熟期SLA变化范围平均为14.6-34.9m~2/kg。尽管干旱胁迫会明显降低夏玉米地上绿叶面积和干重,但却使SLA表现出"补偿性"增大,用于弥补干旱胁迫导致光合产物不足引起的叶片扩张乏力。夏玉米出苗-拔节期、抽雄-成熟期土壤相对湿度(θ)每降低1%,SLA分别上升0.45m~2/kg和0.07m~2/kg,表明出苗-拔节期夏玉米对干旱的"适应"能力更强;而拔节-抽雄期SLA与θ的关系较为复杂,表现为先增大后减小的抛物线型。     

不同沙丘生境主要植物比叶面积和叶干物质含量的比较

研究了生长在不同沙丘生境中 (流动沙丘 ,半固定沙丘和固定沙丘 ) 2 0个植物种 (10个 1年生植物种和 10个多年生植物种 )的比叶面积 (SL A)和叶干物质含量 (L DMC)的变化 ,并且分析了各个沙丘生境的土壤养分特征。结果表明 ,各个植物种的平均 SL A和 L DMC在植物种之间差异显著 ;多数在两种或 3种沙丘生境均有分布的植物其 SL A在不同沙丘生境之间差异显著 ,但是仅有 6个植物种的 L DMC在不同沙丘生境之间表现出差异 (p<0 .0 5 )。与许多研究结果类似 ,1年生植物的 SL A显著大于多年生植物的 SL A,而且两者之间 L DMC存在一定的差异。 1年生植物 SL A和 L DMC之间相关性不显著 ,但多年生植物SL A和 L DMC之间呈显著负相关。综合所有 2 0个植物种可以发现 ,SL A增大时 ,L DMC有下降的趋势     

Specific leaf area and dry matter content estimate thickness in laminar leaves

BACKGROUND AND AIMS: Leaf thickness plays an important role in leaf and plant functioning, and relates to a species' strategy of resource acquisition and use. As such, it has been widely used for screening purposes in crop science and community ecology. However, since its measurement is not straightforward, a number of estimates have been proposed. Here, the validity of the (SLA x LDMC)(-1) product is tested to estimate leaf thickness, where SLA is the specific leaf area (leaf area/dry mass) and LDMC is the leaf dry matter content (leaf dry mass/fresh mass). SLA and LDMC are two leaf traits that are both more easily measurable and often reported in the literature. METHODS: The relationship between leaf thickness (LT) and (SLA x LDMC)(-1) was tested in two analyses of covariance using 11 datasets (three original and eight published) for a total number of 1039 data points, corresponding to a wide range of growth forms growing in contrasted environments in four continents. KEY RESULTS AND CONCLUSIONS: The overall slope and intercept of the relationship were not significantly different from one and zero, respectively, and the residual standard error was 0.11. Only two of the eight datasets displayed a significant difference in the intercepts, and the only significant difference among the most represented growth forms was for trees. LT can therefore be estimated by (SLA x LDMC)(-1), allowing leaf thickness to be derived from easily and widely measured leaf traits.     

不同模拟增雨下白刺比叶面积和叶干物质含量的比较

以荒漠生态系统典型植物白刺(Nitraria tangutorum)为研究对象,根据内蒙古磴口多年平均降水量和植物生长规律,设计两个增雨时段(生长季前期与生长季后期),每个增雨时段设置两个增雨梯度(72.5mm/a(50%)、145mm/a(100%)),对天然白刺灌丛进行增雨实验,研究了不同模拟增雨处理下2012年与2013年生长季白刺叶片的比叶面积(SLA)与叶干物质含量(LDMC)的变化。结果表明,增雨处理可以增加白刺叶片的SLA及LDMC,同时期增雨100%处理对SLA及LDMC的影响大于50%处理,但同时期增雨的两个处理之间无显著差异;白刺叶片SLA在生长季前期对水分响应明显,LDMC则在生长季后期对水分反应敏感;相同增雨处理,2012年白刺叶片SLA及LDMC的净增加值高于2013年;SLA与LDMC在2012年呈显著负相关,在2013年虽呈负相关,但相关性不显著。在未来降雨增加的背景下,荒漠植物白刺叶片SLA与LDMC对增雨具有较强的协调适应能力,在不同生长季节可以通过改变不同的叶片性状来适应环境变化。     

Simulation of leaf area development based on dry matter partitioning and specific leaf area for cut chrysanthemum

This work aims to predict time courses of leaf area index (LAI) based on dry matter partitioning into the leaves and on specific leaf area of newly formed leaf biomass (SLA(n)) for year-round cut chrysanthemum crops. In five glasshouse experiments, each consisting of several plant densities and planted throughout the year, periodic destructive measurements were conducted to develop empirical models for partitioning and for SLA(n). Dry matter partitioning into leaves, calculated as incremental leaf dry mass divided by incremental shoot dry mass between two destructive harvests, could be described accurately (R(2 )= 0.93) by a Gompertz function of relative time, R(t). R(t) is 0 at planting date, 1 at the start of short-days, and 2 at final harvest. SLA(n), calculated as the slope of a linear regression between periodic measurements of leaf dry mass (LDM) and LAI, showed a significant linear increase with the inverse of the daily incident photosynthetically active radiation (incident PAR, MJ m(-2 )d(-1)), averaged over the whole growing period, the average glasshouse temperature and plant density (R(2 )= 0.74). The models were validated by two independent experiments and with data from three commercial growers, each with four planting dates. Measured shoot dry mass increase, initial LAI and LDM, plant density, daily temperature and incident PAR were input into the model. Dynamics of LDM and LAI were predicted accurately by the model, although in the last part of the cultivation LAI was often overestimated. The slope of the linear regression of simulated against measured LDM varied between 0.95 and 1.09. For LAI this slope varied between 1.01 and 1.12. The models presented in this study are important for the development of a photosynthesis-driven crop growth model for cut chrysanthemum crops.     

Two measurement methods of leaf dry matter content produce similar results in a broad range of species

BACKGROUND AND AIMS: Leaf dry matter content (LDMC) is widely used as an indicator of plant resource use in plant functional trait databases. Two main methods have been proposed to measure LDMC, which basically differ in the rehydration procedure to which leaves are subjected after harvesting. These are the 'complete rehydration' protocol of Garnier et al. (2001, Functional Ecology 15: 688-695) and the 'partial rehydration' protocol of Vendramini et al. (2002, New Phytologist 154: 147-157). METHODS: To test differences in LDMC due to the use of different methods, LDMC was measured on 51 native and cultivated species representing a wide range of plant families and growth forms from central-western Argentina, following the complete rehydration and partial rehydration protocols. KEY RESULTS AND CONCLUSIONS: The LDMC values obtained by both methods were strongly and positively correlated, clearly showing that LDMC is highly conserved between the two procedures. These trends were not altered by the exclusion of plants with non-laminar leaves. Although the complete rehydration method is the safest to measure LDMC, the partial rehydration procedure produces similar results and is faster. It therefore appears as an acceptable option for those situations in which the complete rehydration method cannot be applied. Two notes of caution are given for cases in which different datasets are compared or combined: (1) the discrepancy between the two rehydration protocols is greatest in the case of high-LDMC (succulent or tender) leaves; (2) the results suggest that, when comparing many studies across unrelated datasets, differences in the measurement protocol may be less important than differences among seasons, years and the quality of local habitats.     

Specific leaf area estimation model building based on leaf dry matter content of Cunninghamia lanceolata北大核心CSCD

Aims With progresses of leaf functional traits study, there is an increasing demand to explore the life history strategy and trade-offs in plants, as well as estimate stand productivity, by employing easy and simple leaf parameters. For instance, the interconversion between leaf dry matter content (LDMC) and specific leaf area (SLA) just fit the bill. Cunninghamia lanceolata serves as one of the most important afforestation evergreen needle species in subtropical zone. Building the SLA estimation model based on LDMC could provide a new approach to estimate SLA, and establish a connection path between mechanism explanation and productivity evaluation. Moreover, it could also build a bridge between individual level and large-scale, as well as between actuarial and estimation. Methods Leaf samples were collected from two sampling sites located in C. lanceolata growing region: Huitong County of Hunan Province and Xinyang City of Henan Province. The samples covered fundamentally different niches (aspect, slope position, and canopy depth), and different life history (stand age and leaf age). SLA and LDMC were determined along leaf age gradients, and their value distributions in linkage to different factors were discussed. A general model based on LDMC of C. lanceolata was built to estimate SLA, and the impact of leaf age on the model was explored. Important findings The SLA of C. lanceolata was (103.15 ± 69.54) cm2·g–1, while LDMC was 0.39 ± 0.11. The LDMC and SLA of C. lanceolata can be estimated by nonlinear model (R2 = 0.718 4, p < 0.001), which meets the estimation requirements. One-year-old leaves showed the best fitting model (R2 = 0.889, p < 0.001), while old leaves (more than 2-year-old) showed the worst (R2 = 0.100 1, p < 0.001). Old leaves with a lower SLA (52.28–75.74 cm2·g–1) might imply the relative independence among the variation of LDMC. The model based on LDMC to evaluate SLA is credible and effective. The effects on LDMC and SLA along leaf age gradients indicate leaf sensitivity, life history strategies and trade-offs. © 2018 Editorial Office of Chinese Journal of Plant Ecology. All rights reserved.     

Specific leaf area and leaf dry matter content as alternative predictors of plant strategies

A key element of most recently proposed plant strategy schemes is an axis of resource capture, usage and availability. In the search for a simple, robust plant trait (or traits) that will allow plants to be located on this axis, specific leaf area is one of the leading contenders. Using a large new unpublished database, we examine the variability of specific leaf area and other leaf traits, the relationships between them, and their ability to predict position on the resource use axis. Specific leaf area is found to suffer from a number of drawbacks; it is both very variable between replicates and much influenced by leaf thickness. Leaf dry-matter content (sometimes referred to as tissue density) is much less variable, largely independent of leaf thickness and a better predictor of location on an axis of resource capture, usage and availability. However, it is not clear how useful dry matter content will be outside northwest Europe, and in particular in dry climates with many succulents.