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在纯落叶支架中使用三种截然不同的方法估算叶面积指数

Published: August 29, 2019
doi:
10.3791/59757
, , ,
1Forestry and Game Management Research Institute,Research Station at Opočno, 2Department of Silviculture,Mendel University in Brno, 3Department of Forest Botany, Dendrology and Geobiocenology,Mendel University in Brno

Summary

准确估计叶片面积指数（LAI）对于植物生态系统内以及生态系统和大气边界层之间的许多物质和能源通量模型至关重要。因此，在所提出的协议中，有三种方法（陷阱、针技术和PCA）进行精确的LAI测量。

Abstract

叶面积指数（LAI）的精确估计，定义为水平地面面积单位总叶表面积的一半，对于描述生态、林业和农业领域的植被结构至关重要。因此，逐步介绍了三种商业使用方法（垃圾陷阱、针技术和植物冠架分析仪）执行 LAI 估计的程序。比较了具体的方法，并讨论了它们目前的优势、争议、挑战和未来的观点。垃圾陷阱通常被视为参考级别。与参考值相比，针技术和植物树冠分析仪（例如 LAI-2000）经常低估 LAI 值。针技术很容易在落叶架使用，每年垃圾完全分解（例如，橡木和山毛虫架）。然而，基于垃圾陷阱或直接破坏方法的校准是必要的。植物树冠分析仪是一种用于在生态、林业和农业中执行 LAI 估计的常用设备，但由于树叶丛状和传感器视野 （FOV） 中木质元素的贡献，存在潜在误差。讨论了消除这些潜在的错误源。植物树冠分析仪是一种非常合适的设备，用于在高空间水平上执行 LAI 估计、观察季节性 LAI 动态以及长期监测 LAI。

Introduction

LAI，定义为水平地面面积1单位总叶表面积的一半，是许多生物地球物理和化学交换模型中的关键变量，该模型侧重于碳和水通量2、3、4.LAI 与叶的活性表面成正比，在叶中驱动初级生产（光合作用）、蒸腾、能量交换和其他与植物中一系列生态系统过程相关的生理属性社区5.

已开发出多种执行LAI估计的方法和工具，目前市场上有6、7、8、9。执行 LAI 估计的地面方法可以分为两大类：（i） 直接方法，和 （ii） 间接方法10、11、12 。第一组包括直接测量叶面积的方法，而间接方法则利用辐射转移理论（在时间、劳动密集型和技术方面）从更容易测量的参数的测量中推断LAI，13 ，14.

本议定书涉及垃圾陷阱和针技术的实际应用，作为非破坏性的半直接方法10;和光学设备植物树冠分析仪作为间接方法6，7对中欧温带落叶林的选定样品进行LAI估计（参见其结构和树状特征附录 A和附录 B）。

在落叶林和作物中，可以使用分布于树冠层15以下的垃圾陷阱进行无损半直接LAI估计。垃圾陷阱为落叶物种提供精确的LAI值，其中LAI在生长季节到达高原。然而，对于在生长季节可以代替叶子的物种，如杨树，该方法高估了LAI11。此方法假定陷阱的内容表示在支架16的落叶期间，特别是在秋季期间，落在叶中的平均落叶量。陷阱是打开的盒子或网（图1），预定的足够大小（最小0.18米2，但最好超过0.25米2）10，17，侧边防止风吹叶入/出陷阱，并与穿孔的底部避免叶的分解;然而，位于研究支架的树冠层之下，位于地表11之上。陷阱的分布可以是随机的18，也可以是系统在横切19或常规间距网格20。陷阱的数量和分布是执行精确的 LAI 估计的关键方法步骤，反映了独特的站结构、空间均匀性、预期风速和方向，尤其是在稀疏的支架（或小巷和果园），以及评估数据的工作能力。LAI 估计的精度随所研究陷阱频率的上升而增加，为11、21（见图2）。

建议从每个陷阱收集垃圾落物样本的频率至少每月10次，在大雨期间，甚至每周两次，这可能与强降雨同时发生。在化学分析的情况下，有必要防止陷阱中的垃圾分解和雨中物质中营养物质的浸出。在田地中收集叶子后，混合子样本用于估计特定的叶子面积（SLA，cm2 g-1）22，定义为叶子的新鲜投影面积与其干质量重量比。其余的收集的垃圾燥到恒定的重量，并用于计算在实验室中的垃圾的干质量为 gcm – 2 。每个收集日期的叶子干质量通过将收集的生物量乘以SLA或叶干质量（LMA，g cm-2）作为与SLA23、24的反向参数，转换为叶片面积。使用平面测量方法可以确定特定叶子的新鲜投影区域。平面测量方法基于特定叶面积与水平曲面中叶覆盖的区域之间的依赖关系。叶子水平固定在扫描屏幕上，其平均值使用叶面积计进行测量。然后，计算其面积。市场上有许多基于不同测量原理的叶面积计。其中一些包括使用正交投影方法的LI-3000C便携式叶面积计和LI-3100C面积计，后者使用荧光光源和半传导扫描相机测量叶片平均值。下一个设备 CI-202 便携式激光叶面积计使用代码读取器对叶长度进行编码。此外，AM350 和 BSLM101 便携式叶面积计还通常用于执行准确的叶面积估计。

此外，基于分析视频的系统存在的叶面积计。这些叶面积计由摄像机、数字化框架、屏幕和 PC 组成，包括用于进行数据分析的合适软件，如 WD3 WinDIAS 叶图像分析系统11。目前，连接到 PC 的传统扫描仪可用于估计叶区域。之后，叶面积计算为黑色像素数的倍数，其大小取决于所选分辨率（每英寸点 = dpi），或者叶面积通过特定软件（例如 WinFOLIA）进行测量。最后，通过乘以SLA和收缩系数25，将已知地面面积内收集的叶子总干质量转换为LAI，该系数反映新鲜和干燥叶子面积的变化。收缩取决于树种、含水量和叶子柔软度。叶子的长度和宽度的收缩（影响预计面积）通常高达10%26，例如，它的范围从2.6到6.8%的橡树27。按物种对叶子进行分类，以称重和确定具体的叶面积比率是必要的，以确定每个物种对LAI28的总贡献。

通过针技术确定LAI是一种廉价的方法，从斜点四元法29，30，31，32。在落叶架中，它是执行 LAI 估计的替代方法，无需使用陷阱10，其假设是树中的总叶片数及其面积等于完全落叶20后在土壤表面收集的数量.一根细尖的针被垂直刺穿，在落叶10后立即被垂直刺穿躺在地上的垃圾中。完整落叶后，叶子从地面收集到垂直探头的针上，与接触号相关，等于实际 LAI 值。针技术需要密集采样（每个研究台点每个研究站100-300个采样点），以量化平均接触号并正确推导LAI值10、20、33。

的植物冠子分析仪（例如，LAI-2000 或 LAI-2200 PCA）是一种常用的便携式仪器，用于通过测量整个顶篷的透光量来执行间接 LAI 估计7在光谱的过滤蓝色部分（320-490 nm）34,35尽量减少穿过树叶的光的贡献，被树冠分散，穿过树叶7,34.在光谱的蓝色部分，树叶和天空之间的最大对比度达到，树叶在天空中呈黑色34.因此，它基于顶篷间隙分数分析7.该仪器已广泛应用于作物等植物群落的生态生理学研究。36草原37，针叶架8，和落叶架38.植物树冠分析仪使用 FOV 为 148° 的鱼眼光学传感器35将顶篷的半球图像投射到硅探测器上，将它们排列成五个同心环39中心顶角为 7°、23°、38°、53°和 68°9,40,41.五个视图上限（即,270°、180°、90°、45°和10°）可用于限制光学传感器的等位角视图27为了避免在 LAI 评估期间打开区域（对于上述读数）或传感器 FOV 中的操作员设置障碍物的遮阳，可以将 FOV 传感器调整到打开区域，以提供顶篷上方的读数。使用植物树冠分析仪进行测量，在上方（或在足够扩展的开放区域）和研究的树冠下方进行测量7.必须在读数上方和下方使用相同的视图上限，以避免间隙分数估计的偏差34.LAI-2000 PCA 产生陈等人介绍的有效叶面积指数 （LAIe）。42，或者更确切地说，传感器读数值中包含有效的植物面积指数 （PAIe），作为木质元素。在带平叶的落叶架上，LAIe 与平面 LAI 相同。对于常绿森林支架，需要 LAIe 来校正拍摄级别的聚集效果（SPAR、STAR）43，在比拍摄量更大的比例下，聚集索引（*E)44，以及木本元素（包括茎和树枝）的贡献（即,木本与总面积比率），45导致系统 LAI 低估20.比芽或叶更高的空间尺度上的聚集指数可以量化为明显的结块指数 （ACF），当使用更严格的视图帽时，可以使用植物树冠分析仪进行估计27.正如这些作者指出，这个ACF是从LAI值的比率推导，根据Lang的说法，通过不同程序对同质和非均质的檐篷计算从透射中计算出的46，我们假设这个聚集索引描述相当冠状均匀性。除了 ACF 计算之外，新的扩散器帽（使 LAI-2200 PCA 在天气条件方面得到更广泛的应用、用户菜单代替 Fct 代码以及每个文件会话进行更多测量的可能性）是主要内容之一。与前 LAI-2000 PCA 相比，技术升级34,47.测量和随后的内部软件计算基于四个假设：（1） 光阻滞植物元素，包括叶子、树枝和茎，在树冠中随机分布;（2） 树叶是一个光学黑色体，可吸收所有光，它接收，（3）所有植物元素是相同的投影到水平地面作为一个简单的几何凸形状，（4）植物元素是小相比，覆盖面积每个环11.

Protocol

1. 使用垃圾陷阱估计的LAI 首先，进行实地调查，调查所研究台的选址条件和结构（即坡度、森林或植被类型、森林或植被密度、树冠封闭均匀性、冠冠大小和表冠基高度）。 根据所研究支架的同化装置的大小选择网的网格大小，选择合适的垃圾陷阱类型，以定位到顶篷下方（即，网格大小必须小于捕获的同化大小）设备），然后编号和分配在研究的支架内的陷阱，然…

Representative Results

图8中给出了2013年生长季节所有被研究摊位的站级平均LAI值。在除 A 之外的所有绘图上，最高值由作为参考级别的垃圾陷阱测量。相反，通过图 A 上的针技术估计了最高平均 LAI 值。使用垃圾收集器估计的 LAI 值与植物树冠分析仪之间的所有差异均不显著（p > 0.05;图8，左）。在图 B、C 和 D 上，针技术大大低估了从垃圾陷阱中获得的 LAI。相反，在图A上，…

Discussion

垃圾陷阱被认为是执行LAI估计8的最准确的方法之一，但它们比纳入该协议的间接方法35，64更耗费人力、更耗时。在整个使用垃圾陷阱的LAI估计过程中，对SLA的精确估计是最关键的点10，因为SLA可以随植物物种65、日期和年份、陷阱中的时间长度、天气66和地点而变化生育力<sup class="…

Divulgazioni

The authors have nothing to disclose.

Acknowledgements

我们感谢《林业研究杂志》编辑委员会鼓励和授权我们使用本议定书中从该议定书上发表的文章中的代表性结果。我们还衷心感谢两位匿名评论者的宝贵意见，这些评论大大改善了手稿。这项研究由捷克共和国农业部、机构支助MZE-RO0118和国家农业研究局资助（项目No.QK1810126）。

Materials

Area Meter LI-COR Biosciences Inc., NE, USA LI-3100C https://www.licor.com/env/products/leaf_area/LI-3100C/
Computer Image Analysis System Regent Instruments Inc., CA WinFOLIA http://www.regentinstruments.com/assets/images_winfolia2/WinFOLIA2018-s.pdf
File Viewer LI-COR Biosciences Inc., NE, USA FV2200C Software https://www.licor.com/env/products/leaf_area/LAI-2200C/software.html
Laboratory oven Amerex Instruments Inc., CA, USA CV150 https://www.labcompare.com/4-Drying-Ovens/2887-IncuMax-Convection-Oven-250L/?pda=4|2887_2_0|||
Leaf Image Analysis System Delta-T Devices, UK WD3 WinDIAS https://www.delta-t.co.uk/product/wd3/
Litter traps Any NA See Fig. 2
Needle Any NA Maximum diameter of 2 mm
Plant Canopy Analyser LI-COR Biosciences Inc., NE, USA LAI-2000 PCA LAI-2200 PCA or LAI-2200C as improved versions of LAI-2000 PCA can be used, see: https://www.licor.com/env/products/leaf_area/LAI-2200C/
Portable Laser Leaf Area Meter CID Bio-Science, WA, USA CI-202 https://cid-inc.com/plant-science-tools/leaf-area-measurement/ci-202-portable-laser-leaf-area-meter/
Portable Leaf Area Meter ADC, BioScientic Ltd., UK AM350 https://www.adc.co.uk/products/am350-portable-leaf-area-meter/
Portable Leaf Area Meter Bionics Scientific Technogies (P). Ltd., India BSLM101 http://www.bionicsscientific.com/measuring-meters/leaf-area-index-meter.html
Portable Leaf Area Meter LI-COR Biosciences Inc., NE, USA LI-3000C https://www.licor.com/env/products/leaf_area/LI-3000C/
DOWNLOAD MATERIALS LIST

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Tags

Leaf Area IndexLAI EstimationLitter TrapsOptical MethodsDestructive SamplingDeciduous StandsLeaf Area MeasurementEcophysiological StudiesPlant Ecosystems
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Černý, J., Pokorný, R., Haninec, P., Bednář, P. Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands. J. Vis. Exp. (150), e59757, doi:10.3791/59757 (2019).
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