The "plantspec' r package: A tool for spectral analysis of plant stoichiometry
The "plantspec' r package: A tool for spectral analysis of plant stoichiometry
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DOI：
10.1111/2041-210x.13143
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发表时间：
2019-05-01
影响因子：
6.6
通讯作者：
Anderson, T. Michael
中科院分区：
文献类型：
--
作者：
Griffith, Daniel M.;Anderson, T. Michael
植物元素化学计量数据对于生态学家研究生态系统功能、养分循环、植物与草食动物相互作用和叶子经济学至关重要。近红外光谱 (NIRS) 是叶子元素分析的一种经济有效的方法，可以使用植物材料的近红外光谱来预测碳 (C)、氮 (N)、磷 (P) 和钾 (K) 等成分。然而，限制植物生态学家广泛使用 NIRS 的一个主要因素是用于从光谱开发植物化学数据集的免费软件和校准数据的可用性。在这里，我们提出了一对配套的 r 软件包（plantspec' 和 plantspecDB'），它们通过提供从光谱到预测元素数据的整个工作流程来满足这一需求。主要的 r 软件包称为 plantspec'，允许用户操作光谱数据并开发自定义偏最小二乘 (PLS) 模型来预测自己数据集的元素组成。第二个软件包 plantspecDB' 提供近红外光谱以及通过标准分析技术获得的匹配元素数据，这些数据针对从世界各地 18 个草原地点收集的草本样品，主要来源于营养网络实验。 plantspecDB 的数据包还提供批量样品的 C、N、P 和 K 校准，并按植物功能类型（草、禾本科植物和豆科植物）进行分类。最后，我们提供了 plantspec 工作流程的示例，以及这些模型的外部验证，以及东非草的化学计量学应用示例，因为它与它们的进化关系有关。r 包 plantspec 和我们的相关工作流程提供了一个模板来生成稳健的校准模型并增加 NIR 在生态学中的应用。尽管我们专注于植物化学计量，但这里介绍的工作流程可以广泛应用于各种应用，包括土壤、遥感数据、解决方案和组织。最后，我们的全球数据集提供了前所未有的近红外校准数据访问，因为它们与关键植物限制元素的组织浓度有关。
Data on plant elemental stoichiometry are essential for ecologists investigating ecosystem function, nutrient cycling, plant-herbivore interactions and leaf economics.A cost-effective approach to leaf elemental analysis is near-infrared spectroscopy (NIRS), whereby components such as carbon (C), nitrogen (N), phosphorus (P) and potassium (K) can be predicted using NIR spectra from plant material. However, a major factor limiting the widespread use of NIRS by plant ecologists is the availability of free software and calibration data for developing plant chemistry datasets from spectra. Here, we present a pair of companion r packages (plantspec' and plantspecDB') that satisfy this need by providing an entire workflow, from spectra to predicted elemental data.The main r package, called plantspec', allows users to manipulate spectral data and develop custom partial least square (PLS) models for predicting the elemental composition of their own datasets. The second package, plantspecDB', provides NIR spectra, and matched elemental data obtained with standard analytical techniques, for herbaceous samples collected from 18 grassland sites around the world, primarily sourced from the Nutrient Network experiment. The plantspecDB' data package also provides calibrations for C, N, P and K for bulk samples and separated by plant functional type: grasses, forbs and legumes. Finally, we provide an example of the plantspec' workflow, and external validation of these models, and an example application to the stoichiometry of East African grasses as it relates to their evolutionary relationships.The r package plantspec', and our associated workflow, provides a template to produce robust calibration models and increase the application of NIR in ecology. Although, we focus on plant stoichiometry, the workflow presented here can be applied broadly for a broad range of applications, including soils, remote sensing data, solutions and tissues. Finally, our global dataset provides unprecedented access to NIR calibration data as they pertain to tissue concentrations of key plant limiting elements.