1. The leaf is an essential unit for measures of plant ecological traits. Yet, measures of plant chemical traits are often achieved by merging several leaves, masking potential foliar variation within and among plant individuals. This is also the case with cost‐effective measures derived using near‐infrared reflectance spectroscopy (NIRS). The calibration models developed for converting NIRS spectral information to chemical traits are typically based on spectra from merged and milled leaves. In this study, we ask whether such calibration models can be applied to spectra derived from whole leaves, providing measures of chemical traits of single leaves.
2. We sampled cohorts of single leaves from different biogeographic regions, growth forms, species and phenological stages to include variation in leaf and chemical traits. For each cohort, we first sampled NIRS spectra from each whole, single leaf, including leaf sizes down to Ø 4 mm (the minimum area of our NIRS application). Next, we merged, milled and tableted the leaves and sampled spectra from the cohort as a tablet. We applied arctic–alpine calibration models to all spectra and derived chemical traits. Finally, we evaluated the performance of the models in predicting chemical traits of whole, single leaves by comparing the traits derived at the level of leaves to that of the tablets.
3. We found that the arctic–alpine calibration models can successfully be applied to single, whole leaves for measures of nitrogen (R² = 0.88, RMSE = 0.824), phosphorus (R² = 0.65, RMSE = 0.081) and carbon (R² = 0.78, RMSE = 2.199) content. For silicon content, we found the method acceptable when applied to silicon‐rich growth forms (R² = 0.67, RMSE = 0.677). We found a considerable variation in chemical trait values among leaves within the cohorts.
4. This time‐ and cost‐efficient NIRS application provides non‐destructive measures of a set of chemical traits in single, whole leaves, including leaves of small sizes. The application can facilitate research into the scales of variability of chemical traits and include intra‐individual variation. Potential trade‐offs among chemical traits and other traits within the leaf unit can be identified and be related to ecological processes. In sum, this NIRS application can facilitate further ecological understanding of the role of leaf chemical traits.

中文翻译：

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全部一片叶子：使用近红外反射光谱法在叶子表面测量的单叶化学特性

1. 叶是衡量植物生态性状的重要单位。然而，植物化学性状的测量通常是通过合并几片叶子，掩盖植物个体内部和植物之间潜在的叶面变异来实现的。使用近红外反射光谱（NIRS）得出的具有成本效益的措施也属于这种情况。为将NIRS光谱信息转换为化学性状而开发的校准模型通常基于合并和磨碎叶片的光谱。在这项研究中，我们问这样的校准模型是否可以应用于从全叶衍生的光谱，从而提供单叶化学特性的度量。
2. 我们对来自不同生物地理区域，生长形式，物种和物候阶段的单叶队列进行了抽样，以包括叶和化学性状的变化。对于每个队列，我们​​首先从每片整张叶子中采样NIRS光谱，包括最小Ø4 mm（NIRS应用程序的最小面积）的叶子​​。接下来，我们将叶片合并，研磨和压片，并将该群组的采样光谱制成片剂。我们将北极-高山校准模型应用于所有光谱和导出的化学特征。最后，我们通过比较从叶片水平到片剂水平的性状，评估了模型在预测整个单叶化学性状方面的性能。
3. 我们发现，北极-高山校准模型可以成功地应用于单叶，全叶，以测量氮（R ²  = 0.88，RMSE = 0.824），磷（R ²  = 0.65，RMSE = 0.081）和碳（R ²  = 0.78，RMSE = 2.199）内容。对于硅含量，我们发现该方法适用于富硅生长形式（R ²  = 0.67，RMSE = 0.677）。我们发现队列中叶片之间的化学性状值有很大差异。
4. 这种节省时间和成本的NIRS应用程序提供了对单个完整叶片（包括小尺寸叶片）中一系列化学特性的非破坏性测量。该应用程序可以促进对化学性状变异性量表的研究，并包括个体内部变异。可以识别叶单元内化学性状和其他性状之间的潜在权衡，并将其与生态过程相关。总之，该NIRS应用程序可以促进对叶片化学性状作用的进一步生态理解。