Abstract

Abstract 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. 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. 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. 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.

Highlights

  • The essential role of chemical constituents in plants and ecosystem functioning is repeatedly emphasized (White 1993; Elser et al 1996; Aerts & Chapin 2000; Güsewell 2004; Elser et al 2007; LeBauer & Treseder 2008; Cebrian et al 2009; Elser et al 2010; Fay et al 2015)

  • 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

  • We found the arctic-alpine calibration models performed well in predicting content of chemical traits of whole leaves

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Summary

Introduction

The essential role of chemical constituents in plants and ecosystem functioning is repeatedly emphasized (White 1993; Elser et al 1996; Aerts & Chapin 2000; Güsewell 2004; Elser et al 2007; LeBauer & Treseder 2008; Cebrian et al 2009; Elser et al 2010; Fay et al 2015). Foliar chemical constituents show interspecific variability at both spatial and temporal scales within and across ecosystems, and are closely related to plant performance and ecological interactions (Güsewell 2004). Foliar chemical content is among the plant traits with the highest intraspecific variability (Albert et al 2010; Siefert et al 2015; Fajardo & Siefert 2016), that may include intraindividual variability (Ely et al 2019). Most methods to measure foliar chemical content require more than a single leaf, especially when working with small arctic and alpine plant species, causing knowledge about intraspecific variability in chemical traits to be at a rudimentary stage.

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