Dataset Information

Retrieving nitrogen isotopic signatures from fresh leaf reflectance spectra: disentangling ?(15)N from biochemical and structural leaf properties.

ABSTRACT: Linking remote sensing methodology to stable isotope ecology provides a promising approach to study ecological processes from small to large spatial scales. Here, we show that ?(15)N can be detected in fresh leaf reflectance spectra of field samples along a spatial gradient of increasing nitrogen input from an N2-fixing invasive species. However, in field data it is unclear whether ?(15)N directly influences leaf reflectance spectra or if the relationship is based on covariation between ?(15)N and foliar nitrogen content or other leaf properties. Using a (15)N-labeling approach, we experimentally varied ?(15)N independently of any other leaf properties in three plant species across different leaf developmental and physiological states. ?(15)N could successfully be modeled by means of partial least squares (PLSs) regressions, using leaf reflectance spectra as predictor variables. PLS models explained 53-73% of the variation in ?(15)N within species. Several wavelength regions important for predicting ?(15)N were consistent across species and could furthermore be related to known absorption features of N-containing molecular bonds. By eliminating covariation with other leaf properties as an explanation for the relationship between reflectance and ?(15)N, our results demonstrate that (15)N itself has an inherent effect on leaf reflectance spectra. Thus, our study substantiates the use of spectroscopic measurements to retrieve isotopic signatures for ecological studies and encourages future development. Furthermore, our results highlight the great potential of optical measurements for up-scaling isotope ecology to larger spatial scales.

SUBMITTER: Hellmann C

PROVIDER: S-EPMC4416452 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Retrieving nitrogen isotopic signatures from fresh leaf reflectance spectra: disentangling δ(15)N from biochemical and structural leaf properties.

Hellmann Christine C Große-Stoltenberg André A Lauströ Verena V Oldeland Jens J Werner Christiane C

Frontiers in plant science 20150501

Linking remote sensing methodology to stable isotope ecology provides a promising approach to study ecological processes from small to large spatial scales. Here, we show that δ(15)N can be detected in fresh leaf reflectance spectra of field samples along a spatial gradient of increasing nitrogen input from an N2-fixing invasive species. However, in field data it is unclear whether δ(15)N directly influences leaf reflectance spectra or if the relationship is based on covariation between δ(15)N a ...[more]

PMID: 25983740

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Project description:Remote sensing of vegetation by spectroscopy is increasingly used to characterize trait distributions in plant communities. How leaves interact with electromagnetic radiation is determined by their structure and contents of pigments, water, and abundant dry matter constituents like lignins, phenolics, and proteins. High-resolution ("hyperspectral") spectroscopy can characterize trait variation at finer scales, and may help to reveal underlying genetic variation-information important for assessing the potential of populations to adapt to global change. Here, we use a set of 360 inbred genotypes of the wild coyote tobacco Nicotiana attenuata: wild accessions, recombinant inbred lines (RILs), and transgenic lines (TLs) with targeted changes to gene expression, to dissect genetic versus non-genetic influences on variation in leaf spectra across three experiments. We calculated leaf reflectance from hand-held field spectroradiometer measurements covering visible to short-wave infrared wavelengths of electromagnetic radiation (400-2500 nm) using a standard radiation source and backgrounds, resulting in a small and quantifiable measurement uncertainty. Plants were grown in more controlled (glasshouse) or more natural (field) environments, and leaves were measured both on- and off-plant with the measurement set-up thus also in more to less controlled environmental conditions. Entire spectra varied across genotypes and environments. We found that the greatest variance in leaf reflectance was explained by between-experiment and non-genetic between-sample differences, with subtler and more specific variation distinguishing groups of genotypes. The visible spectral region was most variable, distinguishing experimental settings as well as groups of genotypes within experiments, whereas parts of the short-wave infrared may vary more specifically with genotype. Overall, more genetically variable plant populations also showed more varied leaf spectra. We highlight key considerations for the application of field spectroscopy to assess genetic variation in plant populations.

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Dataset Information

Retrieving nitrogen isotopic signatures from fresh leaf reflectance spectra: disentangling ?(15)N from biochemical and structural leaf properties.

Publications

Retrieving nitrogen isotopic signatures from fresh leaf reflectance spectra: disentangling δ(15)N from biochemical and structural leaf properties.

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