Recognizing Amazonian tree species in the field using bark tissues spectra

[Display omitted] •We tested VIS-NIR spectroscopy in trees trunk in field to identify tropical species.•We tested outer bark spectra and inner bark spectra to distinguish species.•We distinguish species from broad phylogenetic variation using bark spectra.•Field bark spectra is a new approach to rec...

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Bibliographic Details
Published in:Forest ecology and management 2018-11, Vol.427 (C), p.296-304
Main Authors: Hadlich, Hilana Louise, Durgante, Flávia Machado, dos Santos, Joaquim, Higuchi, Niro, Chambers, Jeffrey Q., Vicentini, Alberto
Format: Article
Language:English
Subjects:
ENVIRONMENTAL SCIENCES
Forest management
Inner bark
Outer bark
Reflectance data
Species identification
VIS-NIRs
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Summary:[Display omitted] •We tested VIS-NIR spectroscopy in trees trunk in field to identify tropical species.•We tested outer bark spectra and inner bark spectra to distinguish species.•We distinguish species from broad phylogenetic variation using bark spectra.•Field bark spectra is a new approach to recognize species in forest inventories. The identification of tree species in the field is often a subjective process and misidentifications cause many problems for forest management in the Amazon Forest. Near infrared spectra from dried leaves of herbarium specimens are able to distinguish species in tropical forests. However, toolsto improve species identification directly in the field are needed. In this study, we tested whether spectral reflectance of bark tissues (rhytidome and phloem) collected with a portable spectrometer in the field can be used for the discrimination of tree species. Spectral data was collected for 254 trees of 8 families, 10 genera and 11 species from terra firme forests in Central Amazon with an ASD field spectrometer. Data consisted of reflectance values within 350–2500 nm wavelengths. We compared the rate of correct species recognition for different datasets using linear discriminant models. The rate of correct species assignment using this technique was 98% when using spectra from the inner bark (phloem) and 94% with outer bark (rhytidome) spectra. We suggest that the application of this technique can improve the quality of species identification directly during field inventories, fostering better forest management practices.
ISSN:0378-1127
1872-7042
DOI:10.1016/j.foreco.2018.06.002