SpectraPop

1st Practical Course of the Spectra Pop Project. Image credit © 2025 Biodivspec group.

Popularizing the use of the Species Spectral Signature to identify trees in Sustainable Forest Management in the Amazon - Spectra Pop

Description

Errors in the identification of timber species affect the entire production chain in forest management, from the sustainability of the management of species with high commercial value for future harvesting cycles, to inspection and the sale and marketing of timber. Therefore, in an effort to improve the process of identifying species for sustainable forest management, this proposal aims to develop and popularize the use of the species' spectral signature in the identification of high-value commercial species. The combined use of high-tech instruments and appropriate techniques to discriminate tree species is necessary to improve the biodiversity inventory system in tropical countries. Near-infrared leaf spectroscopy has shown promise for discriminating plant species. In this way, we intend to produce a spectral herbarium, use protocols, test more accessible equipment and train people from different groups in society. Thus, we believe in popularizing the use of this tool developed at the National Institute for Amazonian Research to improve the quality of forest management identifications in the Amazon. The popularization and application of this tool will increase the sustainability of forest management in the state of Amazonas. In this way, this proposal aims to develop and popularize technology that will benefit Amazonas environmentally, socially and economically.

Find out more on the SpectraPop website.

This project is part of Call no. 006/2024 - Women in Science (process no. 01.02.016301.04984/2024-17), funded by the Fundação de Amparo à Pesquisa do Estado do Amazonas (FAPEAM).
Caroline C. Vasconcelos
Caroline C. Vasconcelos
Research Fellow

My research interests include taxonomy and systematics (especially neotropical Sapotaceae), spectroscopy as a integrative tools, Amazonian flora, species distribution modeling, floristic studies, and tropical forest ecology.

Related