Anatomical and physical analysis of the bark of three Amazonian tree species as a tool for species identification

Accurate species identification is crucial for conservation efforts and combating illegal logging. This study analyzes the anatomical characteristics and physical properties of the bark of three tropical species: Bertholletia excelsa, Cedrela odorata, and Eschweilera coriacea, to assess their potential for rapid species identification. The hypothesis proposed was that anatomical and physical differences in the bark would allow for effective identification. The study was conducted in the southeastern region of Peru, in the department of Madre de Dios, where nine trees from the three species were randomly selected. Bark samples were collected at breast height (DBH) from the trees. The samples were analyzed macroscopically, microscopically, and for physical properties such as moisture content, basic density, and volumetric shrinkage. The results showed that B. excelsa had the thickest (14.11 cm) and most fibrous bark, while C. odorata had thinner bark (9.33 cm), with a more regular organization. E. coriacea had the thinnest (8.83 cm) and most flexible bark. Regarding physical properties, B. excelsa exhibited the highest moisture content (68.71%), while C. odorata showed the highest basic density (740 kg/m³). This study demonstrates that anatomical and physical characteristics of bark are effective tools for the identification of tree species, contributing to conservation and the prevention of illegal logging.

Authors

Institutions

Publication Details

Journal
Revista Árvore
Published
2025-05-30
DOI
https://doi.org/10.53661/1806-9088202549263890
Primary Topic
Ethnobotanical and Medicinal Plants Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Anatomical and physical analysis of the bark of three Amazonian tree species as a tool for species identification

Leif Armando Portal‐Cahuana, Nestor Mamani-Mendoza
Revista Árvore
Ethnobotanical and Medicinal Plants Studies
article

Anatomical and physical analysis of the bark of three Amazonian tree species as a tool for species identification

Leif Armando Portal‐Cahuana, Nestor Mamani-Mendoza
article en

Abstract

Accurate species identification is crucial for conservation efforts and combating illegal logging. This study analyzes the anatomical characteristics and physical properties of the bark of three tropical species: Bertholletia excelsa, Cedrela odorata, and Eschweilera coriacea, to assess their potential for rapid species identification. The hypothesis proposed was that anatomical and physical differences in the bark would allow for effective identification. The study was conducted in the southeastern region of Peru, in the department of Madre de Dios, where nine trees from the three species were randomly selected. Bark samples were collected at breast height (DBH) from the trees. The samples were analyzed macroscopically, microscopically, and for physical properties such as moisture content, basic density, and volumetric shrinkage. The results showed that B. excelsa had the thickest (14.11 cm) and most fibrous bark, while C. odorata had thinner bark (9.33 cm), with a more regular organization. E. coriacea had the thinnest (8.83 cm) and most flexible bark. Regarding physical properties, B. excelsa exhibited the highest moisture content (68.71%), while C. odorata showed the highest basic density (740 kg/m³). This study demonstrates that anatomical and physical characteristics of bark are effective tools for the identification of tree species, contributing to conservation and the prevention of illegal logging.

Revista ÁrvoreVol. 49(1)
National University Toribio Rodríguez de Mendoza (PE), Universidad Andina del Cusco (PE)
Universidad El Bosque
Openalex Percentile: Top 91%
Ethnobotanical and Medicinal Plants Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.