Review of Macroscopic Features for Hardwood and Softwood Identification and a Proposal for a New Character List

Abstract

With the adoption of a number of anti-illegal logging laws, treaties, memoranda, and international agreements around the world, there is broad and renewed interest in wood identification, especially in the field at the macroscopic level. In response to this interest, and to begin to fill an obvious gap in the corpus of wood anatomical reference material, we review several prominent English-language publications on macroscopic wood identification in order to form a list of characters. We compile characters and organize them in the spirit of the IAWA lists for hardwood and softwood microscopic identification, present the state of the art as it exists, attempt to reconcile the different sets of definitions, characters, and character states, then present our proposed working-list. It is our intent with this publication to open an international discussion regarding the standardization of macroscopic wood identification features, and it is our hope that such a discussion can include critical works from the non-English literature. We also call for an illustrated glossary to accompany the proposed list. A standard lexicon to describe wood at the macroscopic level will simplify the preparation of identification documents and permit the ready translation of keys and other references for easy use and deployment around the world.

IAWA List of Microscopic Bark Features

“…moreover, the practical links between microscopy and macroscopy are equally important in bark as in wood identification (Ruffinatto et al 2015). Unfortunately we did not succeed in finalizing the macroscopic section of the bark list in time, but we hope to remedy this in the future.…”

The anatomy of »blue ring« in the wood of Pinus nigra

“…On sanded transverse sections, growth rings are macroscopically visible thanks to an abrupt change in colour intensity from the lighter earlywood to the darker latewood (Ruffinatto et al, 2015). The blue rings did not show any macroscopic difference compared to previous and following rings (Piermattei et al 2015), the color difference between earlywood and latewood is not affected by the presence of a blue ring.…”

Machine Learning Models with Quantitative Wood Anatomy Data Can Discriminate between Swietenia macrophylla and Swietenia mahagoni

“…In recent decades, international efforts to prohibit or limit the trade of endangered species have been made to combat illegal logging and associated trade [1][2][3][4][5], usually emphasizing the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), which lists species in an identification and provide forensically reliable results [13], but they depend on knowledge of the breadth of variability in a given species and typically require years or decades to develop that expertise. One way to investigate subtle wood anatomical divergences between species is to collect quantitative data relating to key characters and subject these data to multivariate statistical classification [36,37].…”