Improved wood species identification based on multi-view imagery of the three anatomical planes.

Background: The identification of tropical African wood species based on microscopic imagery is a challenging problem due to the heterogeneous nature of the composition of wood combined with the vast number of candidate species. Image classification methods that rely on machine learning can facilitate this identification, provided that sufficient training material is available. Despite the fact that the three main anatomical sections contain information that is relevant for species identification, current methods only rely on transverse sections.

Climatic Signals in Tree Rings of Heritiera fomes Buch.-Ham. in the Sundarbans, Bangladesh.

Mangroves occur along the coastlines throughout the tropics and sub-tropics, supporting a wide variety of resources and services. In order to understand the responses of future climate change on this ecosystem, we need to know how mangrove species have responded to climate changes in the recent past. This study aims at exploring the climatic influences on the radial growth of Heritiera fomes from a local to global scale.

High-resolution proxies for wood density variations in Terminalia superba.

Background And Aims: Density is a crucial variable in forest and wood science and is evaluated by a multitude of methods. Direct gravimetric methods are mostly destructive and time-consuming. Therefore, faster and semi- to non-destructive indirect methods have been developed.