a b s t r a c tThis article performs an in-depth examination on whether indices of diversity and equitability among tree size classes are adequate for studying the structural complexity of forests. Diversity profiles and the intrinsic diversity ordering of several field plots were compared. Results demonstrated that evensized stands are intrinsically non-comparable to uneven-sized stands with regard to their diversity of size classes. Indices describing the diversity of size classes are consequently inadequate, as they order forest structural types (FSTs) inconsistently. The concept of equitability, obtained when removing the richness component from entropy, seemed more adequate for this purpose. Indices of equitability among size classes provided more consistent measures, since the field plots had comparable intrinsic equitability ordering. Furthermore, ranking individual trees by their size is a better approach than ranking size classes, and therefore it is more correct to measure the inequality of tree sizes rather than equitability among size classes. A particular interpretation of Lorenz curves applies when they are used for the study of forest structures, as they should also be compared to a theoretical uniform distribution, and not just the diagonal line-of-absolute-equality. Advised indices are Gini coefficient (GC), De Camino homogeneity (CH), and structure index based on variance (STVI), as they all are consistent with the Lorenz ordering.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.