Diversity and equitability ordering profiles applied to study forest structure

By Ruben Valbuena, Petteri Packalen, Susana Martı´n-Fernández, Matti Maltamo. 2012

99 citations recorded by the source corpus.

Abstract This 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 even-sized 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.

Subfields: Ecology, Evolution, Behavior and Systematics, Forestry, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/62abce0871ba6352b7d683609716de55d033a5c0

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In Ecology, Evolution, Behavior and Systematics

In Forestry

In Nature and Landscape Conservation

Citations in the corpus

Characterizing forest structural types and shelterwood dynamics from Lorenz-based indicators predicted by airborne laser scanning (2013, background): “The Lorenz curve’s axes, xr and Mr, represent relative proportions of stem density and basal area (Valbuena et al. 2012).”
Comparison of airborne laser scanning methods for estimating forest structure indicators based on Lorenz curves (2014, methodology): “In a forest, the Lorenz curve expresses dominance relations by comparing relative cumulated proportions of basal area and stem density accounted for each tree (Valbuena et al., 2012).”
Key structural features of Boreal forests may be detected directly using L-moments from airborne lidar data (2017, methodology): “5 was used because it represents maximum entropy of tree sizes (Valbuena et al., 2012); also recall that Lcv= GC (see Appendix A.”