On simplifying allometric analyses of forest biomass

By Dimitris Zianis, Maurizio Mencuccini. 2004

449 citations recorded by the source corpus.

Subfields: Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/29b982a8d5e77ec1d87bf261683ee95d7041a3b2

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In Environmental Engineering

In Nature and Landscape Conservation

Citations in the corpus

Allometric equations for four valuable tropical tree species (2006, unknown): “The single metric most commonly used for tree allometry is diameter, as is evident in the review (65 species) of Ter-Mikaelian and Korzukhin (1997) and the synthesis (279 equations) compiled by Zianis and Mencuccini (2004).”
Generalized allometric volume and biomass equations for some tree species in Europe (2007, methodology): “2 estimated in this study varied from 1.37 to 3.19, while the mean (~2.32) was quite similar to the empirical power values ð1:16 3:32; x2:368Þ reported by Zianis and Mencuccini (2004).”
Allometric relationships for below- and aboveground biomass of young Scots pines (2004, result): “Thus, our results support the observation that the most common mathematical model in biomass studies is one of the form of y = ax, where y is the aboveground biomass and x the DBH (Zianis and Mencuccini, 2004).”
Below-ground root yield and distribution in natural and replanted mangrove forests at Gazi bay, Kenya (2008, background): “While there is a substantial literature on the above-ground biomass of mangrove forests (see e.g. Soares and Novelli, 2005; Zianis and Mencuccini, 2003; Komiyama et al., 2002; Clough, 1992), fewer studies have considered below-ground biomass (but see Comley and McGuinness, 2005; Ong et al., 2004;…”
Towards a functional and simplified allometry for estimating forest biomass (2006, methodology): “Although it is generally known that the scaling exponent b is between 2 and 3 (Zianis and Mencuccini, 2004), it is also commonly believed that a species-specific equation (i.e., with different coefficients a and b) has to be used because trees may differ in architecture as well as wood density…”
Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data (2015, methodology): “The multiplicative power model form has been widely adopted for stand attribute predictions (Lim & Treitz, 2004; Lim, Treitz, Baldwin, et al., 2003; Means et al., 1999; Næsset, 2002; Zianis & Mencuccini, 2004).”
Species-specific and general allometric equations for estimating tree biomass components of subtropical forests in southern China (2016, result): “This result is consistent with the previous reports (Brown et al. 1989; Zianis and Mencuccini 2004; Basuki et al. 2009; Kuyah et al. 2012) where D was a strong predictor of tree biomass.”