2004
DOI: 10.1007/s00468-004-0333-z
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Additive biomass equations for native eucalypt forest trees of temperate Australia

Abstract: Biomass additivity is a desirable characteristic of a system of equations for predicting component as well as total tree biomass since it eliminates the inconsistency between the sum of predicted values for components such as stem, bark, branch and leaf and the prediction for the total tree. Besides logical consistency, a system of additive biomass equations when estimated by taking into account the inherent correlation among the biomass components has greater statistical efficiency than separately estimated e… Show more

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Cited by 163 publications
(183 citation statements)
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“…This finding is in agreement with prior findings in white pine forests (Peichl and Arain 2007). Similarly, Bi et al (2004) and López Serrano et al (2005) suggested that variations in allometries may be associated with the influence of the growth stage. We agree, but note that the equations using the pooled data from all stand ages also performed well (P < 0.001 for all components), with higher but still small S.E.E.…”
Section: Allometric Relationshipssupporting
confidence: 93%
“…This finding is in agreement with prior findings in white pine forests (Peichl and Arain 2007). Similarly, Bi et al (2004) and López Serrano et al (2005) suggested that variations in allometries may be associated with the influence of the growth stage. We agree, but note that the equations using the pooled data from all stand ages also performed well (P < 0.001 for all components), with higher but still small S.E.E.…”
Section: Allometric Relationshipssupporting
confidence: 93%
“…For each approach, the selected biomass models were simultaneously adjusted to satisfy the biomass compartment additivity constraint (Parresol 1999(Parresol , 2001Návar et al 2002;Carvalho and Parresol 2003;Bi et al 2004;Genet et al 2011). Seemingly unrelated regression method was used to solve the simultaneous equation system through the PROC MODEL procedure in SAS (SAS Institute Inc. 2011), and the parameter values were derived using the maximum likelihood method.…”
Section: Model Fittingmentioning
confidence: 99%
“…Human activities, especially the excessive burning of fossil fuels such as coal, oil and gas have resulted in an excessive increase in atmospheric carbon dioxide (CO2) level. (Bi et al, 2004). The impact of global warming triggered rise sealevel, higher frequency of fires in forests, climate change and occurrence of disasters (flooding and drought).…”
Section: Introductionmentioning
confidence: 99%