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Published (Version of record)CC BY V4.0, Open Access
Published (Version of record)CC BY V4.0, Open
Journal article
The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue
Trees, Forests and People, Vol.2, pp.1-11
12/2020
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Abstract
Allometries that include height as independent variable usually provide greater accuracy on estimates of volume, biomass or individual carbon than other prediction strategies that rely only diameter at breast height as independent variable. However, when these models are applied in Amazon Forest Inventories, it is common to use estimated heights rather than measured heights to prepare volume, biomass or carbon estimates. This practice is common, but rarely discussed and the effect on predictions and precision is usually overlooked. The aim of this study was to examine hypsometric models and evaluate the effect of estimated height on merchantable volume prediction in Eastern Amazonian forests. The study area was a 3,786 ha Forest Management Unit owned by Jari Florestal S.A., in the Jari Valley Region of the State of Pará, Brazil. The data includes 16,099 trees of 25 species, measured and harvested in 2006. Ten percent of the data were reserved for validation of the hypsometric and volumetric estimates. Five hypsometric models and two modelling techniques (linear regression and mixed-effects model) were examined. The choice of best model was based on graphical analyses of residuals, distribution of residuals, heteroscedasticity of error and presence of outliers as assessed by h-values, DFFITS and Cook's distance. The hypsometric relationship and volumetric estimates using DBH and DBH with estimated height were validated with Graybill's test, Theil's error decomposition, Efficiency, Equivalence test and Tukey's test for species estimates level. Heights estimated using a semi-logarithmic mixed-effects model can improve predictions from volume equations. The results show that exploratory data analysis and validation process helped to provide estimates with greater efficiency and should be adopted in related studies. The prediction of height associated with volumetric models for six different species provided volumetric estimates with an error below 5% for the global average volume. The estimated height by the mixed-effect non-power law model should be included in double input models previously developed for volume prediction.
Details
- Title
- The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue
- Creators
- Rodrigo Geroni Mendes Nascimento - Amazon Federal Rural University (UFRA) – Belém Campus, Institute of Agricultural Sciences, Graduate Program in Forest Sciences, BrazilJerome Klaas Vanclay - Southern Cross UniversityAfonso Figueiredo Filho - State University of Midwest Paraná (UNICENTRO) – Riozinho Campus, Department of Forest Engineering, Postgraduate Program in Forest Sciences, BrazilSebastião do Amaral Machado - Federal University of Paraná (UFPR) – Jardim Botânico Campus, Department of Forest Engineering, Graduate Program in Forest Engineering, BrazilAdemir Roberto Ruschel - Brazilian Agricultural Research Corporation (EMBRAPA) – Eastern Amazon Head Office, Laboratory of Ecology and Forest Management, BrazilNelson Akira Hiramatsu - Eucatex - Industry and Commerce S.A. – Forest Unit, Planning and Forest Inventory Coordination, BrazilLucas José Mazzei de Freitas - Brazilian Agricultural Research Corporation (EMBRAPA) – Eastern Amazon Head Office, Laboratory of Ecology and Forest Management, Brazil
- Publication Details
- Trees, Forests and People, Vol.2, pp.1-11
- Publisher
- Elsevier BV
- Grant note
- This contribution is part of a Doctoral dissertation at the Federal University of Paraná (UFPR), which was supported by a fellowship from the Brazilian National Research Council (CNPq).
- Identifiers
- 991012963374302368
- Copyright
- © 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/)
- Academic Unit
- Office of Deputy Vice Chancellor, Research; Faculty of Science and Engineering; School of Environment, Science and Engineering
- Language
- English
- Resource Type
- Journal article