Journal article
Development and testing of allometric equations for estimating above-ground biomass of mixed-species environmental plantings
Forest Ecology and Management, Vol.310, pp.483-494
2013
Abstract
To quantify the impact that planting indigenous trees and shrubs in mixed communities (environmental plantings) have on net sequestration of carbon and other environmental or commercial benefits, precise and non-biased estimates of biomass are required. Because these plantings consist of several species, estimation of their biomass through allometric relationships is a challenging task. We explored methods to accurately estimate biomass through harvesting 3139 trees and shrubs from 22 plantings, and collating similar datasets from earlier studies, in non-arid (>300 mm rainfall year-1) regions of southern and eastern Australia. Site-and-species specific allometric equations were developed, as were three types of generalised, multi-site, allometric equations based on categories of species and growth-habits: (i) species-specific, (ii) genus and growth-habit, and (iii) universal growth-habit irrespective of genus. Biomass was measured at plot level at eight contrasting sites to test the accuracy of prediction of tonnes dry matter of above-ground biomass per hectare using different classes of allometric equations. A finer-scale analysis tested performance of these at an individual-tree level across a wider range of sites. Although the percentage error in prediction could be high at a given site (up to 45%), it was relatively low (<11%) when generalised allometry-predictions of biomass was used to make regional- or estate-level estimates across a range of sites. Precision, and thus accuracy, increased slightly with the level of specificity of allometry. Inclusion of site-specific factors in generic equations increased efficiency of prediction of above-ground biomass by as much as 8%. Site-and-species-specific equations are the most accurate for site-based predictions. Generic allometric equations developed here, particularly the generic species-specific equations, can be confidently applied to provide regional- or estate-level estimates of above-ground biomass and carbon.
Details
- Title
- Development and testing of allometric equations for estimating above-ground biomass of mixed-species environmental plantings
- Authors
- Keryn I Paul (Author) - CSIRO Ecosystem SciencesStephen H Roxburgh (Author) - CSIRO Ecosystem SciencesJacqueline R England (Author) - CSIRO Ecosystem SciencesPeter Ritson (Author) - Western Australia Department of Agriculture and FoodTrevor Hobbs (Author) - South Australia Department of Environment, Water and Natural ResourcesKim Brooksbank (Author) - Western Australia Department of Agriculture and FoodR John Raison (Author) - CSIRO Ecosystem SciencesJohn S Larmour (Author) - CSIRO Ecosystem SciencesSimon Murphy (Author) - Victorian Department of Environment and Primary IndustriesJaymie Norris (Author) - Victorian Department of Environment and Primary IndustriesCraig Neumann (Author) - South Australia Department of Environment, Water and Natural ResourcesTom Lewis (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and EngineeringJustin Jonson (Author) - Threshold Environmental Pty Ltd.Jenny L Carter (Author) - CSIRO Ecosystem SciencesGeoff McArthur (Author) - AusCarbon Pty Ltd.Craig Barton (Author) - University of New South WalesBen Rose (Author) - Carbon Neutral Pty Ltd.
- Publication details
- Forest Ecology and Management, Vol.310, pp.483-494
- Publisher
- Elsevier BV
- Date published
- 2013
- DOI
- 10.1016/j.foreco.2013.08.054
- ISSN
- 0378-1127
- Copyright note
- Copyright © 2013 Elsevier BV.
- Organisation Unit
- University of the Sunshine Coast, Queensland; Forest Research Institute
- Language
- English
- Record Identifier
- 99448811902621
- Output Type
- Journal article
Metrics
4 File views/ downloads
1187 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Forestry
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites