Improved models for estimating temporal changes in carbon sequestration in above-ground biomass of mixed-species environmental plantings

Paul, Keryn I, Roxburgh, Stephen H, England, Jacqueline R, de Ligt, Robert, Larmour, John S, Brooksbank, Kim, Murphy, Simon, Ritson, Peter, Hobbs, Trevor, Lewis, Tom, Preece, Noel D, Cunningham, Shaun C, Read, Zoe, Clifford, David and Raison, R John 2015, Improved models for estimating temporal changes in carbon sequestration in above-ground biomass of mixed-species environmental plantings, Forest ecology and management, vol. 338, pp. 208-218, doi: 10.1016/j.foreco.2014.11.025.

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Title Improved models for estimating temporal changes in carbon sequestration in above-ground biomass of mixed-species environmental plantings
Author(s) Paul, Keryn I
Roxburgh, Stephen H
England, Jacqueline R
de Ligt, Robert
Larmour, John S
Brooksbank, Kim
Murphy, Simon
Ritson, Peter
Hobbs, Trevor
Lewis, Tom
Preece, Noel D
Cunningham, Shaun C
Read, Zoe
Clifford, David
Raison, R John
Journal name Forest ecology and management
Volume number 338
Start page 208
End page 218
Total pages 11
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2015-02-15
ISSN 0378-1127
Keyword(s) FullCAM
Growth rate
Biodiversity plantings
Carbon accounting
Summary Plantings of mixed native species (termed 'environmental plantings') are increasingly being established for carbon sequestration whilst providing additional environmental benefits such as biodiversity and water quality. In Australia, they are currently one of the most common forms of reforestation. Investment in establishing and maintaining such plantings relies on having a cost-effective modelling approach to providing unbiased estimates of biomass production and carbon sequestration rates. In Australia, the Full Carbon Accounting Model (FullCAM) is used for both national greenhouse gas accounting and project-scale sequestration activities. Prior to undertaking the work presented here, the FullCAM tree growth curve was not calibrated specifically for environmental plantings and generally under-estimated their biomass. Here we collected and analysed above-ground biomass data from 605 mixed-species environmental plantings, and tested the effects of several planting characteristics on growth rates. Plantings were then categorised based on significant differences in growth rates. Growth of plantings differed between temperate and tropical regions. Tropical plantings were relatively uniform in terms of planting methods and their growth was largely related to stand age, consistent with the un-calibrated growth curve. However, in temperate regions where plantings were more variable, key factors influencing growth were planting width, stand density and species-mix (proportion of individuals that were trees). These categories provided the basis for FullCAM calibration. Although the overall model efficiency was only 39-46%, there was nonetheless no significant bias when the model was applied to the various planting categories. Thus, modelled estimates of biomass accumulation will be reliable on average, but estimates at any particular location will be uncertain, with either under- or over-prediction possible. When compared with the un-calibrated yield curves, predictions using the new calibrations show that early growth is likely to be more rapid and total above-ground biomass may be higher for many plantings at maturity. This study has considerably improved understanding of the patterns of growth in different types of environmental plantings, and in modelling biomass accumulation in young (<25 years old) plantings. However, significant challenges remain to understand longer-term stand dynamics, particularly with temporal changes in stand density and species composition.
Language eng
DOI 10.1016/j.foreco.2014.11.025
Field of Research 050102 Ecosystem Function
07 Agricultural And Veterinary Sciences
05 Environmental Sciences
06 Biological Sciences
Socio Economic Objective 961202 Rehabilitation of Degraded Farmland
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Grant ID LP0990038
Copyright notice ©2015, Elsevier
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