Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/22539
Title: Using measured stocks of biomass and litter carbon to constrain modelled estimates of sequestration of soil organic carbon under contrasting mixed-species environmental plantings
Contributor(s): Paul, Keryn I (author); England, Jacqueline R (author); Madhavan, Dinesh B (author); Herrmann, Tim (author); Baker, Thomas G (author); Cunningham, Shaun C (author); Perring, Michael P (author); Polglase, Phil J (author); Wilson, Brian  (author)orcid ; Cavagnaro, Timothy R (author); Lewis, Tom (author); Read, Zoe (author)
Publication Date: 2018
DOI: 10.1016/j.scitotenv.2017.09.263
Handle Link: https://hdl.handle.net/1959.11/22539
Abstract: Reforestation of agricultural land with mixed-species environmental plantings of native trees and shrubs contributes to abatement of greenhouse gas emissions through sequestration of carbon, and to landscape remediation and biodiversity enhancement. Although accumulation of carbon in biomass is relatively well understood, less is known about associated changes in soil organic carbon (SOC) following different types of reforestation. Direct measurement of SOC may not be cost effective where rates of SOC sequestration are relatively small and/or highly spatially-variable, thereby requiring intensive sampling. Hence, our objective was to develop a verified modelling approach for determining changes in SOC to facilitate the inclusion of SOC in the carbon accounts of reforestation projects. We measured carbon stocks of biomass, litter and SOC (0-30 cm) in 125 environmental plantings (often paired to adjacent agricultural sites), representing sites of varying productivity across the Australian continent. After constraining a carbon accounting model to observed measures of growth, allocation of biomass, and rates of litterfall and litter decomposition, the model was calibrated to maximise the efficiency of prediction of SOC and its fractions. Uncertainties in both measured and modelled results meant that efficiencies of prediction of SOC across the 125 contrasting plantings were only moderate, at 39-68%. Data-informed modelling nonetheless improved confidence in outputs from scenario analyses, confirming that: (i) reforestation on agricultural land highly depleted in SOC (i.e. previously under cropping) had the highest capacity to sequester SOC, particularly where rainfall was relatively high (> 600 mm year- ¹), and; (ii) decreased planting width and increased stand density and the proportion of eucalypts enhanced rates of SOC sequestration. These results improve confidence in predictions of SOC following environmental reforestation under varying conditions. The calibrated model will be a useful tool for informing land managers and policy makers seeking to understand the dynamics of SOC following such reforestation.
Publication Type: Journal Article
Source of Publication: Science of the Total Environment, v.615, p. 348-359
Publisher: Elsevier BV
Place of Publication: Netherlands
ISSN: 1879-1026
0048-9697
Fields of Research (FoR) 2008: 050301 Carbon Sequestration Science
Fields of Research (FoR) 2020: 410604 Soil chemistry and soil carbon sequestration (excl. carbon sequestration science)
410405 Environmental rehabilitation and restoration
410601 Land capability and soil productivity
Socio-Economic Objective (SEO) 2008: 961402 Farmland, Arable Cropland and Permanent Cropland Soils
961403 Forest and Woodlands Soils
Socio-Economic Objective (SEO) 2020: 180605 Soils
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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