Using measured stocks of biomass and litter carbon to constrain modelled estimates of sequestration of soil organic carbon under contrasting mixed-species environmental plantings

Keryn I. Paul, Jacqueline R. England, Thomas G. Baker, Shaun C. Cunningham, Michael P. Perring, Phil J. Polglase, Brian Wilson, Timothy R. Cavagnaro, Tom Lewis, Zoe Read, Dinesh B. Madhavan, Tim Herrmann

Research output: Contribution to journalArticle

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.

LanguageEnglish
Pages348-359
Number of pages12
JournalScience of the Total Environment
Volume615
DOIs
StatePublished - 15 Feb 2018

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Organic carbon
Biomass
litter
Carbon
organic carbon
Reforestation
Soils
carbon
biomass
reforestation
soil
planting
carbon sequestration
agricultural land
prediction
Biodiversity
litterfall
Remediation
Gas emissions
Greenhouse gases

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Paul, Keryn I. ; England, Jacqueline R. ; Baker, Thomas G. ; Cunningham, Shaun C. ; Perring, Michael P. ; Polglase, Phil J. ; Wilson, Brian ; Cavagnaro, Timothy R. ; Lewis, Tom ; Read, Zoe ; Madhavan, Dinesh B. ; Herrmann, Tim. / Using measured stocks of biomass and litter carbon to constrain modelled estimates of sequestration of soil organic carbon under contrasting mixed-species environmental plantings. In: Science of the Total Environment. 2018 ; Vol. 615. pp. 348-359
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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.",
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Paul, KI, England, JR, Baker, TG, Cunningham, SC, Perring, MP, Polglase, PJ, Wilson, B, Cavagnaro, TR, Lewis, T, Read, Z, Madhavan, DB & Herrmann, T 2018, 'Using measured stocks of biomass and litter carbon to constrain modelled estimates of sequestration of soil organic carbon under contrasting mixed-species environmental plantings' Science of the Total Environment, vol 615, pp. 348-359. DOI: 10.1016/j.scitotenv.2017.09.263

Using measured stocks of biomass and litter carbon to constrain modelled estimates of sequestration of soil organic carbon under contrasting mixed-species environmental plantings. / Paul, Keryn I.; England, Jacqueline R.; Baker, Thomas G.; Cunningham, Shaun C.; Perring, Michael P.; Polglase, Phil J.; Wilson, Brian; Cavagnaro, Timothy R.; Lewis, Tom; Read, Zoe; Madhavan, Dinesh B.; Herrmann, Tim.

In: Science of the Total Environment, Vol. 615, 15.02.2018, p. 348-359.

Research output: Contribution to journalArticle

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AU - Paul,Keryn I.

AU - England,Jacqueline R.

AU - Baker,Thomas G.

AU - Cunningham,Shaun C.

AU - Perring,Michael P.

AU - Polglase,Phil J.

AU - Wilson,Brian

AU - Cavagnaro,Timothy R.

AU - Lewis,Tom

AU - Read,Zoe

AU - Madhavan,Dinesh B.

AU - Herrmann,Tim

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N2 - 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.

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