Evaluation of the ECOSSE model for simulating soil carbon under short rotation forestry energy crops in Britain

Marta Dondini (Corresponding Author), Edward Owen Jones, Mark Lee Andrew Richards, Mark Alexander Pogson, Rebecca Rowe, Aidan Keith, Mike Perks, Niall McNamara, Joanne Ursula Smith, Peter Smith

Research output: Contribution to journalArticle

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Abstract

Understanding and predicting the effects of land-use change to short rotation forestry (SRF) on soil carbon (C) is an important requirement for fully assessing the C mitigation potential of SRF as a bioenergy crop. There is little current knowledge of SRF in the UK and in particular a lack of consistent measured data sets on the direct impacts of land use change on soil C stocks. The ECOSSE model was developed to simulate soil C dynamics and greenhouse gas (GHG) emissions in mineral and organic soils. The ECOSSE model has already been applied spatially to simulate land-use change impacts on soil C and GHG emissions. However, it has not been extensively evaluated under SRF. Eleven sites comprising 29 transitions in Britain, representing land-use change from nonwoodland land uses to SRF, were selected to evaluate the performance of ECOSSE in predicting soil C and soil C change in SRF plantations. The modelled C under SRF showed a strong correlation with the soil C measurements at both 0–30 cm (R = 0.93) and 0–100 cm soil depth (R = 0.82). As for the SRF plots, the soil C at the reference sites have been accurately simulated by the model. The extremely high correlation for the reference fields (R ≥ 0.99) shows a good performance of the model spin-up. The statistical analysis of the model performance to simulate soil C and soil C changes after land-use change to SRF highlighted the absence of significant error between modelled and measured values as well as the absence of significant bias in the model. Overall, this evaluation reinforces previous studies on the ability of ECOSSE to simulate soil C and emphasize its accuracy to simulate soil C under SRF plantations.
Original languageEnglish
Pages (from-to)527–540
Number of pages14
JournalGlobal Change Biology. Bioenergy
Volume7
Issue number3
Early online date20 Jan 2014
DOIs
Publication statusPublished - May 2015

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energy crop
Forestry
energy crops
soil carbon
Crops
United Kingdom
forestry
Soils
Carbon
carbon
soil
Land use
land use change
plantation forestry
greenhouse gas emissions
greenhouse gas
evaluation
Gas emissions
Greenhouse gases
bioenergy

Keywords

  • ECOSSE model
  • energy crops
  • land-use change
  • Process-based model
  • short-rotation forestry
  • soil carbon

Cite this

Evaluation of the ECOSSE model for simulating soil carbon under short rotation forestry energy crops in Britain. / Dondini, Marta (Corresponding Author); Jones, Edward Owen; Richards, Mark Lee Andrew; Pogson, Mark Alexander; Rowe, Rebecca; Keith, Aidan; Perks, Mike; McNamara, Niall; Smith, Joanne Ursula; Smith, Peter.

In: Global Change Biology. Bioenergy, Vol. 7, No. 3, 05.2015, p. 527–540.

Research output: Contribution to journalArticle

Dondini, Marta ; Jones, Edward Owen ; Richards, Mark Lee Andrew ; Pogson, Mark Alexander ; Rowe, Rebecca ; Keith, Aidan ; Perks, Mike ; McNamara, Niall ; Smith, Joanne Ursula ; Smith, Peter. / Evaluation of the ECOSSE model for simulating soil carbon under short rotation forestry energy crops in Britain. In: Global Change Biology. Bioenergy. 2015 ; Vol. 7, No. 3. pp. 527–540.
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abstract = "Understanding and predicting the effects of land-use change to short rotation forestry (SRF) on soil carbon (C) is an important requirement for fully assessing the C mitigation potential of SRF as a bioenergy crop. There is little current knowledge of SRF in the UK and in particular a lack of consistent measured data sets on the direct impacts of land use change on soil C stocks. The ECOSSE model was developed to simulate soil C dynamics and greenhouse gas (GHG) emissions in mineral and organic soils. The ECOSSE model has already been applied spatially to simulate land-use change impacts on soil C and GHG emissions. However, it has not been extensively evaluated under SRF. Eleven sites comprising 29 transitions in Britain, representing land-use change from nonwoodland land uses to SRF, were selected to evaluate the performance of ECOSSE in predicting soil C and soil C change in SRF plantations. The modelled C under SRF showed a strong correlation with the soil C measurements at both 0–30 cm (R = 0.93) and 0–100 cm soil depth (R = 0.82). As for the SRF plots, the soil C at the reference sites have been accurately simulated by the model. The extremely high correlation for the reference fields (R ≥ 0.99) shows a good performance of the model spin-up. The statistical analysis of the model performance to simulate soil C and soil C changes after land-use change to SRF highlighted the absence of significant error between modelled and measured values as well as the absence of significant bias in the model. Overall, this evaluation reinforces previous studies on the ability of ECOSSE to simulate soil C and emphasize its accuracy to simulate soil C under SRF plantations.",
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note = "Acknowledgements This work contributes to the ELUM (Ecosystem Land Use Modelling & Soil Carbon GHG Flux Trial) project, which was commissioned and funded by the Energy Technologies Institute (ETI). We acknowledge the E-OBS data set from the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com) and the data providers in the ECA&D project (http://www.ecad.eu). Pete Smith is a Royal Society-Wolfson Research Merit Award holder",
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N1 - Acknowledgements This work contributes to the ELUM (Ecosystem Land Use Modelling & Soil Carbon GHG Flux Trial) project, which was commissioned and funded by the Energy Technologies Institute (ETI). We acknowledge the E-OBS data set from the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com) and the data providers in the ECA&D project (http://www.ecad.eu). Pete Smith is a Royal Society-Wolfson Research Merit Award holder

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N2 - Understanding and predicting the effects of land-use change to short rotation forestry (SRF) on soil carbon (C) is an important requirement for fully assessing the C mitigation potential of SRF as a bioenergy crop. There is little current knowledge of SRF in the UK and in particular a lack of consistent measured data sets on the direct impacts of land use change on soil C stocks. The ECOSSE model was developed to simulate soil C dynamics and greenhouse gas (GHG) emissions in mineral and organic soils. The ECOSSE model has already been applied spatially to simulate land-use change impacts on soil C and GHG emissions. However, it has not been extensively evaluated under SRF. Eleven sites comprising 29 transitions in Britain, representing land-use change from nonwoodland land uses to SRF, were selected to evaluate the performance of ECOSSE in predicting soil C and soil C change in SRF plantations. The modelled C under SRF showed a strong correlation with the soil C measurements at both 0–30 cm (R = 0.93) and 0–100 cm soil depth (R = 0.82). As for the SRF plots, the soil C at the reference sites have been accurately simulated by the model. The extremely high correlation for the reference fields (R ≥ 0.99) shows a good performance of the model spin-up. The statistical analysis of the model performance to simulate soil C and soil C changes after land-use change to SRF highlighted the absence of significant error between modelled and measured values as well as the absence of significant bias in the model. Overall, this evaluation reinforces previous studies on the ability of ECOSSE to simulate soil C and emphasize its accuracy to simulate soil C under SRF plantations.

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