Simulation of greenhouse gases following land‐use change to bioenergy crops using the ECOSSE model: a comparison between site measurements and model predictions. Issue 5 (5th November 2015) - Dondini, Marta; Richards, Mark I. A.; Pogson, Mark; McCalmont, Jon; Drewer, Julia; Marshall, Rachel; Morrison, Ross; Yamulki, Sirwan; Harris, Zoe M.; Alberti, Giorgio; Siebicke, Lukas; Taylor, Gail; et al.
Abstract: This article evaluates the suitability of the ECOSSE model to estimate soil greenhouse gas (GHG) fluxes from short rotation coppice willow (SRC‐Willow), short rotation forestry (SRF‐Scots Pine) and Miscanthus after land‐use change from conventional systems (grassland and arable). We simulate heterotrophic respiration ( R h ), nitrous oxide (N2 O) and methane (CH4 ) fluxes at four paired sites in the UK and compare them to estimates of R h derived from the ecosystem respiration estimated from eddy covariance (EC) and R h estimated from chamber (IRGA) measurements, as well as direct measurements of N2 O and CH4 fluxes. Significant association between modelled and EC‐derived R h was found under Miscanthus, with correlation coefficient ( r ) ranging between 0.54 and 0.70. Association between IRGA‐derived R h and modelled outputs was statistically significant at the Aberystwyth site ( r  =   0.64), but not significant at the Lincolnshire site ( r  =   0.29). At all SRC‐Willow sites, significant association was found between modelled and measurement‐derived R h (0.44 ≤  r  ≤   0.77); significant error was found only for the EC‐derived R h at the Lincolnshire site. Significant association and no significant error were also found for SRF‐Scots Pine and perennial grass. For the arable fields, the modelled CO2 correlated well just with the IRGA‐derived R h at one site ( r  =   0.75). No bias in the model was found at any site, regardless of the measurement type used for the model evaluation. Across all land uses, fluxes of CH4 and N2 O were shown to represent a small proportion of the total GHG balance; these fluxes have been modelled adequately on a monthly time‐step. This study provides confidence in using ECOSSE for predicting the impacts of future land use on GHG balance, at site level as well as at national level.