Simulation of greenhouse gases following land‐use change to bioenergy crops using the ECOSSE model: a comparison between site measurements and model predictions

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 landuse change from conventional systems (grassland and arable). We simulate heterotrophic respiration (R h ), nitrous oxide (N 2 O) and methane (CH 4 ) 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 N 2 O and CH 4 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 CO 2 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 CH 4 and N 2 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.

Greenhouse gas emissions from the energy crop oilseed rape (Brassica napus); the role of photosynthetically active radiation in diurnal N2O flux variation

“…As C availability drives denitrification both directly (Firestone & Davidson, 1989) and indirectly as increased microbial respiration depletes O 2 (Farquharson & Baldock, 2008), it is logical that by mediating exuded photosynthate PAR strongly influences N 2 O emission when vegetation is present. N 2 O fluxes are notoriously difficult to model, especially at fine temporal resolution (Fitton et al, 2014b), and although the models, DNDC (Abdalla et al, 2009), DailyDayCent (Fitton et al, 2014a) and ECOSSE (Dondini et al, 2016), include various estimates of SOC, they also do not use PAR as a driving input. However, we have not found any explanatory models of measured N 2 O fluxes which use PAR, whilst soil organic carbon (SOC) or dissolved organic carbon (DOC) has only occasionally been used to explain N 2 O fluxes from soils (e.g.…”

Measured and modelled effect of land‐use change from temperate grassland to Miscanthus on soil carbon stocks after 12 years

“…Due to the limited number of long‐term empirical studies of land use conversion into energy crops, a number of models have been used to estimate changes in SOC (Robertson, Davies, Smith, Dondini, & McNamara, ). ECOSSE (Estimation of Carbon in Organic Soils: Sequestration and Emissions) is a process‐based model that has been successfully tested and used for simulating SOC under perennial energy crops including grassland and Miscanthus in this UK region (Dondini et al, ; Dondini, Richards,Pogson, Jones, et al, ; Dondini, Richards, Pogson, McCalmont, et al, ). However, empirical baseline data of SOC stocks in LUC from grassland to Miscanthus, coupled with data of SOC stocks under the mature crop (over 10 years old) would provide further model validation.…”

High‐resolution spatial modelling of greenhouse gas emissions from land‐use change to energy crops in the United Kingdom

“…Shaded areas show the 95% confidence interval of the distribution of modelled results (due to spatial variation) from the simulations across the United Kingdom. Error bars show the 95% confidence interval of estimated error based on the comparison of modelled and measured net GHG balance from site‐level modelling studies (Dondini et al ., , ,b). The red portion of each panel shows a net GHG emission, the green portion shows a net GHG sink.…”

“…Uncertainty arising from the model was estimated as part of the site‐specific modelling exercise reported in Dondini et al . (, ,b). Here, we focus on uncertainties arising from the use of national scale data.…”

“…The ECOSSE model has been thoroughly evaluated and shown to simulate SOC change, N 2 O and CH 4 emissions reliably, for bioenergy crop transitions in the United Kingdom using field data from Miscanthus , SRC and SRF field sites, as described in Dondini et al ., , ,b).…”