To predict the response of C-rich soils to external change, models are needed that accurately reflect the conditions of these soils. Estimation of Carbon in Organic Soils -Sequestration and Emissions (ECOSSE) is a model that allows simulations of soil C and N turnover in both mineral and organic soils using only the limited meteorological, land-use and soil data that is available at the national scale. Because it is able to function at field as well as national scales if appropriate input data are used, field-scale evaluations can be used to determine uncertainty in national simulations. Here we present an evaluation of the uncertainty expected in national-scale simulations of Scotland, using data from the National Soil Inventory of Scotland. This data set provides measurements of C change for the range of soils, climates and land-use types found across Scotland. The simulated values show a high degree of association with the measurements in both total C and change in C content of the soil. Over all sites where land-use change occurred, the average deviation between the simulated and measured values of percentage change in soil C was less than the experimental error (11% simulation error, 53% measurement error). This suggests that the uncertainty in the national-scale simulations will be ~11%. Only a small bias in the simulations was observed compared to the measured values, suggesting that a small underestimate of the change in soil C should be expected at the national scale (-4%).

Abstract. Remote sensing and inverse modelling studies indicate that the tropics emit more CH 4 and N 2 O than predicted by bottom-up emissions inventories, suggesting that terrestrial sources are stronger or more numerous than previously thought. Tropical uplands are a potentially large and important source of CH 4 and N 2 O often overlooked by past empirical and modelling studies. To address this knowledge gap, we investigated spatial, temporal and environmental trends in soil CH 4 and N 2 O fluxes across a long elevation gradient (600-3700 m a.s.l.) in the Kosñi-pata Valley, in the southern Peruvian Andes, that experiences seasonal fluctuations in rainfall. The aim of this work was to produce preliminary estimates of soil CH 4 and N 2 O fluxes from representative habitats within this region, and to identify the proximate controls on soil CH 4 and N 2 O dynamics. Area-weighted flux calculations indicated that ecosystems across this altitudinal gradient were both atmospheric sources and sinks of CH 4 on an annual basis. Montane grasslands (3200-3700 m a.s.l.) were strong atmospheric sources, emitting 56.94 ± 7.81 kg CH 4 -C ha −1 yr −1 . Upper montane forest (2200-3200 m a.s.l.) and lower montane forest (1200-2200 m a.s.l.) were net atmospheric sinks (−2.99 ± 0.29 and −2.34 ± 0.29 kg CH 4 -C ha −1 yr −1 , respectively); while premontane forests (600-1200 m a.s.l.) fluctuated between source or sink depending on the season (wet season: 1.86 ± 1.50 kg CH 4 -C ha −1 yr −1 ; dry season: −1.17 ± 0.40 kg CH 4 -C ha −1 yr −1 ). Analysis of spatial, temporal and environmental trends in soil CH 4 flux across the study site suggest that soil redox was a dominant control on net soil CH 4 flux. Soil CH 4 emissions were greatest from habitats, landforms and during times of year when soils were suboxic, and soil CH 4 efflux was inversely correlated with soil O 2 concentration (Spearman's ρ = −0.45, P < 0.0001) and positively correlated with water-filled pore space (Spearman's ρ = 0.63, P < 0.0001). Ecosystems across the region were net atmospheric N 2 O sources. Soil N 2 O fluxes declined with increasing elevation; area-weighted flux calculations indicated that N 2 O emissions from premontane forest, lower montane forest, upper montane forest and montane grasslands averaged 2.23 ± 1.31, 1.68 ± 0.44, 0.44 ± 0.47 and 0.15 ± 1.10 kg N 2 O-N ha −1 yr −1 , respectively. Soil N 2 O fluxes from premontane and lower montane forests exceeded prior model predictions for the region. Comprehensive investigation of field and laboratory data collected in this study suggest that soil N 2 O fluxes from this region were primarily driven by denitrification; that nitrate (NO

We implemented a spatial application of a previously evaluated model of soil GHG emissions, ECOSSE, in the United Kingdom to examine the impacts to 2050 of land-use transitions from existing land use, rotational cropland, permanent grassland or woodland, to six bioenergy crops; three 'first-generation' energy crops: oilseed rape, wheat and sugar beet, and three 'second-generation' energy crops: Miscanthus, short rotation coppice willow (SRC) and short rotation forestry poplar (SRF). Conversion of rotational crops to Miscanthus, SRC and SRF and conversion of permanent grass to SRF show beneficial changes in soil GHG balance over a significant area. Conversion of permanent grass to Miscanthus, permanent grass to SRF and forest to SRF shows detrimental changes in soil GHG balance over a significant area. Conversion of permanent grass to wheat, oilseed rape, sugar beet and SRC and all conversions from forest show large detrimental changes in soil GHG balance over most of the United Kingdom, largely due to moving from uncultivated soil to regular cultivation. Differences in net GHG emissions between climate scenarios to 2050 were not significant. Overall, SRF offers the greatest beneficial impact on soil GHG balance. These results provide one criterion for selection of bioenergy crops and do not consider GHG emission increases/decreases resulting from displaced food production, bio-physical factors (e.g. the energy density of the crop) and socio-economic factors (e.g. expenditure on harvesting equipment). Given that the soil GHG balance is dominated by change in soil organic carbon (SOC) with the difference among Miscanthus, SRC and SRF largely determined by yield, a target for management of perennial energy crops is to achieve the best possible yield using the most appropriate energy crop and cultivar for the local situation.

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.

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