Publication Date:
2017-03-22
Description:
This paper aims to evaluate the suitability of the ECOSSE model to estimate soil heterotrophic respiration (R h ) from arable land and short rotation coppices of poplar and willow. Between 2011 and 2013, we measured R h with automatic closed dynamic chambers on root exclusion plots at one site in the UK (willow, mixed commercial genotypes of Salix spp.) and two sites in Italy (arable and poplar, Populus × Canadensis Moench, Oudemberg genotype), and compared these measured fluxes to simulated values of R h with the ECOSSE model. Correlation coefficients ( r ) between modelled and measured monthly R h data were strong and significant, with a range between 0.81 and 0.96 for all three types of vegetation. There was no significant error and bias in the model for any site. The model was able to predict seasonal trends in R h at all three sites even though it occasionally underestimated the flux values during warm weather in spring and summer. Because of the strong correlation between the measured and modelled values, it is unlikely that underestimation of the flux is the result of missing processes in the model. Therefore, further detailed monitoring of R h is needed to modify the model. In this research, a limited set of input data was used to simulate R h at the three sites. Nevertheless, overall results of the model evaluation suggest that the ECOSSE model simulates soil R h adequately under all land uses tested and that continuous and direct measurements (such as automatic chambers installed on root-exclusion plots) are a useful tool to test model performance to simulate R h at the site level. Highlights Model evaluation is crucial to predict soil carbon balance accurately. Modelled and measured heterotrophic respiration were compared for three land uses. The model performed well statistically for all three vegetation types. Modelled heterotrophic respiration should be evaluated by comparison to continuous measurements.
Print ISSN:
1351-0754
Electronic ISSN:
1365-2389
Topics:
Geosciences
,
Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
Permalink
