Wspólnotowy Serwis Informacyjny Badan i Rozwoju - CORDIS

Uncertainty estimate of the national level biomass and soil carbon stock and stock change

The objective of work package 6.3 ("uncertainty estimate of the national level biomass and soil carbon stock adn stock change") was to estimate the overall uncertainty of carbon stocks and stock changes in forests on the national level when applying the top-down approach. A step-by-step estimation of uncertainty of the improved carbon stock estimates of D6.1 ("improved regional and national level estimates of the carbon stock and stock change of tree biomass for six European countries") and D6.2 ("improved national level estimates of the carbon stock and stock change of the forest soils for six European countries") was carried out for Finland, Sweden, Ireland and Spain using Monte Carlo simulation. The results for Germany and Austria had to be discarded, because erroneous BEFs had been used in the analysis. Unfortunately it was not possible to repeat the uncertainty assessment with the correct input data due to time constraints. In addition, a soil model comparison was conducted to estimate the effect of the choice of the soil carbon model on the overall carbon assessment.

UNCERTAINTY ANALYSIS. A large-scale forest scenario model (EFISCEN) in combination with a dynamic soil model (YASSO) was used to estimate biomass and soil carbon stocks and stock changes. EFISCEN uses aggregated inventory data as input and models the development of forest resources in 5-year time steps. The national forest inventory data used in EFISCEN were gathered around the year 1990 for Finland and Ireland, and around 1995 for Sweden and Spain. Sources of uncertainty that were taken into account in the analysis of biomass were: inventory data, biomass allocation, dry wood density and carbon content.

Simulations of biomass uncertainty were done in two steps:
1) the inventory data was converted into total biomass taking into account the error related to data itself and the error of BEFs; and
2) the total biomass was converted into carbon so that the uncertainty of carbon content was taken into account.

The uncertainty analysis for the stock change from the initial year (1990/1995) to 2010 was done assuming that the data would be based on two inventories - the uncertainty of EFISCEN scenario (i.e. level of thinning and felling, no change in forest area and tree species) was excluded from the analysis since we did not have information about its reliability. The uncertainty was calculated in Monte Carlo simulation by calculating the difference between the stocks of the initial year and 2010 so that the uncertainty of stocks was taken into account. Sources of uncertainty in the soil carbon assessment that were taken into account in the analyses were uncertainty estimates of turnover rates and uncertainty estimates of parameters in the soil carbon model. The soil carbon stocks were assessed with a modelling approach, where biomass estimates of different compartments are converted to litter using compartment-specific turnover rates. This litter is given as input to the YASSO soil model, in which litter decomposition was simulated.

Biomass C stock uncertainty ranged between 2 and 5%. The uncertainty of the biomass C stock change ranged between 11 and 27%, and was dependent on the size of the change. When the biomass C stock change was low, the uncertainty was higher, while a large C stock change resulted in a lower uncertainty. C stocks in the soils were much more uncertain than the biomass C stocks, but the C stock change estimate for the soils were more reliable than the soil C stock assessment. The soil C stock uncertainties were very similar between countries - about 45% - because similar assumptions are made in the soil model. Uncertainties in soil C stock changes were highest in Finland (34%) and ranged between 20 and 23% for Sweden, Ireland and Spain.

SOIL MODEL COMPARISON. This chapter analysed the uncertainty related to model structure and possible bias in the selected soil model based on a comparison of four models - 4C, EFIMOD (with the soil module ROMUL), RothC, and YASSO. The models were compared with respect to the simulated soil carbon pools of four sites in southern Finland, and two sites in southern and northern Germany. Soil carbon pools were compared for the carbon in the organic layer, the mineral soil, and the total soil carbon.

The choice of the model for the assessment of the carbon stock and stock changes in forest soils may considerably influence the uncertainty of the carbon stock assessment. The overall uncertainty due to the selection of simulation tool for the soil carbon assessment at individual sites may be in the same order of magnitude as the uncertainty due to model parameters. The identified differences between models were site and species dependent, and the small number of six study sites with two different litter input time series was not sufficient to generalise the quantitative importance of the uncertainty compared to other sources of uncertainty.

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