Towards complete and harmonized assessment of soil carbon stocks and balance in forests: The ability of the Yasso07 model across a wide gradient of climatic and forest conditions in Europe (original) (raw)
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Geoscientific Model Development, 2016
Dynamic soil models are needed for estimating impact of weather and climate change on soil carbon stocks and fluxes. Here, we evaluate performance of Yasso07 and ROMULv models against forest soil carbon stock measurements. More specifically, we ask if litter quantity, litter quality and weather data are sufficient drivers for soil carbon stock estimation. We also test whether inclusion of soil water holding capacity improves reliability of modelled soil carbon stock estimates. Litter input of trees was estimated from stem volume maps provided by the National Forest Inventory, while understorey vegetation was estimated using new biomass models. The litter production rates of trees were based on earlier research, while for understorey biomass they were estimated from measured data. We applied Yasso07 and ROMULv models across Finland and ran those models into steady state; thereafter, measured soil carbon stocks were compared with model estimates. We found that the role of understorey ...
A multi-model comparison of soil carbon assessment of a coniferous forest stand
Environmental Modelling & Software, 2012
We simulated soil carbon stock dynamics of an Austrian coniferous forest stand with five soil-only models (Q, ROMUL, RothC, SoilCO2/RothC and Yasso07) and three plantesoil models (CENTURY, Coup-Model and Forest-DNDC) for an 18-year period and the decomposition of a litter pulse over a 100-year period. The objectives of the study were to assess the consistency in soil carbon estimates applying a multi-model comparison and to present and discuss the sources of uncertainties that create the differences in model results. Additionally, we discuss the applicability of different modelling approaches from the view point of large-scale carbon assessments.
Geoderma, 2015
Soil organic carbon (SOC) stocks in forest floors and in mineral and peat forest soils were estimated at the European scale. The assessment was based on measured C concentration, bulk density, coarse fragments and effective soil depth data originating from 4914 plots in 22 EU countries belonging to the UN/ECE ICP Forests 16 × 16 km Level I network. Plots were sampled and analysed according to harmonized methods during the 2nd European Forest Soil Condition Survey. Using continuous carbon density depth functions, we estimated SOC stocks to 30-cm and 1-m depth, and stratified these stocks according to 22 WRB Reference Soil Groups (RSGs) and 8 humus forms to provide European scale benchmark values. Average SOC stocks amounted to 22.1 t C ha −1 in forest floors, 108 t C ha −1 in mineral soils and 578 t C ha −1 in peat soils, to 1 m depth. Relative to 1-m stocks, the vertical SOC distribution confirmed global patterns reported for forest soils:~50% of SOC was stored in the upper 20 cm, and~55-65% in the upper 30 cm of soil. Assuming 163 Mha of European forest cover and by using various scaling up procedures, we estimated total stocks at 3.50-3.94 Gt C in forest floors and 21.4-22.7 Gt C in mineral and peat soils down to 1-m, which is~40% more than commonly published. The most useful predictors and stratifiers for C stocks were humus form and tree species for the forest floor, RSG for mineral soils and parent material for peat soils. This dataset will be further explored, predominantly for validation of soil C models, resampling and comparison with legacy and future forest SOC inventories.
line 18 and it was made clear that only the biomass vs biomass cover relationship was made using data from 18 stands (a total of 504 of 0.3*0.3 m 2 sample squares), while co-kriging was based on 2501 permanent sample plots with understorey cover measurements. 2. There is only one important point which is not clear so far, the depth of the SOC estimates. I did not find any information about the depth for which SOC was predicted. Sections 2.4.2 and 2.4.3 about Yasso07 & ROMULv models were modified in order to describe how soil depth was defined with models. For Biosoil data this information was given in the section 2.5. 3. From my point of view the structure of those models only allows a prediction for topsoils (0-20 cm), for deeper parts stabilization mechanisms of mineral-associated SOC must be taken into account. At least, model performance should be tested not for the total depth but for different depth increments (e.g. 0-20, 20-40 cm etc.). We agree that models have their strength in estimation of decomposition of litter with varied quality. Both models still have compartments for stabile carbon, but these carbon pools are not depth-specific. In the Yasso07 model this pool is named as "humus" box, while in the ROMULv model this is named as "stabile humus" box (see fig.1). These boxes integrate stabile carbon accumulation from various processes, including that of mineral association. Both models are used in such applications (greenhouse gas inventories, evaluation of the effects of alternative forest management practices) where estimates for deeper soil layers are needed and the models are parametrized accordingly.
A new baseline of organic carbon stock in European agricultural soils using a modelling approach
Global Change Biology, 2014
Proposed European policy in the agricultural sector will place higher emphasis on soil organic carbon (SOC), both as an indicator of soil quality and as a means to offset CO 2 emissions through soil carbon (C) sequestration. Despite detailed national SOC data sets in several European Union (EU) Member States, a consistent C stock estimation at EU scale remains problematic. Data are often not directly comparable, different methods have been used to obtain values (e.g. sampling, laboratory analysis) and access may be restricted. Therefore, any evolution of EU policies on C accounting and sequestration may be constrained by a lack of an accurate SOC estimation and the availability of tools to carry out scenario analysis, especially for agricultural soils. In this context, a comprehensive model platform was established at a pan-European scale (EU + Serbia, Bosnia and Herzegovina, Croatia, Montenegro, Albania, Former Yugoslav Republic of Macedonia and Norway) using the agro-ecosystem SOC model CENTURY. Almost 164 000 combinations of soil-climate-land use were computed, including the main arable crops, orchards and pasture. The model was implemented with the main management practices (e.g. irrigation, mineral and organic fertilization, tillage) derived from official statistics. The model results were tested against inventories from the European Environment and Observation Network (EIONET) and approximately 20 000 soil samples from the 2009 LUCAS survey, a monitoring project aiming at producing the first coherent, comprehensive and harmonized top-soil data set of the EU based on harmonized sampling and analytical methods. The CENTURY model estimation of the current 0-30 cm SOC stock of agricultural soils was 17.63 Gt; the model uncertainty estimation was below 36% in half of the NUTS2 regions considered. The model predicted an overall increase of this pool according to different climate-emission scenarios up to 2100, with C loss in the south and east of the area (involving 30% of the whole simulated agricultural land) compensated by a gain in central and northern regions. Generally, higher soil respiration was offset by higher C input as a consequence of increased CO 2 atmospheric concentration and favourable crop growing conditions, especially in northern Europe. Considering the importance of SOC in future EU policies, this platform of simulation appears to be a very promising tool to orient future policymaking decisions.
Projected changes in mineral soil carbon of European forests, 1990–2100
Canadian Journal of Soil Science, 2006
Forests are a major land use in Europe, and European forest soils contain about the same amount of carbon as is found in tree biomass. Changes in the size of the forest soil carbon pool could have significant impacts on the European carbon budget. We present the first assessment of future changes in European forest soil organic carbon (SOC) stocks using a dedicated process-based SOC model and state-of-the-art databases of driving variables. Soil carbon change was calculated for Europe using the Rothamsted Carbon model using climate data from four climate models, forced by four Intergovernmental Panel on Climate Change (IPCC) emissions scenarios (SRES). Changes in litter input to the soil due to forest management, projected changes in net primary production (NPP), forest age-class structure, and changes in forest area were taken into account. Results are presented for mineral soil only. Under some climate scenarios carbon in forest soils will increase slightly (0.1 to 4.6 Pg) in Euro...
Soil Use and Management, 2010
Six Italian research sites, representative of Mediterranean and mountain forests and equipped with eddy covariance towers, were used in this study to test the performance of the CENTURY 4.5 model in predicting the dynamics of soil organic carbon (SOC) changes during the commitment periods (CP) of the Kyoto Protocol (2008-2012; 2013-2017). We show that changes in SOC stocks over short periods of time are difficult to detect, and explore the potential for models to be used for reporting SOC changes for forests that will remain forests, under Article 3.4 of the Kyoto Protocol. As the eddy covariance flux sites have been active for 10 yr on average, being initiated over the period between 1996 and 1998, the model was evaluated by comparing the modelled SOC stocks with those directly measured at each site in different years. Since long term series of observed values for soil carbon were not available, the validation of other model outputs such as net primary production (NPP) and soil nitrogen stocks, gives some confidence in long term simulations. Once the model performance was evaluated, two climate change scenarios, A1F1 (world markets-fossil fuel intensive) and B2 (local sustainability), were considered for prediction of C stock changes during the commitment periods of the Kyoto Protocol. In general, despite the need to consider the uncertainties in the direct measurements, at each site model fit with measured SOC stocks was good, with the simulated values within the standard deviation of the measurements. In this regard, the similarity between the SOC measured in 2008 and that predicted for the two forthcoming commitment periods points out the difficulty of detecting carbon stock changes by direct measurements, given the closeness in time to the present of the commitment periods. In any case, all sites show positive variations that are possibly related to the fertilization effects of increasing CO 2 and to longer growing seasons, since no change in management occurred. Compared with the SOC measured in 2008, at the end of the second commitment period, the modelled SOC variations were smaller than 2% in the Mediterranean forests and comprised between 2% and 7% in the mountain forests. These variations, although small, indicate it might be possible to statistically detect differences after 10 yr in mountain forests with a reasonable number of samples. In conclusion, this work shows that since SOC stock changes are minimal within both CP, models can be effective tools for estimating future changes in SOC amounts, as an alternative to, or in support of, direct measurements when a short period of time is considered.
Ecological Modelling, 2011
Boreal forest soils such as those in Sweden contain a large active carbon stock. Hence, a relatively small change in this stock can have a major impact on the Swedish national CO 2 balance. Understanding of the uncertainties in the estimations of soil carbon pools is critical for accurately assessing changes in carbon stocks in the national reports to UNFCCC and the Kyoto Protocol. Our objective was to analyse the parameter uncertainties of simulated estimates of the soil organic carbon (SOC) development between 1994 and 2002 in Swedish coniferous forests with the Q model. Both the sensitivity of model parameters and the uncertainties in simulations were assessed. Data of forests with Norway spruce, Scots pine and Lodgepole pine, from the Swedish Forest Soil Inventory (SFSI) were used. Data of 12 Swedish counties were used to calibrate parameter settings; and data from another 11 counties to validate. The "limits of acceptability" within GLUE were set at the 95% confidence interval for the annual, mean measured SOC at county scale. The calibration procedure reduced the parameter uncertainties and reshaped the distributions of the parameters county-specific. The average measured and simulated SOC amounts varied from 60 t C ha −1 in northern to 140 t C ha −1 in the southern Sweden. The calibrated model simulated the soil carbon pool within the limits of acceptability for all calibration counties except for one county during one year. The efficiency of the calibrated model varied strongly; for five out of 12 counties the model estimates agreed well with measurements, for two counties agreement was moderate and for five counties the agreement was poor. The lack of agreement can be explained with the high interannual variability of the down-scaled measured SOC estimates and changes in forest areas over time. We conclude that, although we succeed in reducing the uncertainty in the model estimates, calibrating of a regional scale process-oriented model using a national scale dataset is a sensitive balance between introducing and reducing uncertainties. Parameter distributions showed to be scale sensitive and county specific. Further analysis of uncertainties in the methods used for reporting SOC changes to the UNFCCC and Kyoto protocol is recommended.