Forest soil carbon stock estimates in a nationwide inventory: evaluating performance of the ROMULv and Yasso07 models in Finland (original) (raw)
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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.
The Science of the total environment, 2017
Accurate carbon-balance accounting in forest soils is necessary for the development of climate change policy. However, changes in soil organic carbon (SOC) occur slowly and these changes may not be captured through repeated soil inventories. Simulation models may be used as alternatives to SOC measurement. The Yasso07 model presents a suitable alternative because most of the data required for the application are readily available in countries with common forest surveys. In this study, we test the suitability of Yasso07 for simulating SOC stocks and stock changes in a variety of European forests affected by different climatic, land use and forest management conditions and we address country-specific cases with differing resources and data availability. The simulated SOC stocks differed only slightly from measured data, providing realistic, reasonable mean SOC estimations per region or forest type. The change in the soil carbon pool over time, which is the target parameter for SOC rep...
Are Swedish forest soils sinks or sources for CO2—model analyses based on forest inventory data
Biogeochemistry, 2008
Forests soils should be neither sinks nor sources of carbon in a long-term perspective. From a Swedish perspective the time since the last glaciation has probably not been long enough to reach a steady state, although changes are currently very slow. In a shorter perspective, climatic and management changes over the past 100 years have probably created imbalances between litter input to soils and organic carbon mineralisation. Using extant data on forest inventories, we applied models to analyse possible changes in the carbon stocks of Swedish forest soils. The models use tree stocks to provide estimates of tree litter production, which are fed to models of litter decomposition and from which carbon stocks are calculated. National soil carbon stocks were estimated to have increased by 3 Tg yr -1 or 12-13 g m -2 yr -1 in the period 1926-2000 and this increase will continue because soil stocks are far from equilibrium with current litter inputs. The figure obtained is likely to be an underestimation because wet sites store more carbon than predicted here and the inhibitory effect of nitrogen deposition on soil carbon mineralisation was neglected. Knowledge about site history prior to the calculation period determines the accuracy of current soil carbon stocks estimates, although changes can be more accurately estimated.
Forest Ecology and Management, 2006
Growing stocks of trees in Europe have increased in a magnitude that is significant in terms of carbon (C) sink strength. Estimates of the soil C sink strength that this increased stock of trees may have induced on a regional scale are scarce, uncertain and difficult to compare. This illustrates the need for a widely applicable calculation method. Here, we calculate a C budget of productive forest in southeast Norway based on forest inventory information, biomass expansion factors (BEF), biomass turnover rates and the dynamic soil model Yasso. We estimate a 29% increase (112-145 Tg) of C in biomass between 1971 and 2000, and estimate the associated increase of C in soils (including dead wood) to be 4.5% (181-189 Tg). The C sink strengths in biomass and soils (including dead wood) in 1990 are 0.38 and 0.08 Mg ha À1 yr À1 , respectively. Estimated soil C density is 58 Mg C ha À1 or ca 40% of measured soil C density in Norwegian forest soils. A sensitivity analysis -using uncertainty estimates of model inputs and parameters based on empirical data -shows that the underestimation of the soil C stock can be due to overestimation of decomposition rates of recalcitrant organic matter in the soil model and to including only trees as a source of litter. However, uncertainty in these two factors is shown to have a minimal effect on soil sink estimates. The key uncertainty in the soil sink is the initial value of the soil C stock, i.e. the assumed steady state soil C stock at the start of the time series in 1970. However, this source of uncertainty is reduced in importance for when approaching the end of the data series. This indicates that a longer time series of forest inventory data will decrease the uncertainty in the soil sink estimate due to initialisation of the soil C stock. Other, less significant, sources of uncertainty in estimates of soil stock and sink are BEF for fine roots and turnover rates of fine roots and foliage. The used method for calculation of a forest C budget can be readily applied to other regions for which similar forest resource data are available. #
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.
Forest Ecology and Management, 2003
We have used a combination of conventional forest yield tables and a theory for carbon cycles to analyse consequences of climatic change and changes in forest management for carbon stores in Swedish forest soils. The yield tables provide us, for different forest stands, with growth and litter production, which are then fed into a decomposition model from which time series of soil carbon development are obtained. The decomposition model is developed on the basis of the continuous-quality theory and takes into account effects of temperature and substrate quality differences.
Carbon stock in litter and organic soil in drained and naturally wet forest lands in Latvia
Research for Rural Development, 2020
The aim of the study is to evaluate carbon stock in litter and organic forest soils in Latvia as well as to characterize accumulation of carbon in litter in afforested lands. The study is providing empirically valid information about soil and litter carbon changes for the National greenhouse gas (GHG) inventory by using data from National forest inventory (NFI), forest soil monitoring demonstration project BioSoil and other studies. The study proves significance of organic forest soil carbon pool in Latvia and demonstrates necessity to extend NFI incorporated forest soil monitoring program to improve data on soil density in wet organic soils, as well as to integrate data characterizing water regime in forests. The acquired data also proves that the conservative approach of calculation of carbon stock changes in litter in afforested lands applied in the Latvia's National GHG inventory avoids overestimation of CO 2 removals. The data on litter carbon stock collected in this study is sufficient to estimate total carbon stock for stands dominated by most common tree species and long term impact of changes of species composition. Measurements of organic soil and litter thickness should be continued by NFI and integrated with more detailed soil monitoring to increase accuracy of carbon stock estimates and gather data necessary for verification of modelling data, particularly in afforested lands and due to change of dominant species.
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.