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Articles containing the keyword 'soil carbon'.

Category: Research article

article id 1628, category Research article
Jürgen Aosaar, Ülo Mander, Mats Varik, Hardo Becker, Gunnar Morozov, Martin Maddison, Veiko Uri. (2016). Biomass production and nitrogen balance of naturally afforested silver birch (Betula pendula Roth.) stand in Estonia. Silva Fennica vol. 50 no. 4 article id 1628. https://doi.org/10.14214/sf.1628
Highlights: Leafless aboveground biomass of the 17-year-old natural silver birch stand growing in abandoned agricultural land reached 94 Mg ha–1; The largest fluxes in N budget were net nitrogen mineralization and gaseous N2-N emission; Nitrogen leaching was low; Soil N content increased with the stand age, soil C content remained stable; N2O and N2 fluxes in boreal deciduous forest were analysed.

Silver birch (Betula pendula Roth.) is one of the main pioneer tree species occupying large areas of abandoned agricultural lands under natural succession in Estonia. We estimated aboveground biomass (AGB) dynamics during 17 growing seasons, and analysed soil nitrogen (N) and carbon (C) dynamics for 10 year period in a silver birch stand growing on former arable land. Main N fluxes were estimated and nitrogen budget for 10-year-old stand was compiled. The leafless AGB and stem mass of the stand at the age of 17-years were 94 and 76 Mg ha–1 respectively. The current annual increment (CAI) of stemwood fluctuated, peaking at 10 Mg ha–1 yr–1 at the age of 15 years; the mean annual increment (MAI) fluctuated at around 4–5 Mg ha–1. The annual leaf mass of the stand stabilised at around 3 Mg ha–1 yr–1. The stand density decreased from 11600 to 2700 trees ha–1 in the 8- and 17-year-old stand, respectively. The largest fluxes in N budget were net nitrogen mineralization and gaseous N2-N emission. The estimated fluxes of N2O and N2 were 0.12 and 83 kg ha–1 yr–1, respectively; N leaching was negligible. Nitrogen retranslocation from senescing leaves was approximately 45 kg ha–1, N was mainly retranslocated into stembark. The N content in the upper 0–10 cm soil layer increased significantly (145 kg ha–1) from 2004 to 2014; soil C content remained stable. Both the woody biomass dynamics and the N cycling of the stand witness the potential for bioenergetics of such ecosystems.

  • Aosaar, Estonian University of Life Sciences, Institute of Forestry and Rural Engineering, Kreutzwaldi 1, 51014 Tartu, Estonia ORCID ID:E-mail: jyrgen.aosaar@emu.ee (email)
  • Mander, University of Tartu, Institute of Ecology and Earth Sciences, Ülikooli 18, 50090 Tartu, Estonia ORCID ID:E-mail: ulo.mander@ut.ee
  • Varik, Estonian University of Life Sciences, Institute of Forestry and Rural Engineering, Kreutzwaldi 1, 51014 Tartu, Estonia ORCID ID:E-mail: mats.varik@emu.ee
  • Becker, Estonian University of Life Sciences, Institute of Forestry and Rural Engineering, Kreutzwaldi 1, 51014 Tartu, Estonia ORCID ID:E-mail: hardo.becker@emu.ee
  • Morozov, Estonian University of Life Sciences, Institute of Forestry and Rural Engineering, Kreutzwaldi 1, 51014 Tartu, Estonia ORCID ID:E-mail: gunnar.morozov@emu.ee
  • Maddison, University of Tartu, Institute of Ecology and Earth Sciences, Ülikooli 18, 50090 Tartu, Estonia ORCID ID:E-mail: martin.maddison@ut.ee
  • Uri, Estonian University of Life Sciences, Institute of Forestry and Rural Engineering, Kreutzwaldi 1, 51014 Tartu, Estonia ORCID ID:E-mail: veiko.uri@emu.ee
article id 935, category Research article
Loice M. A. Omoro, Mike Starr, Petri K. E. Pellikka. (2013). Tree biomass and soil carbon stocks in indigenous forests in comparison to plantations of exotic species in the Taita Hills of Kenya. Silva Fennica vol. 47 no. 2 article id 935. https://doi.org/10.14214/sf.935
Carbon (C) densities of the tree biomass and soil (0–50 cm) in indigenous forest and plantations of eucalyptus, cypress and pine in the Taita Hills, Kenya were determined and compared. The cypress and pine plantations were about 30-years-old and eucalyptus plantations about 50-years-old. Biomass C densities were estimated from breast height diameter and wood density using allometric functions developed for tropical species and an assumed C content of 50%. Belowground biomass C densities were estimated using root:shoot biomass ratios. Soil organic C (SOC) densities were calculated from measured organic carbon contents (0–20 and 20–50 cm layers) and modelled bulk density values. Mean total biomass C and SOC densities for indigenous forest were greater than those of the plantations, and the difference was significant (p < 0.05) in the cases of cypress and pine biomass and pine SOC. The correlation between biomass C and SOC densities was nearly significant in the case of indigenous forest, but negative. Biomass C densities were not significantly correlated with mean annual precipitation, mean annual temperature or potential evapotranspiration, but pine biomass C densities were significantly correlated to actual evapotranspiration. SOC densities were more strongly correlated to mean annual precipitation than biomass C densities, but only significantly so in the case of pine. Neither biomass C nor SOC densities were correlated to plant available water capacity of the soil. Indigenous forest SOC densities were significantly correlated to soil clay contents, but negatively. Indigenous forests sequester more C in biomass and soil than do 30 to 50-year-old plantations of exotics, but it remains unclear if this is an intrinsic difference between indigenous forest and plantations of exotics or because of insufficient time for SOC levels in plantations to recover after clearance of original indigenous forest.
  • Omoro, Viikki Tropical Resources Institute, Department of Forest Sciences, P.O. Box 27 (Latokartanonkaari 7), FI-00014 University of Helsinki, Finland ORCID ID:E-mail: loice.omoro@helsinki.fi
  • Starr, Department of Forest Sciences, P. O. Box 27 (Latokartanonkaari 7), FI-00014 University of Helsinki, Finland ORCID ID:E-mail: mike.starr@helsinki.fi (email)
  • Pellikka, Department of Geosciences and Geography, P. O. Box 64 (Gustaf Hällströminkatu 2), FI-00014 University of Helsinki, Finland ORCID ID:E-mail: petri.pellikka@helsinki.fi
article id 159, category Research article
Johan Stendahl, Maj-Britt Johansson, Erik Eriksson, Åke Nilsson, Ola Langvall. (2010). Soil organic carbon in Swedish spruce and pine forests – differences in stock levels and regional patterns. Silva Fennica vol. 44 no. 1 article id 159. https://doi.org/10.14214/sf.159
The selection of tree species is one factor to consider if we want to mitigate carbon dioxide emissions to the atmosphere through forest management. The objectives of this study were to estimate the differences in soil organic carbon (SOC) stocks under Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.) forests and to examine causes of differences in the accumulation of carbon in the forest soil. Large-scale inventory data was used to quantify variations in SOC stock in relation to stand type and the accumulation of carbon for spruce and pine stands was analysed by simulation. Based on field data, the national mean SOC stock was 9.2 kg m–2 in spruce dominated stands and 5.7 kg m–2 in pine dominated stands. For both species, the SOC stock, measured in the field inventory, increased significantly with increasing temperature, although at different rates. The SOC stock was larger for spruce under all temperature conditions, but the difference between species diminished with increasing temperature. The simulations indicated that the build-up of SOC over several rotations was 22% higher in spruce stands than in pine stands under similar environmental conditions. The main difference was found to be the greater input of harvest residues for spruce. Further, the simulations showed that ground vegetation contributed considerably more to the litter production under pine than under spruce. On sites where both Scots pine and Norway spruce are considered suitable, the latter should be selected if the aim of the forest management policy is to maximize the accumulation of SOC in the forest. Further, spruce is more favourable for SOC accumulation in areas with cold temperatures and on sites with low productivity.
  • Stendahl, Department of Soil and Environment, P.O. Box 7001, Swedish University of Agricultural Sciences, SE-75007 Uppsala, Sweden ORCID ID:E-mail: johan.stendahl@mark.slu.se (email)
  • Johansson, Department of Soil and Environment, P.O. Box 7001, Swedish University of Agricultural Sciences, SE-75007 Uppsala, Sweden ORCID ID:E-mail:
  • Eriksson, Department of Energy and Technology, P.O. Box 7061, Swedish University of Agricultural Sciences, SE-75007 Uppsala, Sweden ORCID ID:E-mail:
  • Nilsson, Department of Soil and Environment, P.O. Box 7001, Swedish University of Agricultural Sciences, SE-75007 Uppsala, Sweden ORCID ID:E-mail:
  • Langvall, Unit for Field-based Forest Research, Asa Experimental Forest and Research Station, Swedish University of Agricultural Sciences, SE-36030 Lammhult, Sweden ORCID ID:E-mail:

Category: Special section

article id 290, category Special section
Mikko Peltoniemi, Esther Thürig, Stephen Ogle, Taru Palosuo, Marion Schrumpf, Thomas Wutzler, Klaus Butterbach-Bahl, Oleg Chertov, Alexander Komarov, Aleksey Mikhailov, Annemieke Gärdenäs, Charles Perry, Jari Liski, Pete Smith, Raisa Mäkipää. (2007). Models in country scale carbon accounting of forest soils. Silva Fennica vol. 41 no. 3 article id 290. https://doi.org/10.14214/sf.290
Countries need to assess changes in the carbon stocks of forest soils as a part of national greenhouse gas (GHG) inventories under the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol (KP). Since measuring these changes is expensive, it is likely that many countries will use alternative methods to prepare these estimates. We reviewed seven well-known soil carbon models from the point of view of preparing country-scale soil C change estimates. We first introduced the models and explained how they incorporated the most important input variables. Second, we evaluated their applicability at regional scale considering commonly available data sources. Third, we compiled references to data that exist for evaluation of model performance in forest soils. A range of process-based soil carbon models differing in input data requirements exist, allowing some flexibility to forest soil C accounting. Simple models may be the only reasonable option to estimate soil C changes if available resources are limited. More complex models may be used as integral parts of sophisticated inventories assimilating several data sources. Currently, measurement data for model evaluation are common for agricultural soils, but less data have been collected in forest soils. Definitions of model and measured soil pools often differ, ancillary model inputs require scaling of data, and soil C measurements are uncertain. These issues complicate the preparation of model estimates and their evaluation with empirical data, at large scale. Assessment of uncertainties that accounts for the effect of model choice is important part of inventories estimating large-scale soil C changes. Joint development of models and large-scale soil measurement campaigns could reduce the inconsistencies between models and empirical data, and eventually also the uncertainties of model predictions.
  • Peltoniemi, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: mikko.peltoniemi@metla.fi (email)
  • Thürig, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland; European Forest Institute, Joensuu, Finland ORCID ID:E-mail:
  • Ogle, Natural Resources Ecology Laboratory, Colorado State University, Fort Collins, USA ORCID ID:E-mail:
  • Palosuo, European Forest Institute, Joensuu, Finland ORCID ID:E-mail:
  • Schrumpf, Max-Planck-Institute for Biogeochemistry, Jena, Germany ORCID ID:E-mail:
  • Wutzler, Max-Planck-Institute for Biogeochemistry, Jena, Germany ORCID ID:E-mail:
  • Butterbach-Bahl, Institute for Meteorology and Climate Research, Forschungszentrum Karlsruhe GmbH, Garmisch-Partenkirchen, Germany ORCID ID:E-mail:
  • Chertov, St. Petersburg State University, St. Petersburg-Peterhof, Russia ORCID ID:E-mail:
  • Komarov, Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy of Sciences, Pushchino, Russia ORCID ID:E-mail:
  • Mikhailov, Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy of Sciences, Pushchino, Russia ORCID ID:E-mail:
  • Gärdenäs, Dept. of Soil Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden ORCID ID:E-mail:
  • Perry, USDA Forest Service, Northern Research Station, St. Paul, MN USA ORCID ID:E-mail:
  • Liski, Finnish Environment Institute, Helsinki, Finland ORCID ID:E-mail:
  • Smith, School of Biological Sciences, University of Aberdeen, Aberdeen, UK ORCID ID:E-mail:
  • Mäkipää, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: raisa.makipaa@metla.fi
article id 289, category Special section
Thomas Wutzler, Martina Mund. (2007). Modelling mean above and below ground litter production based on yield tables. Silva Fennica vol. 41 no. 3 article id 289. https://doi.org/10.14214/sf.289
Estimates of litter production are a prerequisite for modeling soil carbon stocks and its changes at regional to national scale. However, the required data on biomass removal is often available only for the recent past. In this study we used yield tables as a source of probable past forest management to drive a single tree based stand growth model. Next, simulated growth and timber volume was converted to tree compartment carbon stocks and biomass turnover. The study explicitly accounted for differences in site quality between stands. In addition we performed a Monte Carlo uncertainty and sensitivity analysis. We exemplify the approach by calculating long-term means of past litter production for 10 species by using yield tables that have been applied in Central Germany during the last century. We found that litter production resulting from harvest residues was almost as large as the one from biomass turnover. Differences in site quality caused large differences in litter production. At a given site quality, the uncertainty in soil carbon inputs were 14%, 17%, and 25% for beech, spruce, and pine stands, respectively. The sensitivity analysis showed that the most influential parameters were associated with foliage biomass and turnover. We conclude that rates of mean past litter production and their uncertainties can reliably be modeled on the basis of yield tables if the model accounts for 1) full rotation length including thinning and final harvest, 2) differences in site quality, and 3) environmental dependency of foliage biomass and foliage turnover.
  • Wutzler, Max Planck Institute for Biogeochemistry, Jena, Germany ORCID ID:E-mail:
  • Mund, Max Planck Institute for Biogeochemistry, Jena, Germany ORCID ID:E-mail:
article id 287, category Special section
Mikko Peltoniemi, Juha Heikkinen, Raisa Mäkipää. (2007). Stratification of regional sampling by model-predicted changes of carbon stocks in forested mineral soils. Silva Fennica vol. 41 no. 3 article id 287. https://doi.org/10.14214/sf.287
Monitoring changes in soil C has recently received interest due to reporting under the Kyoto Protocol. Model-based approaches to estimate changes in soil C stocks exist, but they cannot fully replace repeated measurements. Measuring changes in soil C is laborious due to small expected changes and large spatial variation. Stratification of soil sampling allows the reduction of sample size without reducing precision. If there are no previous measurements, the stratification can be made with model-predictions of target variable. Our aim was to present a simulation-based stratification method, and to estimate how much stratification of inventory plots could improve the efficiency of the sampling. The effect of large uncertainties related to soil C change measurements and simulated predictions was targeted since they may considerably decrease the efficiency of stratification. According to our simulations, stratification can be useful with a feasible soil sample number if other uncertainties (simulated predictions and forecasted forest management) can be controlled. For example, the optimal (Neyman) allocation of plots to 4 strata with 10 soil samples from each plot (unpaired repeated sampling) reduced the standard error (SE) of the stratified mean by 9–34% from that of simple random sampling, depending on the assumptions of uncertainties. When the uncertainties of measurements and simulations were not accounted for in the division to strata, the decreases of SEs were 2–9 units less. Stratified sampling scheme that accounts for the uncertainties in measured material and in the correlates (simulated predictions) is recommended for the sampling design of soil C stock changes.
  • Peltoniemi, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: mikko.peltoniemi@metla.fi (email)
  • Heikkinen, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail:
  • Mäkipää, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: raisa.makipaa@metla.fi

Category: Article

article id 5561, category Article
Jari Liski. (1995). Variation in soil organic carbon and thickness of soil horizons within a boreal forest stand – effect of trees and implications for sampling. Silva Fennica vol. 29 no. 4 article id 5561. https://doi.org/10.14214/sf.a9212

Spatial variation in the density of soil organic carbon (kg/m2) and the thickness of soil horizons (F/H, E) were investigated in a 6 m x 8 m area in Scots pine (Pinus sylvestris L.) stand in Southern Finland for designing an effective sampling for the C density and studying the effect of trees on the variation. The horizon thickness of the podzolized soil were measured on a total of 126 soil cores (50 cm deep) and the C density of the organic F/H and 0–10 cm, 10–20 cm and 20–40 cm mineral soil layers was analysed.

The C density varied 3–5 fold within the layers and the coefficients of variation ranged from 22 % to 40%. Considering the gain in confidence per sample, 8–10 samples were suggested for estimating the mean C density in the F/H and 0–40 cm layers, although about 30 samples are needed for 10% confidence in the mean. The C densities and horizon thicknesses were spatially dependent within the distances of 1–8 m, the spatial dependence accounting for 43–86% of the total variance. The F/H layer was thicker and contained more C within 1–3 m radius from trees. In the 10–20 cm and 20–40 cm layers (B horizon) the C density also increased towards the trees, but more pronouncedly in the immediate vicinity of the stems. Because the spatial patterning of the E horizon thickness was similar, the increase was attributed to stemflow and precipitation of organic compounds in the podzol B horizon.

  • Liski, ORCID ID:E-mail:

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