Category :
Special section
article id 472,
category
Special section
Raisa Mäkipää,
Jari Liski,
Mats Olsson,
Pete Smith,
Esther Thürig.
(2007).
Workshop on Development of Models and Forest Soil Surveys for Monitoring of Soil Carbon.
Silva Fennica
vol.
41
no.
3
article id 472.
https://doi.org/10.14214/sf.472
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Selected Papers of the Workshop on Development of Models and Forest Soil Surveys for Monitoring of Soil Carbon.
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Mäkipää,
Finnish Forest Research Institute
E-mail:
rm@nn.fi
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Liski,
Finnish Environment Institute, Finland
E-mail:
jl@nn.fi
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Olsson,
Swedish University of Agricultural Sciences, Sweden
E-mail:
mo@nn.se
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Smith,
University of Aberdeen, UK
E-mail:
ps@nn.uk
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Thürig,
Swiss Federal Research Institute WSL, Switzerland
E-mail:
et@nn.ch
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
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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.
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Peltoniemi,
Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland
E-mail:
mikko.peltoniemi@metla.fi
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Thürig,
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland; European Forest Institute, Joensuu, Finland
E-mail:
et@nn.ch
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Ogle,
Natural Resources Ecology Laboratory, Colorado State University, Fort Collins, USA
E-mail:
so@nn.us
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Palosuo,
European Forest Institute, Joensuu, Finland
E-mail:
tp@nn.fi
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Schrumpf,
Max-Planck-Institute for Biogeochemistry, Jena, Germany
E-mail:
ms@nn.de
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Wutzler,
Max-Planck-Institute for Biogeochemistry, Jena, Germany
E-mail:
tw@nn.de
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Butterbach-Bahl,
Institute for Meteorology and Climate Research, Forschungszentrum Karlsruhe GmbH, Garmisch-Partenkirchen, Germany
E-mail:
kbb@nn.de
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Chertov,
St. Petersburg State University, St. Petersburg-Peterhof, Russia
E-mail:
oc@nn.ru
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Komarov,
Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy of Sciences, Pushchino, Russia
E-mail:
ak@nn.ru
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Mikhailov,
Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy of Sciences, Pushchino, Russia
E-mail:
am@nn.ru
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Gärdenäs,
Dept. of Soil Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
E-mail:
ag@nn.se
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Perry,
USDA Forest Service, Northern Research Station, St. Paul, MN USA
E-mail:
cp@nn.us
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Liski,
Finnish Environment Institute, Helsinki, Finland
E-mail:
jl@nn.fi
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Smith,
School of Biological Sciences, University of Aberdeen, Aberdeen, UK
E-mail:
ps@nn.uk
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Mäkipää,
Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland
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
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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.
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Wutzler,
Max Planck Institute for Biogeochemistry, Jena, Germany
E-mail:
tm@nn.de
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Mund,
Max Planck Institute for Biogeochemistry, Jena, Germany
E-mail:
mm@nn.de
article id 288,
category
Special section
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Carbon sequestration rates in forest soil can be estimated using the concept of calculable stable remains in decomposing litter. In a case study of Swedish forest land we estimated C-sequestration rates for the two dominant tree species in the forest floor on top of the mineral soil. Carbon sequestration rates were upscaled to the forested land of Sweden with 23 x 106 ha with Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (Karst.) L.). Two different theoretical approaches, based on limit-value for litter decomposition and N-balance for vegetation and SOM gave rates of the same magnitude. For the upscaling, using these methods, 17 000 grids of 5 x 5 km were used.
The ‘limit-value approach’ gave a sequestration of 4.8 106 tons of C, annually sequestered in the forest floor, with an average of 180 kg C ha–1 yr–1 and a range from 40 to 410 kg C ha–1 yr–1. The ‘N-balance approach’ gave an average value of c. 96 kg ha–1 yr–1 and a range from –60 to 360 kg ha–1 yr–1. A method based on direct measurements of changes in humus depth over 40 years, combined with C analyses gave an average rate that was not very different from the calculated rates, viz. c. 180 kg ha–1 yr–1 and a range from –20 to 730 kg ha–1 yr–1. These values agree with forest floor C sequestration rate based on e.g. sampling of chronsequences but differ from CO2 balance measurements.
The three approaches showed different patterns over the country and regions with high and low carbon sequestration rates that were not always directly related to climate.
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Berg,
Dept. of Forest Ecology, University of Helsinki, Finland (present address: Dipartimento Biologia Strutturale e Funzionale, Complesso Universitario, Monte S. Angelo, Napoli, Italy
E-mail:
bjorn.berg@helsinki.fi
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Gundersen,
Forest & Landscape Denmark, University of Copenhagen, Denmark
E-mail:
pg@nn.dk
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Akselsson,
Swedish Environmental Research Institute, IVL, Gothenburg, Sweden
E-mail:
ca@nn.se
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Johansson,
Department of Forest Soils, SLU, Uppsala, Sweden
E-mail:
mbj@nn.se
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Nilsson,
Department of Forest Soils, SLU, Uppsala, Sweden
E-mail:
an@nn.se
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Vesterdal,
Forest & Landscape Denmark, University of Copenhagen, Denmark
E-mail:
lv@nn.dk
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
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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.
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Peltoniemi,
Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland
E-mail:
mikko.peltoniemi@metla.fi
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Heikkinen,
Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland
E-mail:
jh@nn.fi
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Mäkipää,
Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland
E-mail:
raisa.makipaa@metla.fi
Category :
Research article
article id 471,
category
Research article
Michael Vohland,
Johannes Stoffels,
Christina Hau,
Gebhard Schüler.
(2007).
Remote sensing techniques for forest parameter assessment: multispectral classification and linear spectral mixture analysis.
Silva Fennica
vol.
41
no.
3
article id 471.
https://doi.org/10.14214/sf.471
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One of the most common applications of remote sensing in forestry is the production of thematic maps, depicting e.g. tree species or stand age, by means of image classification. Nevertheless, the absolute quantification of stand variables is even more essential for forest inventories. For both issues, satellite data are attractive for their large-area and up-to-date mapping capacities. This study followed two steps, and at first a supervised parametric classification was performed for a German test site based on a radiometrically corrected Landsat-5 TM scene. There, eight forest classes were identified with an overall accuracy of 87.5%. In the following, the study focused on the estimation of one key stand variable, the stem number per hectare (SN), which was carried out for a number of Norway spruce stands that had been clearly identified in the multispectral classification. For the estimation of SN, the approach of Linear Spectral Mixture Analysis (LSMA) was found to be clearly more effective than spectral indices. LSMA is based on the premise that measured reflectances can be linearly modelled from a set of so-called endmember spectra. In this study, the endmember sets were held variable to decompose pixel values to abundances of a vegetation, a background (soil, litter, bark) and a shade fraction. Forest structure determines the visible portions of these fractions, and therefore, a multiple regression using them as predictor variables provided the best SN estimates. LSMA allows a pixel-by-pixel quantification of SN for complete satellite images. This opens the view to exploit these data for an improved calibration of large-scale multi-parameter assessment strategies (e.g. statistical modelling or the kNN method for satellite data interpretation).
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Vohland,
University of Trier, Faculty of Geography and Geosciences, Remote Sensing Department, Trier, Germany
E-mail:
mv@nn.de
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Stoffels,
University of Trier, Faculty of Geography and Geosciences, Remote Sensing Department, Trier, Germany
E-mail:
js@nn.de
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Hau,
University of Trier, Faculty of Geography and Geosciences, Remote Sensing Department, Trier, Germany
E-mail:
ch@nn.de
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Schüler,
Research Institution for Forest Ecology and Forestry (FAWF), Department of Forest Growth and Silviculture, Trippstadt, Germany
E-mail:
gs@nn.de
article id 286,
category
Research article
Riitta Hänninen,
A. Maarit I. Kallio.
(2007).
Economic impacts on the forest sector of increasing forest biodiversity conservation in Finland.
Silva Fennica
vol.
41
no.
3
article id 286.
https://doi.org/10.14214/sf.286
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In the next coming years, political decisions will be made upon future actions to safeguard forest biodiversity in Southern Finland. We address the economic consequences on the Finnish forest sector of conserving additional 0.5% to 5% of the old growth forest land in Southern Finland. The impacts on supply, demand and prices of wood and forest industry production are analysed employing a partial equilibrium model of the Finnish forest sector. An increase in conservation raises wood prices and thus the production costs of the forest industry. This makes sawnwood production fall, but does not affect paper and paperboard production. The forest owners’ aggregated wood sales income is unaffected or slightly increased, because an increase in stumpage prices offsets the decrease in the harvests. If conservation increases wood imports, negative effects on forest industry become smaller whereas aggregated forest owners’ income may decline depending on the magnitude of import substitution.
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Hänninen,
Finnish Forest Research Institute, Unioninkatu 40 A, FI-00170 Helsinki, Finland
E-mail:
riitta.hanninen@metla.fi
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Kallio,
Finnish Forest Research Institute, Unioninkatu 40 A, FI-00170 Helsinki, Finland
E-mail:
maarit.kallio@metla.fi
article id 285,
category
Research article
Heli Peltola,
Antti Kilpeläinen,
Kari Sauvala,
Tommi Räisänen,
Veli-Pekka Ikonen.
(2007).
Effects of early thinning regime and tree status on the radial growth and wood density of Scots pine.
Silva Fennica
vol.
41
no.
3
article id 285.
https://doi.org/10.14214/sf.285