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Articles by Raisa Mäkipää

Category: Commentary

article id 475, category Commentary
Petteri Muukkonen, Raisa Mäkipää. (2006). Biomass equations for European trees: addendum. Silva Fennica vol. 40 no. 4 article id 475. https://doi.org/10.14214/sf.475
A review of stem volume and biomass equations for tree species growing in Europe (Zianis et al. 2005) resulted in suggestions for additional equations. The numbers of original equations, compiled from scientific articles were 607 for biomass and 230 for stem volume. On the basis of the suggestions and an updated literature search, some new equations were published after our review, but more equations were also available from earlier literature. In this addendum, an additional 188 biomass equations and 8 volume equations are presented. One new tree species (Pinus cembra) is included in the list of volume equations. Biomass equations for twelve new tree species are presented: Abies alba, Carbinus betulus, Larix decidua, P. cembra, P. nigra, Quercus robur, Salix caprea, S. ‘Aquatica’, S. dasyclados, S. phylicifolias, S. triandra and S. accuparia. The tree-level equations predict stem volume, whole tree biomass or biomass of certain components (e.g., foliage, roots, total above-ground) as a function of diameter or diameter and height of a tree. Biomass and volume equations with other independent variables have also been widely developed but they are excluded from this addendum because the variables selected may reflect locally valid dependencies that cannot be generalized to other geographical regions. Most of the equations presented here are developed for Sweden, Finland and Norway in northern Europe, for Austria in central Europe and for Italy in southern Europe. There are also few equations from Poland and Belgium. Most of the equations deal with above-ground components such as stem, branches and foliage, but some new equations are also available for root biomass. Zianis et al. (2005) and this addendum can be used together as guides to the original publications of these equations. Our updated database of the biomass and volume equations is available also from the website www.metla.fi/hanke/3306/tietokanta.htm.
  • Muukkonen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: petteri.muukkonen@metla.fi
  • Mäkipää, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: raisa.makipaa@metla.fi (email)

Category: Research article

article id 340, category Research article
Petteri Muukkonen, Raisa Mäkipää, Raija Laiho, Kari Minkkinen, Harri Vasander, Leena Finér. (2006). Relationship between biomass and percentage cover in understorey vegetation of boreal coniferous forests. Silva Fennica vol. 40 no. 2 article id 340. https://doi.org/10.14214/sf.340
In the present study, the aboveground biomass of the understorey vegetation of boreal coniferous forests was modelled according to the percentage cover. A total of 224 observations from 22 stands in upland forests and 195 observations from 14 different studies in peatland forests were utilized for the present analyses. The relationships between biomass and percentage cover can be used in ecosystem and carbon-cycle modelling as a rapid nondestructive method for estimation of the aboveground biomass of lichens, bryophytes, herbs and grasses, and dwarf shrubs in upland forests and bottom and field layers in peatland forests.
  • Muukkonen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: petteri.muukkonen@metla.fi (email)
  • Mäkipää, Finnish Forest Research Institute, Unioninkatu 40 A, FI-00170 Helsinki, Finland ORCID ID:E-mail:
  • Laiho, Department of Forest Ecology, P.O. Box 24, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Minkkinen, Department of Forest Ecology, P.O. Box 24, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Vasander, Department of Forest Ecology, P.O. Box 24, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Finér, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail:

Category: Research note

article id 91, category Research note
Raisa Mäkipää, Tapio Linkosalo. (2011). A non-destructive field method for measuring wood density of decaying logs. Silva Fennica vol. 45 no. 5 article id 91. https://doi.org/10.14214/sf.91
Decaying dead wood density measurements are a useful indicator for multiple purposes, such as for estimating the amount of carbon in dead wood and making predictions of potential diversity of dead wood inhabiting fungi and insects. Currently, qualitative decay phases are used as wood density estimates in many applications, since measuring the density is laborious. A quantitative measure of density would, however, be preferred over the qualitative one. Penetrometers, which are commonly used for measuring the density of standing trees, might also be applicable to dead wood density measurements. We tested the device for making quick, quantitative measurements of decaying logs. The penetrometer measures the depth into which a pre-loaded spring forces a pin in the wood. We tested pins of 5 and 10 mm diameter together with an original 2.5 mm pin and compared the results with gravimetric density measurements of the sample logs. Our results suggest that the standard pin works for less decayed wood, but for more decomposed wood, the thicker 5 mm pin gave more reliable estimates when the penetration measures were converted to densities with a linear regression function (R2 = 0.62, F = 82.9, p = 0.000). The range of wood densities successfully measured with the 5 mm pin was from 180 to 510 kg m–3. With the 10 mm pin, the measuring resolution of denser wood was compromised, while the improvement at the other end of density scale was not large. As a conclusion, the penetrometer seems to be a promising tool for quick density testing of decaying logs in field, but it needs to be modified to use a thicker measuring pin than the standard 2.5 mm pin.
  • Mäkipää, The Finnish Forest Research Institute, Vantaa, Finland ORCID ID:E-mail: raisa.makipaa@metla.fi (email)
  • Linkosalo, The Finnish Forest Research Institute, Vantaa, Finland ORCID ID:E-mail:

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
Selected Papers of the Workshop on Development of Models and Forest Soil Surveys for Monitoring of Soil Carbon.
  • Mäkipää, Finnish Forest Research Institute ORCID ID:E-mail:
  • Liski, Finnish Environment Institute, Finland ORCID ID:E-mail:
  • Olsson, Swedish University of Agricultural Sciences, Sweden ORCID ID:E-mail:
  • Smith, University of Aberdeen, UK ORCID ID:E-mail:
  • Thürig, Swiss Federal Research Institute WSL, Switzerland ORCID ID:E-mail:
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 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 5399, category Article
Raisa Mäkipää. (1994). Effects of nitrogen fertilization on the humus layer and ground vegetation under closed canopy in boreal coniferous stands. Silva Fennica vol. 28 no. 2 article id 5399. https://doi.org/10.14214/sf.a9164

Forest ecosystems may accumulate large amounts of nitrogen in the biomass and in the soil organic matter. However, there is increasing concern that deposition of inorganic nitrogen compounds from the atmosphere will lead to nitrogen saturation; excess nitrogen input does not increase production. The aim of this study was to determine the long-term changes caused by nitrogen input on accumulation of nitrogen in forest soils and in ground vegetation.

The fertilization experiments used in this study were established during 1958–1962. They were situated on 36- to 63-year-old Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) stands of different levels of fertility. The experiments received nitrogen fertilization 5–7 times over a 30-year period, and the total input of nitrogen was 596–926 kg/ha.

Nitrogen input increased the amount of organic matter in the humus layer and the nitrogen concentration in the organic matter. Furthermore, the total amount of nutrients (N, P, K, Ca and Mg) bound by the humus layer increased due to the increase in the amount of organic matter. However, nitrogen input decreased the biomass of ground vegetation. The nitrogen concentration of the plant material on the nitrogen-fertilized plots was higher than on the control plots, but the amount of nutrients bound by ground vegetation decreased owing to the drastic decrease in the biomass of mosses. Ground vegetation does not have the potential to accumulate nitrogen, because vegetation is dominated by slow-growing mosses and dwarf shrubs which do not benefit from nitrogen input.

  • Mäkipää, ORCID ID:E-mail:

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