Category :
Article
article id 5598,
category
Article
Timo Kuuluvainen,
Kari Leinonen,
Markku Nygren,
Antti Penttinen.
(1996).
Statistical opportunities for comparing stand structural heterogeneity in managed and primeval forests: an example from boreal spruce forest in southern Finland.
Silva Fennica
vol.
30
no.
2–3
article id 5598.
https://doi.org/10.14214/sf.a9243
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The horizontal and vertical stand structure of living trees was examined in a managed and in a primeval Norway spruce-dominated forest in Southern Finland. Tree size distributions (DBHs, tree height) were compared using frequency histograms. The vertical distribution of tree heights was illustrated as tree height plots and quantified as the tree height diversity (THD) using the Shannon-Weaver formula. The horizontal spatial pattern of trees was described with stem maps and quantified with Ripley's K-function. The spatial autocorrelation of tree sizes was examined with semivariogram analysis. In the managed forest the DBH and height distributions of trees were bimodal, indicating a two-layered vertical structure with a single dominant tree layer and abundant regeneration in the understory. The primeval forest had a much higher total number of trees which were rather evenly distributed in different diameter and tree height classes. The K-function summaries for trees taller than 15 m indicated that the primeval stand was close to complete random pattern. The managed stand was regular at small distances (up to 4 m). The semivariograms of tree sizes (DBH tree height) showed that the managed forest had a clear spatial dependence in tree sizes up to inter-tree distances of about 12 meters. In contrast, the primeval spruce forest had a variance peak at very short inter-tree distances (< 1 m) and only weak spatial autocorrelation at short inter-tree distances (1–5 m). Excluding the understory trees (h < 15 m) from the analysis drastically changed the spatial structure of the forest as revealed by semivariograms. ln general, the structure of the primeval forest was both horizontally and vertically more variable and heterogeneous compared to the managed forest. The applicability of the used methods in describing fine-scale forest structure i discussed.
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Kuuluvainen,
E-mail:
tk@mm.unknown
-
Leinonen,
E-mail:
kl@mm.unknown
-
Nygren,
E-mail:
mn@mm.unknown
-
Penttinen,
E-mail:
ap@mm.unknown
article id 5578,
category
Article
Mika Aurela,
Tuomas Laurila,
Juha-Pekka Tuovinen.
(1996).
Measurements of O3, CO2 and H2O fluxes over a Scots pine stand in eastern Finland by the micrometeorological eddy covariance method.
Silva Fennica
vol.
30
no.
2–3
article id 5578.
https://doi.org/10.14214/sf.a9223
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The eddy covariance technique is a novel micrometeorological method that enables the determination of the atmosphere-biosphere exchange rate of gases such as ozone and carbon dioxide on an ecosystem scale. This paper describes the technique and presents results from the first direct measurements of turbulent fluxes of O3, CO2 and H2O above a forest in Finland. The measurements were performed during 15 July-5 August 1994 above a Scots pine (Pinus sylvestris L.) stand near the Mekrijärvi research station in Eastern Finland.
The expected diurnal cycles were observed in the atmospheric fluxes of O3, CO2 and H2O. The data analysis includes interpretation of the O3 flux in terms of the dry deposition velocity and evaluation the dependency of the net CO2 flux on radiation. The eddy covariance method and the established measurement system has proved suitable for providing high-resolution data for studying ozone deposition to a forest as well as the net carbon balance and related physiological processes of an ecosystem.
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Aurela,
E-mail:
ma@mm.unknown
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Laurila,
E-mail:
tl@mm.unknown
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Tuovinen,
E-mail:
jt@mm.unknown
article id 5524,
category
Article
Annika Kangas.
(1994).
Classical and model based estimators for forest inventory.
Silva Fennica
vol.
28
no.
1
article id 5524.
https://doi.org/10.14214/sf.a9158
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In this study, model-based and design-based inference methods are used for estimating mean volume and its standard error for systematic cluster sampling. Results obtained with models are compared to results obtained with classical methods. The data are from the Finnish National Forest Inventory. The variation of volume in ten forestry board districts in Southern Finland is studied. The variation is divided into two components: trend and correlated random errors. The effect of the trend and the covariance structure on the obtained mean volume and standard error estimates is discussed. The larger the coefficient of determination of the trend model, the smaller the model-based estimates of standard error, when compared to classical estimates. On the other hand, the wider the range and level of autocorrelation between the sample plots, the larger the model-based estimates of standard error.
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Kangas,
E-mail:
ak@mm.unknown
article id 4888,
category
Article
Olavi Luukkanen.
(1973).
Havaintoja kuusen vapaapölytysjälkeläistöjen ja männyn metsikköalkuperien CO2-aineenvaihdunnasta.
Silva Fennica
vol.
7
no.
4
article id 4888.
https://doi.org/10.14214/sf.a14726
English title:
Observations on CO2 exchange in open pollinated progenies of Norway spruce and provenances of Scots pine.
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Photosynthesis and dark respiration in five families of autochtonous Norway spruce (Picea abies (L.) H. Karst.) and in seedlings from twenty Finnish stands of Scots pine (Pinus sylvestris L.) were investigated in constant environmental conditions. Values of CO2 exchange were compared with the height growth and weight of seedlings in Norway spruce and with the weight alone in Scots pine. No statistically significant differences were found in CO2 exchange among progenies or stands. Photosynthetic efficiency and photosynthetic capacity showed a positive correlation both in spruce and in pine. Growth and net photosynthetic capacity were linearly and positively correlated in pine. Spruce and a higher light compensation point than pine. The use of an open IRGA system with several simultaneous measurements and the trap-type cuvette construction in genetic work are discussed.
The PDF includes a summary in English.
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Luukkanen,
E-mail:
ol@mm.unknown
Category :
Article
article id 7685,
category
Article
Risto Ojansuu.
(1993).
Prediction of Scots pine increment using a multivariate variance component model.
Acta Forestalia Fennica
no.
239
article id 7685.
https://doi.org/10.14214/aff.7685
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Diameter and volume increment as well as change in stem form of Scots pine (Pinus sylvestris L.) were analysed to predict tree increment variables. A stem curve set model is presented, based on prediction of the diameters at fixed angles in a polar coordinate system. This model consists of three elementary stem curves: 1) with bark, 2) without bark, and 3) without bark five years earlier. The differences between the elementary stem curves are the bark curve and the increment curve. The error variances at fixed angles and covariances between the fixed angles are divided into between-stand and within-stand components. Using principal components, the between-stand and within-stand covariance matrices are condensed separately for stem curve with bark, bark curve and increment curve. The two first principal components of the bark curve describe the vertical change in Scots pine bark type and the first principal component of the increment curve describes the increment rate. The elementary stem curves, bark curve and increment curve as well as corresponding stem volumes, bark volume and volume increment can be predicted for all trees in the stand with free choice of sample tree measurements. When only a few sample trees are measured, the stem curve set model gives significantly more accurate predictions of bark volume and volume increment for tally trees than does the volume method, which is based on the differences between two independent predictions of volume. The volume increment of tally trees can be predicted as reliably with as without measurement of sample tree height increment.
The PDF includes a summary in English.
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Ojansuu,
E-mail:
ro@mm.unknown
Category :
Special section
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
-
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 478,
category
Research article
Ronald E. McRoberts,
Daniel G. Wendt,
Greg C. Liknes.
(2005).
Stratified estimation of forest inventory variables using spatially summarized stratifications.
Silva Fennica
vol.
39
no.
4
article id 478.
https://doi.org/10.14214/sf.478
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Large area natural resource inventory programs typically report estimates for selected geographic areas such as states or provinces, counties, and municipalities. To increase the precision of estimates, inventory programs may use stratified estimation, with classified satellite imagery having been found to be an efficient and effective basis for stratification. For the benefit of users who desire additional analyses, the inventory programs often make data and estimation procedures available via the Internet. For their own analyses, users frequently request access to stratifications used by the inventory programs. When data analysis is via the Internet and stratifications are based on classifications of even medium resolution satellite imagery, the memory requirements for storing the stratifications and the online time for processing them may be excessive. One solution is to summarize the stratifications at coarser spatial scales, thus reducing both storage requirements and processing time. If the bias and loss of precision resulting from using summaries of stratifications is acceptably small, then this approach is viable. Methods were investigated for using summaries of stratifications that do not require storing and processing the entire pixel-level stratifications. Methods that summarized satellite image-based 30 m x 30 m pixel stratifications at spatial scales up to 2400 ha produced stratified estimates of the mean that were generally within 5-percent of estimates for the same areas obtained using the pixel stratifications. In addition, stratified estimates of variances using summarized stratifications realized nearly all the gain in precision that was obtained with the underlying pixel stratifications.
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McRoberts,
North Central Research Station, USDA Forest Service, 1992 Folwell Avenue, Saint Paul, Minnesota, USA 5510
E-mail:
rmcroberts@fs.fed.us
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Wendt,
Region 9, USDA Forest Service, 626 East Wisconsin Avenue, Milwaukee, Wisconsin 53202, USA
E-mail:
dgw@nn.us
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Liknes,
North Central Research Station, USDA Forest Service, 1992 Folwell Avenue, Saint Paul, Minnesota, USA 5510
E-mail:
gcl@nn.us
article id 433,
category
Research article
Raija Laiho,
Timo Penttilä,
Jukka Laine.
(2004).
Variation in soil nutrient concentrations and bulk density within peatland forest sites.
Silva Fennica
vol.
38
no.
1
article id 433.
https://doi.org/10.14214/sf.433
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The within-site variability of soil characteristics on sites with different soil types remains poorly quantified, although this information is crucial for the success of research on soil properties, and especially for monitoring soil properties over time. We used coefficients of variation and multilevel variance component models to examine the within-site variation of soil (0–30 cm) mineral nutrient concentrations (P, K, Ca, Mg, Fe, mg g–1; Mn, Zn, mg g–1) and bulk density (kg m–3) on boreal deep-peat sites. We then evaluated the reliability of the site-level estimates (sample means) obtained using different sampling intensities (numbers of samples per site). Our 11 sites represented a single original site type within the oligotrophic nutrient level. Two of the sites were undrained while the rest had been drained for forestry at different points in time. Overall, P concentrations showed the smallest and Mn concentrations the largest within-site variation. The sampling depth contributed more than 50% of the total variance in all other characteristics except the concentrations of P and Fe, and bulk density. The variance proportions of peatland basin, site (within basin), and sampling location (within site) varied by sampling depth for most soil characteristics. The estimates obtained when using a certain number of samples per site were always more reliable for the 0–30 cm layer’s composite samples than for any single 10-cm layer at any depth sampled. On average, it was found that between 4 (P) and some 200 (Mn) samples per site would be needed for the estimates to have a theoretical 10% maximum deviation.
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Laiho,
Univ. of Helsinki, Dept. of Forest Ecology, Peatland Ecology Group, P.O. Box 27, FIN-00014 University of Helsinki, Finland
E-mail:
raija.laiho@helsinki.fi
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Penttilä,
Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FIN-01301 Vantaa, Finland
E-mail:
tp@nn.fi
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Laine,
Univ. of Helsinki, Dept. of Forest Ecology, Peatland Ecology Group, P.O. Box 27, FIN-00014 University of Helsinki, Finland
E-mail:
jl@nn.fi
Category :
Review article
article id 369,
category
Review article
Jaroslaw Zawadzki,
Chris J. Cieszewski,
Michal Zasada,
Roger C. Lowe.
(2005).
Applying geostatistics for investigations of forest ecosystems using remote sensing imagery.
Silva Fennica
vol.
39
no.
4
article id 369.
https://doi.org/10.14214/sf.369
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Geostatistically based methods that utilize textural information are frequently used to analyze remote sensing (RS) images. The role of these methods in analyzing forested areas increased rapidly during the last several years following advancements in high-resolution RS technology. The results of numerous applications of geostatistical methods for processing RS forest images are encouraging. This paper summarizes such results. Three closely related topics are reviewed: 1) specific properties of geostatistical measures of spatial variability calculated from digital images of forested areas, 2) determination of biophysical forest parameters using semivariograms and characterization of forest ecosystem structure at the stand level, and 3) forest classification methods based on spatial information.
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Zawadzki,
Environmental Engineering Department, Warsaw Technical University, Ul. Nowowiejska 20, 00-653 Warsaw, Poland
E-mail:
jaroslaw.zawadzki@is.pw.edu.pl
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Cieszewski,
D. B. Warnell School of Forest Resources, University of Georgia, Athens, GA 30602, USA
E-mail:
cjc@nn.us
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Zasada,
Department of Forest Productivity, Faculty of Forestry, Warsaw Agricultural University, Poland
E-mail:
mz@nn.pl
-
Lowe,
D. B. Warnell School of Forest Resources, University of Georgia, Athens, GA 30602, USA
E-mail:
rcl@nn.us
Category :
Research note
article id 403,
category
Research note
Timo Saksa,
Juha Heiskanen,
Jari Miina,
Jaakko Tuomola,
Taneli Kolström.
(2005).
Multilevel modelling of height growth in young Norway spruce plantations in southern Finland.
Silva Fennica
vol.
39
no.
1
article id 403.
https://doi.org/10.14214/sf.403
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Height development of Norway spruce (Picea abies (L.) Karst.) transplants was studied on 22 sites prepared by disc trenching or mounding. At the age of 4–9 years the plantations were surveyed using a multistage sampling design. For every planted spruce on a plot, the past annual height increments were measured as far into the past as possible. Multilevel mixed linear modelling was used to analyse the variation in growth at different levels (year, stand, cluster, plot, tree) and the effects of climatic and site characteristics on height growth. The within-plantation variation in height growth was higher on mounded sites than on disc-trenched sites. The mean temperature and the precipitation sum of the summer months affected height growth positively. Soil characteristics measured from undisturbed soil did not explain the height growth of seedlings on mounded sites, whereas on disc-trenched sites, the depth of the organic layer and the soil temperature had a positive effect and the depth of the eluvial horizon a negative effect. The modelling approach used proved to be a useful method for examining the sources of variation in development of young plantations.
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Saksa,
The Finnish Forest Institute, Suonenjoki Research Station, FI-77600 Suonenjoki, Finland
E-mail:
ts@nn.fi
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Heiskanen,
The Finnish Forest Institute, Suonenjoki Research Station, FI-77600 Suonenjoki, Finland
E-mail:
jh@nn.fi
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Miina,
The Finnish Forest Institute, Joensuu Research Centre, P. O. Box 68, FI-80101 Joensuu, Finland
E-mail:
jm@nn.fi
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Tuomola,
The University of Joensuu, Mekrijärvi Research Station, FI-82900 Ilomantsi, Finland
E-mail:
jt@nn.fi
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Kolström,
The University of Joensuu, Mekrijärvi Research Station, FI-82900 Ilomantsi, Finland
E-mail:
tk@nn.fi