Articles containing the keyword 'variance'

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.

• Kuuluvainen, E-mail: tk@mm.unknown
• Leinonen, E-mail: kl@mm.unknown
• Nygren, E-mail: mn@mm.unknown
• Penttinen, E-mail: ap@mm.unknown

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.

• Aurela, E-mail: ma@mm.unknown
• Laurila, E-mail: tl@mm.unknown
• Tuovinen, E-mail: jt@mm.unknown

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.

• Kangas, E-mail: ak@mm.unknown

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.

• Luukkanen, E-mail: ol@mm.unknown

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.

• Ojansuu, E-mail: ro@mm.unknown

• Peltoniemi, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: mikko.peltoniemi@metla.fi
• 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

• McRoberts, North Central Research Station, USDA Forest Service, 1992 Folwell Avenue, Saint Paul, Minnesota, USA 5510 E-mail: rmcroberts@fs.fed.us
• Wendt, Region 9, USDA Forest Service, 626 East Wisconsin Avenue, Milwaukee, Wisconsin 53202, USA E-mail: dgw@nn.us
• Liknes, North Central Research Station, USDA Forest Service, 1992 Folwell Avenue, Saint Paul, Minnesota, USA 5510 E-mail: gcl@nn.us

• 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
• Penttilä, Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FIN-01301 Vantaa, Finland E-mail: tp@nn.fi
• 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

• Zawadzki, Environmental Engineering Department, Warsaw Technical University, Ul. Nowowiejska 20, 00-653 Warsaw, Poland E-mail: jaroslaw.zawadzki@is.pw.edu.pl
• Cieszewski, D. B. Warnell School of Forest Resources, University of Georgia, Athens, GA 30602, USA E-mail: cjc@nn.us
• 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

• Saksa, The Finnish Forest Institute, Suonenjoki Research Station, FI-77600 Suonenjoki, Finland E-mail: ts@nn.fi
• Heiskanen, The Finnish Forest Institute, Suonenjoki Research Station, FI-77600 Suonenjoki, Finland E-mail: jh@nn.fi
• Miina, The Finnish Forest Institute, Joensuu Research Centre, P. O. Box 68, FI-80101 Joensuu, Finland E-mail: jm@nn.fi
• Tuomola, The University of Joensuu, Mekrijärvi Research Station, FI-82900 Ilomantsi, Finland E-mail: jt@nn.fi
• Kolström, The University of Joensuu, Mekrijärvi Research Station, FI-82900 Ilomantsi, Finland E-mail: tk@nn.fi