Current issue: 57(2)
Under compilation: 57(3)
Models for individual-tree basal area growth were constructed for Scots pine (Pinus sylvestris L.), pubescent birch (Betula pubescens Ehrh.) and Norway spruce (Picea abies (L.) Karst.) growing in drained peatland stands. The data consisted of two separate sets of permanent sample plots forming a large sample of drained peatland stands in Finland. The dependent variable in all models was the 5-year basal area growth of a tree. The independent tree-level variables were tree dbh, tree basal area, and the sum of the basal area of trees larger than the target tree. Independent stand-level variables were stand basal area, the diameter of the tree of median basal area, and temperature sum. Categorical variables describing the site quality, as well as the condition and age of drainage, were used. Differences in tree growth were used as criteria in reclassifying the a priori site types into new yield classes by tree species. All models were constructed as mixed linear models with a random stand effect. The models were tested against the modelling data and against independent data sets.
One of the difficulties in constructing growth and yield tables has been to determine which of the sample plots growing the same tree species and belonging to the same forest site type, with reference to the quality of stands, have to be included in the same growth series.
New growth and yield tables for the most important tree species were constructed in Finland in 1916–1919, using new principles that aim at avoiding some of the common weaknesses. There were two main differences to the earlier work. First, the site quality class (forest site type) was determined for each sample plot when the sample plot was measured, independently of the stand occupying the site. In this way it was possible to treat the sample plots of each site as an independent group from the beginning, and so that the quality classes were the same for all the tree species. Second, mathematic-statistical methods were used to deduct the so-called stem frequency distribution series, when studying which of the sample plots of the same quality class belong to the same growth series. They represent the average number of stems of the different diameter classes. A more detailed description of the method used to create the growth and yield tables is published in Acta Forestalia Fennica no. 15.
In the PDF is included a summary in Finnish.
The study is based on the results of the soil studies by Valmari (1921) and the growth inventories of respective areas. The aim is to show the connection of soil fertility (nutrient content) and forest growth with means of correlation calculations. The examined nutrients were nitrogen, calcium and phosphorus, also the electrolyte content was studied.The results show that with increase of nitrogen content of the soil the growth of pine stand increases as well. The correlation is clearly identified. The number of birch and spruce stands is too small for systematic review. For calcium there is a similar kind of relation. With phosphorus content or amount of electrolytes the correlation with doesn’t exist. Also the loss on ignition test was conducted. The relation found is somewhat weak.
Tree growth is one of the factors that have been used to determine the site quality. The aim of the study was to show that growth of single trees growing on a same forest site class are similar, but differ from trees growing on a different site type. To compare the tree growth, a stem analysis was performed to dominant trees in Scots pine (Pinus sylvestris L.) stands, measured in 15 Myrtillus type sample plots and in 15 Calluna type sample plots in state forests in Salmi, situated in north side of Lake Ladoga. The height growth when the tree was young was higher in the trees growing in the Myrtillus type than in the Calluna type. Also, the trees of same age are higher in Myrtillus type stand than in the Calluna type. In Calluna type, the height growth, however, evens out later in age than in the Myrtillus type. The volume growth of the trees begins to increase earlier in Myrtillus type, and is higher than in Calluna type. Similarly, the diameter growth in breast height is higher in the Myrtillus type.
The PDF includes a summary in German.
The relationship between site characteristics and understorey vegetation composition was analysed with quantitative methods, especially from the viewpoint of site quality estimation. Theoretical models were applied to an empirical data set collected from the upland forests of Southern Finland comprising 104 sites dominated by Scots pine (Pinus sylvestris. L.) and 165 sites dominated by Norway spruce (Picea abies (L.) H. Karst.). Site index H100 was used as an independent measure of site quality.
A new model for the estimation of site quality at sites with a known understorey vegetation composition was introduced. It is based on the application of Bayes’ theorem to the density function of site quality within the study area combined with the species-specific presence-absence response curves. The resulting probability density function may be used for calculating an estimate for the site variable
Using this method, a jackknife estimate of site index H100 was calculated separately for pine- and spruce-dominated sites. The results indicated that the cross-validation root mean squared error (RMSEcv) of the estimates improved from 2.98 m down to 2.34 m relative to the ”null” model (standard deviation of the sample distribution) in pine-dominated forests. In spruce-dominated forests RMSEcv decreased from 3.94 m down to 3.19 m.
In order to assess these results, four other estimation methods based on understorey vegetation composition were applied to the same data set. The results showed that none of the methods was clearly superior to the others. In pine-dominated forests RMSEcv varied between 2.34 and 2.47 m, and the corresponding range for spruce-dominated forest was from 3.13 to 3.57 m.
Two operative forest site class estimation methods utilizing satellite images have been developed for forest income taxation purposes. For this, two pixelwise classification methods and two post-processing methods for estimating forest site fertility are compared using different input data. The pixelwise methods are discriminant analysis, based on generalized squared distances, and logistic regression analysis. The results of pixelwise classifications are improved either with mode filtering within forest stands or assuming a Markov random field type dependence between pixels. The stand delineation is obtained by using ordinary segmentation techniques. Optionally, known stand boundaries given by the interpreter can be applied. The spectral values of images are corrected using a digital elevation model of the terrain. Some textural features are preliminary tested in classification. All methods are justified by using independent test data.
A test of the practical methods was carried out and a cost-benefit analysis computed. The estimated cost saving in site quality classification varies from 14% to 35% depending on the distribution of the site classes of the area. This means a saving of about 2.0–4.5 million FMK per year in site fertility classification for income taxation purposes. The cost savings would rise even to 60% if that version of the method were chosen where field checking is totally omitted. The classification accuracy at the forest holding level would still be similar to that of traditional method.
The PDF includes a summary in Finnish.
Physical soil properties have a marked influence on the quality of forest sites and on the preconditions for forest growth and management. In this study, water retention characteristics (WRC) and related physical soil properties in addition to vegetation coverage and tree stand data were studied at upland forest sites in Finland. Fixed and mixed models between soil and site characteristics were formed to estimate physical and hydrologic soil characteristics and the site quality with indirect co-varying variables. In the present data, the site quality index (H100) shows a high coefficient of determination in respect to the temperature sum. It is also related to soil fine fraction content, topsoil pH and water retention at field capacity. The thickness of the humus layer is predictable from the pH and cover of xeric and mesic plant species. The soil fine fraction content (clay + silt) is closely related to water retention at field capacity, the soil layer and site type, and without WRC to the temperature sum and site index and type, as well as the slope angle. The soil bulk density is related to organic matter, depth (layer) or alternatively to organic matter, slope and field estimated textural class (fine, medium, coarse). Water retention characteristics were found to be best determinable by the fine fraction content, depth and bulk density. Water content and air-filled porosity at field capacity are closely related to the fine fraction. This study provides novel models for further investigations that aim at improved prediction models for forest growth, hydrology and trafficability.