Current issue: 54(2)
The purpose of this paper is to review tests made on the basis of Finnish material with regard to the efficiency of the 10-point cluster in sampling a stand in forest inventory. Currently, this system is applied in field work in the national forest surveys in the United States of America. The paper reports on tests, made on the basis of Finnish material, for comparison of the 10-point cluster of variable plots with 13 other designs in sampling a stand in forest survey. The research material consists of 12 stands, with Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) H. Karst.) as the main species.
The main results are concerned with the ability of different designs to provide gross volume estimates. As a measure of efficiency, three alternative series of variances were used, adjusted by three alternatives of time. The results are applicable, for instance, in double-sampling with photo and field classifications. In the comparisons, no attention was paid to the possibility of systematic errors in various designs.
For inventory volume, the 10-point cluster proved to be about 10 per cent less efficient than the best design of each alternative. The use of a single circular plot of 1,000 m2 can be recommended under the conditions of this test; furthermore, one or two 500 m2 plots were more efficient than any combination of variable plots.
The reason for the use of the 10-point cluster in forest surveying has been the ability of the design to provide simultaneous information on area condition classes. Among the designs tested, the 10-point cluster seems to be the only one capable of application in the estimation of condition classes.
Most of the information obtained by means of the 10-point cluster can be gained through ocular estimation, and from the sample trees to be measured in any design, but a cluster of several points appears to offer good means of estimation, for instance, of the presence of clumps and gasps in a stand.
It is necessary to study the problems related to the size, number and location of sample plots as well as to the effect of stratification. This paper, mainly concerned with the volume of the growing stock based on measurements, comprises a part of the research in progress related to the issue.
The study contains a discussion of certain problems relevant to the planning of a forest inventory on the basis of variation in the volume of the growing stock. In particular, the aim has been to give data for selection of the size and number of sample plots, and to illustrate the importance of stratification, here based principally on dominant height.
The research material comprised two forest areas of 10 ha each; measurement of the growing stock was made in units of 49 m2. Based on the data was constructed a model area embracing 4 forested strata and one non-forested stratum. The mean and standard deviations of the volumes was calculated for the forest area as a whole and for the different strata. On studying stratification, two approaches were employed to distribute the sample plots among the strata: optimum allocation and proportional allocation. The latter is simple in application, and gave for forested areas number of sample plots which did not exceed by more than 10% those obtained by optimum allocation. It is obvious that the application of stratification is worthy of consideration within forest areas which comprise parts with distinct differences. The decrease in number of plots with increasing plot size is considerably more marked within a stratified area. Thus, larger sample plots should be used in the former case than in the later. The investigations give hints on how forest inventories should be carried out. However, it has some limitations, which are discussed in the paper.
The PDF includes a summary in English.
The annual fellings and sales of pulpwood from the State Forests of Finland comprised 4.0–4.6 million m3 in 1955–1959. In order to improve the accuracy of the methods used in estimating the pulpwood stocks marked for felling, a pilot survey of 18 marked stocks was carried out in 1959. The stock area, average plot volume, variation of the plot volumes, size and shape of the plot and the distribution of the trees by diameter classes as factors affecting the precision have been studied in this paper.
The greater the mean volume of a plot the more homogenous is the structure of the marked stock. The same number of plots gives a better relative precision for the south Finnish marked stock than for the north Finnish ones, which are heterogenous and less valuable. Stocks smaller than 50 ha can often be estimated more advantageously by the strip method or visually than by the plot method. The proper size of plot in Southern Finland is 0.02–0.03 ha. In Northern Finland the plots should be larger due to the heterogenous stocks, about 0.05 ha. The shape can be either circular or rectangular. The former may be more practical and reliable in the field. The minimum number of sample trees is considered to be about 200 per 100 sample plots 0.03 ha in size.
The PDF includes a summary in English.
Theoretical and practical aspects of permanent sample plots are discussed in this paper. A study material of 6,871 permanent sample plots was generated using increment sample plots of the 7th National Forest Inventory of Finland. The effect of measurement errors and use of increment functions as ”a priori” information was studied via simulation experiments. The change in the growing stock volume between two consecutive measurement rounds was divided into the components drain, growth and mortality. Finally, a hypothetical inventory design using permanent sample plots was evaluated.
The PDF includes an abstract in Finnish.
18 permanent sample subplots of the Swedish and the Hassian Forestry Institute, each measured in equal intervals for several decades, were divided into subplots of different size. An analysis of variance was calculated for every set of subplot size. The development of intraclass-correlations over years and over different sizes of subplots could be explained if three different correlations were assumed: soil-correlation, correlations from irregular distribution of the trees, and correlation resulting from competition. Intraclass-correlations were positive or negative depending on dominance of one or two of these correlations.
An explanatory simultation study of competitional variance showed the effect of the degree of competitional correlations on the variance of means of subplots of different sizes. If this coefficient was small, all variances of subplots means within the range investigated became larger than expected in experiments without competition, with larger coefficients the variances of means of the smaller subplots became smaller, those of larger subplots larger than expected.
Plots of medium or large size are probably optimal for long term experiments with forest trees, if all sources of costs in such experiments are taken into account.
The PDF includes a summary in English and Finnish.
Emphasis was laid on the finding of regression equations to indicate the dependence of standard error upon various variables in systematic sampling. As a result, the size of sample for a given precision could be computed, under varying alternatives of sample plot size and type. Another task was that of examining inventory costs by means of time studies. On combination of the results in regard to the sample size and survey time, the relative efficiency of different alternatives could be discussed, with a view to the precision of the total volume of growing stock.
The PDF includes a summary in Finnish.