Articles containing the keyword 'sampling'

Cut-off importance sampling (CIS) is introduced as a means of sampling individual trees for the purpose of estimating bole volume. The novel feature of this variant of importance sampling is the establishment on the bole of a cut-off height, H_C, above which sampling is precluded. An estimator of bole volume between predetermined heights H_L and H_U > H_C is proposed, and its design-based bias and mean square error are derived. In an application of CIS as the second stage of a two-stage sample to estimate aggregate bole volume, the gain in precision realized from CIS more than offset its bias when compared to the precision of importance sampling when H_C = H_U.

• Robinson, E-mail: ar@mm.unknown
• Gregoire, E-mail: tg@mm.unknown
• Valentine, E-mail: hv@mm.unknown

The use of random parameter models in forestry has been proposed as one method of incorporating different levels of information into prediction equations. By explicitly considering the variance-covariance structure of observations and considering some model parameters as random rather than fixed, one can incorporate more complex error structures in analysing data.

Competition indices and variance component techniques were applied to 92 Scots pine (Pinus sylvestris L.) -dominated permanent sample plots on drained peatlands in Northern Finland. By quantifying stand, plot, and tree level variation, it was possible to identify the level (stand, plot or tree) at which the explanatory variables contributed to the model. The replication of plots within stands revealed little variation among plots within a single stand but significant variation occurred at stand and tree levels. Positive and negative effects of inter-tree competition are identified by examining simple correlation statistics and the random parameter model.

• Penner, E-mail: mp@mm.unknown
• Hökkä, E-mail: hh@mm.unknown
• Penttilä, E-mail: tp@mm.unknown

Spatial variation in the density of soil organic carbon (kg/m²) and the thickness of soil horizons (F/H, E) were investigated in a 6 m x 8 m area in Scots pine (Pinus sylvestris L.) stand in Southern Finland for designing an effective sampling for the C density and studying the effect of trees on the variation. The horizon thickness of the podzolized soil were measured on a total of 126 soil cores (50 cm deep) and the C density of the organic F/H and 0–10 cm, 10–20 cm and 20–40 cm mineral soil layers was analysed.

The C density varied 3–5 fold within the layers and the coefficients of variation ranged from 22 % to 40%. Considering the gain in confidence per sample, 8–10 samples were suggested for estimating the mean C density in the F/H and 0–40 cm layers, although about 30 samples are needed for 10% confidence in the mean. The C densities and horizon thicknesses were spatially dependent within the distances of 1–8 m, the spatial dependence accounting for 43–86% of the total variance. The F/H layer was thicker and contained more C within 1–3 m radius from trees. In the 10–20 cm and 20–40 cm layers (B horizon) the C density also increased towards the trees, but more pronouncedly in the immediate vicinity of the stems. Because the spatial patterning of the E horizon thickness was similar, the increase was attributed to stemflow and precipitation of organic compounds in the podzol B horizon.

• Liski, E-mail: jl@mm.unknown

A simple, manually-operated and easily portable device for sampling volumetric soil cores to a depth of 100 cm with a minimum soil disturbance is described. The device consists of a sample tube, a sampler and an extension tube. A dead blow nylon mallet is used to force the sampler into the soil and a small winch attached to an aluminium tube pulls the sampler from the soil. The total weight of the equipment (sampler, mallet and winch) is 18.5 kg and may be carried in the trunk of a small car. Sampling is easily done by one person in good physical condition but four-handed operation is recommended as more efficient. The sampling device has been in heavy use during the summers of 1993–95 when several hundred soil cores have been extracted on various sites all over Finland.

• Westman, E-mail: cw@mm.unknown

A calculation procedure is presented for calculating and analysing remeasured permanent sample plots. Data for eight different fixed and variable size plot types were simulated on the basis of two stands whose trees were mapped and measured in 1982 and 1986. The accuracy and efficiency of the plot types were assessed and compared.

The calculation procedure is based on tree-wise expansion factors and the division of tree sampled into state/measurement classes. Nine classes were required for variable size plots and six for fixed size plots. A relascope plot with basal-area factor 1 (m²/ha) proved to be most efficient for estimating basal-area at a given time and a fixed size circular plot with radius 10 m for estimating basal-area increment over a given time period.

The main problems were related to the estimation of non-measurable variables, e.g., the initial diameters of ingrowth trees, i.e., trees having passed the threshold size during the measurement period. Most problematic were cut trees belonging to the ingrowth or sample enlargement classes. It is nevertheless thought that the system is appropriate for monitoring forest changes and making sensitivity analyses with permanent sample plots.

• Poso, E-mail: sp@mm.unknown
• Waite, E-mail: mw@mm.unknown

Tree height data from 33 progeny trials of Scots pine (Pinus sylvestris L.) were used to determine the effect of within-plot subsampling on the magnitude of statistically detectable differences between families, family heritability and correlation of family means based on different sample sizes. The results indicated that in trials established with a standard plot configuration of 25 trees per plot, measuring only 10–15 trees gives nearly the same precision as with assessment of all the plot trees. Even as few as 4–6 trees assessed per plot may constitute a sufficient sample if families or parental trees of extreme performance are being selected. Trials established with non-contiguous plots were found to be more efficient than those established using multiple-tree contiguous plots.

• Haapanen, E-mail: mh@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

Spatial and age-related variation in nutrient concentrations of Scots pine (Pinus sylvestris L.) needles was studied during 1984–86 in three stands of different stages of development. The dry weight of current needles was significantly (p < 0.05) higher in the tree top than in a composite sample representing the whole crown. However, there were no significant differences in the concentrations of nutrients in needles between upper and lower crown levels. The concentrations of mobile nutrients N, P, K and Mg decreased with increasing needle age whereas the concentrations of poorly mobile nutrients Ca, Mn and Fe increased during needle ageing. The coefficient of variation for nutrient concentrations varied irregularly when only a few trees were sampled but stabilized when tree number was ten or more.
The PDF includes an abstract in Finnish.

• Helmisaari, E-mail: hh@mm.unknown

In producing time series of soil properties, there are many technical and statistical problems which need to be taken into account when sampling and analysing the measurement data. In field the reliable localization of sample plots and the precise distinction of different soil layers are important to reduce the variance caused by the sampling procedure. In laboratory the use of same extraction salt, sample pretreatment procedure and filter paper throughout a measurement series is important. The remarkable small-scale variation within a sampling plot leads to a need of a large number of samples to be collected.

In this study, no trends attributable to soil acidification in the contents of exchangeable base cations could be found among the years 1982, 1985 and 1988. However, in eluvial and illuvial layers the pH decreased and the content of extractable H+ increased during this period. In illuvial layer also the content of extractable aluminium increased.

The PDF includes an abstract in Finnish.

• Ilvesniemi, E-mail: hi@mm.unknown

Correlation functions of the mean volume, land use class and soil class were estimated using the data of the Finnish National Forest Inventory. Estimated functions were used for approximating the standard error of e.g. the mean volume of a cluster of plots. Standard error estimates can be used for comparing different inventory designs.

The PDF includes an abstract in Finnish.

• Korhonen, E-mail: kk@mm.unknown
• Maltamo, E-mail: mm@mm.unknown

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.

• Päivinen, E-mail: rp@mm.unknown
• Yli-Kojola, E-mail: hy@mm.unknown

A method for using satellite data in forest inventories and updating is described and tested. The stand characteristics estimated by the method showed high correlation with the same characteristics measured in the field. The correlation coefficients for volume, age and mean height were about 0.85. It seems that the method is applicable to practical forestry. Extensive work in programming, however, is required.

The PDF includes an abstract in Finnish.

• Poso, E-mail: sp@mm.unknown
• Paananen, E-mail: rp@mm.unknown
• Similä, E-mail: ms@mm.unknown

Three replacement strategies in continuous forest inventory of the Enso-Gutzeit Company have been presented and discussed. The first strategy adopts data from only the last two inventory occasions; the second strategy employs data from all four occasions, in which there are two groups of permanent plots measured on the first three occasions and independently on the last two occasions; the third strategy also utilizes data from all four occasions, but includes only one group permanent plots measured on all four occasions. Results indicate that the last strategy is best for efficiency. The difference between the first two strategies is small. 

The PDF includes an abstract in Finnish.

• Peng, E-mail: sp@mm.unknown

Different sampling methods (the percentage cover scale, the graphical method, two-point quadrat methods, the five-, nine- and twelve-class cover scales, and the biomass harvesting) were used in estimating abundance of ground vegetation in clear-cut areas and on an abandoned field in Southern and Central Finland. The results are examined with the help of DCA ordinations. In addition, the species numbers and diversity indices obtained by different sampling methods are compared.

There were no large differences in DCA configurations between the sampling methods. According to all the sampling methods, a complex soil fertility-moisture gradient (a forest site type) was interpreted as the main ordination gradient in the vegetation data for clear-cut areas. However, different sampling methods did not give similar estimates of species numbers and diversity indices.

The PDF includes a summary in Finnish.

• Jukola-Sulonen, E-mail: ej@mm.unknown
• Salemaa, E-mail: ms@mm.unknown

The choice of sampling method is of prime importance when seeking relevant information about the height distribution and spatial arrangement of seedlings in the regeneration surveys. It is suggested that the size of sampling plots should depend on the height of the seedlings. Tall seedlings should be sampled from a larger area than short ones since tall seedlings are more important for the future development of the stand. We suggest principles for a technical development task to construct a device which is easy to use in practical regeneration surveys and by which sampling can be made proportional to plant height or any desired function of height.

The PDF includes a summary in Finnish.

• Lappi, E-mail: jl@mm.unknown
• Kotisaari, E-mail: ak@mm.unknown
• Smolander, E-mail: hs@mm.unknown

Measurement of timber in a vehicle load or in a bundle is best performed at the mill where the measuring of large quantities can be mechanized and sampling is possible. Load measurement methods include calculation of the number of units, measurement of pile volume, weight scaling and determination of solid content in accordance with Archimedes principle by immersion in water. For some timber assortments, load measurement is sufficiently accurate and suitable unit of measure. The accuracy of load measurement can be increased or the result can be converted by sampling to a more appropriate unit of measure.

In load sampling measurement, a sample is taken from the population, and the desired more accurate measurement is made from the sample. The basic measurement for the whole population can be converted into the more accurate measuring unit by means of the ratio between it and the basic measure. Unit, pile and weight sampling can be used. The aim for pulpwood is to calculate the dry matter content without bark, which means that the amount of bark and the dry weight of wood must be determined by sampling.

The size of the sample depends on size of the population, variation of the ratio between the loads, and the accuracy required. As the quantity of wood to be measured decreases, sampling measurement will reduce the measuring costs by up to 80%. In addition, there is saving in costs by rationalization.

The PDF includes a summary in English.

• Leinonen, E-mail: el@mm.unknown
• Rikkonen, E-mail: pr@mm.unknown

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.

• Stern, E-mail: ks@mm.unknown

This paper reports on tests made for the study of alternative methods in forest survey. Data were acquired by measurements in five areas in Finland and in Mexico, varying in size from 20 to 900 ha. The principal characteristics used in the analysis was the entire volume. By the combination of neighbouring plots, the variation could be studied for different plot sizes and survey strips. Variable (relascope) plots could be compared.

A starting point for the comparison of different sampling methods, calculations were made of the coefficients of variation for each plot type; total and within the strata. The amount of decrease of variation with an increasing plot size could be established. Comparisons have been made of the following sampling methods: simple random, stratified random, simple systematic, and stratified systematic sampling.

On comparisons of the standard error of sample mean it was found that in both stratified sampling and different types of systematic sampling there is, with increasing size and diminishing interval of sample plots, an increase in the relative improvement of the result against simple random sampling. Only in exceptional cases did systematic surveys give results which were less precise than those derived by other methods.

In discussion of some methods for determination of the precision of systematic sampling, possibilities of theoretical determination of the degree of precision was considered. An empirical study was made of the behaviour of some equations based on the sample itself. The larger the plot size and the shorter the plot interval, the more the equations overestimated in general the variance of sample mean.

As none of the equations studied gave reliable results, regression equations were calculated for the relative standard error on the basis of the data measured. The independent variables were plot size, plot or strip interval, area of survey unit and mean volume. The results arrived at are based mainly on the complete measurement of one area only. To enable extension of the scope of application, more material is needed with a complete enumeration of trees.

The PDF includes a summary in Finnish.

• Nyyssönen, E-mail: an@mm.unknown
• Kilkki, E-mail: pk@mm.unknown
• Mikkola, E-mail: em@mm.unknown

Highest degree of precision in determining the areas of different strata in forest survey is achieved when the areas are measured from a map. However, in practice the stratum-areas usually need to be determined on the basis of samples taken in the field or from aerial photographs. The goal of the present investigation was to determine the precision in stratum-area estimation on the application of different sampling methods.

Three sampling methods were used: 1. sampling with random plots, 2. uniform systematic plot sampling, and 3. sampling with equidistant lines.

The dependence of the standard error of stratum-areas in systematic line and plot sampling was examined by regression analysis. The models for regression equations were derived from random sampling formulae. It appears that the characteristics of these formulae were applicable as variables in the regression equations for systematic samples. Also, some characteristics of the distribution of the stratum was found, which seem to influence the error in sampling with equidistant lines.

The results as regards uniform systematic plot sampling indicate that the use of random sampling formulae leads to considerable over-estimation of the standard error. Nonetheless, unless relatively short intervals between sample plots are used in the forest survey made on the ground, it is of advantage to study the division of the area into strata by measuring the distribution of the survey lines in these strata.

The results can be used in two ways: for estimation of the precision in a survey already made, or to predetermine the sample size in a survey to be made. The results may be applicable to areas ranging from 100 to 1,000 ha in size, as well as to larger areas.

• Nyyssönen, E-mail: an@mm.unknown
• Kilkki, E-mail: pk@mm.unknown

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.

• Nyyssönen, E-mail: an@mm.unknown
• Kilkki, E-mail: pk@mm.unknown

To enhance the utilization of the wood, the sawmills are forced to place more emphasis on planning to master the whole production chain from the forest to the end product. One significant obstacle to integrating the forest-sawmill-market production chain is the lack of appropriate information about forest stands. Since the wood procurement point of view in forest planning systems has been almost totally disregarded there has been a great need to develop an easy and efficient pre-harvest measurement method, allowing separate measurement of stands prior to harvesting. The main purpose of this study was to develop a measurement method for Scots pine (Pinus sylvestris L.) stands which forest managers could use in describing the properties of the standing trees for sawing production planning.

Study materials were collected from ten Scots pine stands located in North Häme and South Pohjanmaa, in Southern Finland. The data comprise test sawing data on 314 pine stems, diameter at breast height (dbh) and height measures of all trees and measures of the quality parameters of pine sawlog stems in all ten study stands as well as the locations of all trees in six stands. The study was divided into four sub-studies which deal with pine quality prediction, construction of diameter and dead branch height distributions, sampling designs and applying height and crown height models. The final proposal for the pre-harvest measurement method is a synthesis of the individual sub-studies.

Quality analysis resulted in choosing dbh, distance from stump height to the first dead branch, crown height and tree height as the most appropriate quality characteristics of Scots pine. Dbh and dead branch height are measured from each pine sample tree while height and crown height are derived from dbh measures by aid of mixed height and crown height models. Pine and spruce diameter distribution as well as dead branch height distribution are most effectively predicted by the kernel function. Roughly 25 sample trees seem to be appropriate in pure pine stands. In mixed stands the number of sample trees needs to be increased in proportion to the intensity of pines in order to attain the same level of accuracy.

• Uusitalo, E-mail: ju@mm.unknown

The study concerns with the methodology and efficiency of integrating multitemporal satellite image data with permanent sample plots in a continuous forest inventory and compartment wise estimation. The generalized least squares estimation for the population, and the unsupervised stratification for compartments, are the main estimation methods employed. The experimental material is composed of real and simulated multitemporal images (Landsat TM) and field data. Precision analyses for the estimation and comparisons for a number of estimation and updating methods, as well as statistical options are given.

The PDF includes a summary in Finnish.

• Peng, E-mail: sp@mm.unknown

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.

• Nyyssönen, E-mail: an@mm.unknown
• Roiko-Jokela, E-mail: pr@mm.unknown
• Kilkki, E-mail: pk@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

In Thailand and various other countries tree seedlings are generally planted using simple manual tools, often a ‘planting stick’, but the method requires time-consuming, labour-intensive teamwork. However, use of a ‘planting tube’ allows a single person to perform both the preparation and planting work. Thus, in a classical time study and ergonomic survey we compared the productivity, cost-effectiveness, and ergonomic impact of planting Eucalyptus spp. seedlings using the two tools at the same planting site in Western Thailand. The planting tube method proved to be more productive, more cost-efficient, and less burdensome than the planting stick method (with time and cost requirements of 21 s and €0.0061 per seedling, versus 16.6 s and €0.0463 per seedling, respectively). In conclusion, the planting tube method may be a viable alternative to reduce costs and increase productivity, while maintaining reasonable workloads for the workers, despite the higher purchase price of planting tubes.

• Kaakkurivaara, Department of Forest Engineering, Faculty of Forestry, Kasetsart University, 50 Phahonyothin Rd, Lat Yao, Chatuchak, Bangkok 10900, Thailand E-mail: tomi.kaakkurivaara@gmail.com
• Kaakkurivaara, Department of Forest Engineering, Faculty of Forestry, Kasetsart University, 50 Phahonyothin Rd, Lat Yao, Chatuchak, Bangkok 10900, Thailand E-mail: ffornrm@ku.ac.th

Growing demand for wood products, combined with efforts to conserve natural forests, have supported a steady increase in the global extent of planted forests. Here, a two-phase sampling strategy for large-scale assessment of the total area and the total wood volume of fast-growing forest tree crops within agricultural land is presented. The first phase is performed using tessellation stratified sampling on high-resolution remotely sensed imagery and is sufficient for estimating the total area of plantations by means of a Monte Carlo integration estimator. The second phase is performed using stratified sampling of the plantations selected in the first phase and is aimed at estimating total wood volume by means of an approximation of the first-phase Horvitz-Thompson estimator. Vegetation indices from Sentinel-2 are exploited as freely available auxiliary information in a linear regression estimator to improve the design-based precision of the estimator based on the sole sample data. Estimators of the totals and of the design-based variances of total estimators are presented. A simulation study is developed in order to check the design-based performance of the two alternative estimators under several artificial distributions supposed for poplar plantations (random, clustered, spatially trended). An application in Northern Italy is also reported. The regression estimator turns out to be invariably better than that based on the sole sample information. Possible integrations of the proposed sampling scheme with conventional national forest inventories adopting tessellation stratified sampling in the first phase are discussed.

• Marcelli, University of Tuscia, Department for Innovation in Biological, Agro-food and Forest systems, Viterbo, Italy; Fondazione Edmund Mach, Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, San Michele all’Adige, Italy E-mail: agnese.marcelli@student.unisi.it
• Mattioli, University of Tuscia, Department for Innovation in Biological, Agro-food and Forest systems, Viterbo, Italy; CREA, Research Centre for Forestry and Wood, Arezzo, Italy E-mail: walter.mattioli@crea.gov.it
• Puletti, CREA, Research Centre for Forestry and Wood, Arezzo, Italy E-mail: nicola.puletti@crea.gov.it
• Chianucci, CREA, Research Centre for Forestry and Wood, Arezzo, Italy E-mail: fchianucci@gmail.com
• Gianelle, Fondazione Edmund Mach, Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, San Michele all’Adige, Italy E-mail: damiano.gianelle@fmach.it
• Grotti, CREA, Research Centre for Forestry and Wood, Arezzo, Italy; University of Roma La Sapienza, Department of Architecture and Design, Rome, Italy E-mail: mirkogrotti@gmail.com
• Chirici, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy E-mail: gherardo.chirici@unifi.it
• D' Amico, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy E-mail: giovanni.damico@unifi.it
• Francini, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy; University of Molise, Department of Agricultural, Environmental and Food Sciences, Campobasso, Italy E-mail: saverio.francini@gmail.com
• Travaglini, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy E-mail: davide.travaglini@unifi.it
• Fattorini, University of Siena, Department of Economics and Statistics, Siena, Italy E-mail: lorenzo.fattorini@unisi.it
• Corona, CREA, Research Centre for Forestry and Wood, Arezzo, Italy E-mail: piermaria.corona@crea.gov.it

Climate change has been estimated to increase the risk of storm damage in forests in Finland. There is a growing need for methods to obtain information on the extent and severity of storm damage after a storm occurrence. The first objective of this study was to test whether digital photographs taken from aircrafts flying at low-altitude can be utilized in locating storm-damaged areas and estimating the need for harvesting of wind-thrown trees. The second objective was to test the performance of selected estimators. Depending on distances between flight lines, plots on lines and the used estimator, the relative standard errors of storm area estimates varied between 7.7 and 48.7%. For the area for harvesting and volume of wind-thrown trees, the relative standard errors of estimates varied between 16.8 and 167.3%. Using forest area information from Multisource National Forest Inventory data improved the accuracy of the estimates. However, performance of a simple random sampling estimator and ratio estimator were quite similar. Lindeberg’s method for variance estimation based on adjacent lines was sensitive to line directions in relation to possible trends in storm-damaged area locations. Our results showed that the tested method could be used in estimating storm-damaged area provided that the network of flight lines and photographs on lines are sufficiently dense. The developed model for simulations can be utilized also with forthcoming storms as model’s parameters can be freely adjusted to meet, e.g., the intensity and extent of the storm.

• Hyvönen, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: pekka.hyvonen@luke.fi
• Heinonen, E-mail: jaakkoheinonen@gmail.com

Forest ecological restoration by burning is widely applied to promote natural, early-successional sites and increase landscape biodiversity. Burning is also used as a forest management practice to facilitate forest regeneration after clearcutting. Besides the desired goals, restoration burnings also affect soil biogeochemistry, particularly soil organic matter (SOM) and related soil carbon stocks but the long-term effects are poorly understood. However, in order to study these effects, a reliable estimate of spatial variability is first needed for effective sampling. Here we investigate spatial variability of SOM and vegetation features 13 years after burnings and in combination with variable harvest levels. We sampled four experimental sites representing distinct management and restoration treatments with an undisturbed control. While variability of vegetation cover and biomass was generally higher in disturbed sites, soil parameter variability was not different between the four sites. The joint ecological patterns of soil and vegetation parameters across the whole sample continuum support well the prior assumptions on the characteristic disturbance conditions within each of the study sites. We designed and employed statistical simulations as a means to plan prospective sampling. Sampling six forest sites for each treatment type with 30 independent soil cores per site would provide enough statistical power to adequately capture the impacts of burning on SOM based on the data we obtained here and statistical simulations. In conclusion, we argue that an informed design-based approach to documenting the ecosystem effects of forest burnings is worth applying both through obtaining new data and meta-analysing the existing.

• Čugunovs, University of Eastern Finland, School of Forest Sciences, Yliopistokatu 7, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: mihails.cugunovs@uef.fi
• Tuittila, University of Eastern Finland, School of Forest Sciences, Yliopistokatu 7, P.O. Box 111, FI-80101 Joensuu, Finland http://orcid.org/0000-0001-8861-3167 E-mail: eeva-stiina.tuittila@uef.fi
• Mehtätalo, University of Eastern Finland, School of Computing, Science Park, Länsikatu 15, P.O. Box 111, 80101 Joensuu, Finland http://orcid.org/0000-0002-8128-0598 E-mail: lauri.mehtatalo@uef.fi
• Pekkola, University of Eastern Finland, School of Forest Sciences, Yliopistokatu 7, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: laura.pekkola@gmail.com
• Sara-Aho, University of Eastern Finland, School of Forest Sciences, Yliopistokatu 7, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: ida.sara-aho@mhy.fi
• Kouki, University of Eastern Finland, School of Forest Sciences, Yliopistokatu 7, P.O. Box 111, FI-80101 Joensuu, Finland http://orcid.org/0000-0003-2624-8592 E-mail: jari.kouki@uef.fi

The quantification of the contribution of tropical forests to global carbon stocks and climate change mitigation requires availability of data and tools such as allometric equations. This study made available volume and biomass models for eighteen tree species in a semi-deciduous tropical forest in West Africa. Generic models were also developed for the forest ecosystem, and basic wood density determined for the tree species. Non-destructive sampling approach was carried out on five hundred and one sample trees to analyse stem volume and biomass. From the modelling of volume and biomass as functions of diameter at breast height (Dbh) and stem height, logarithmic models had better predictive capabilities. The model validation showed that in absence of data on height, models using Dbh only as variable was an alternative. The comparison of basic wood densities to data published in literature enabled to conclude that the non-destructive sampling was a good approach to determining reliable basic wood density. The comparative analysis of species-specific models in this study with selected generic models for tropical forests indicated low probability to identify effective generic models with good predictive ability for biomass. Given tree species richness of tropical forests, the study demonstrated the hypothesis that species-specific models are preferred to generic models, and concluded that further research should be oriented towards development of specific models to cover the full range of dominant tree species of African forests.

• Goussanou, Laboratory of Applied Ecology, Faculty of Agronomic Sciences, University of Abomey-Calavi, 01 BP 526 Cotonou, Benin E-mail: cedricgoussanou@gmail.com
• Guendehou, Laboratory of Applied Ecology, Faculty of Agronomic Sciences, University of Abomey-Calavi, 01 BP 526 Cotonou, Benin; Benin Centre for Scientific and Technical Research, 03 BP 1665 Cotonou, Benin E-mail: sguendehou@yahoo.fr
• Assogbadjo, Laboratory of Applied Ecology, Faculty of Agronomic Sciences, University of Abomey-Calavi, 01 BP 526 Cotonou, Benin E-mail: assogbadjo@yahoo.fr
• Kaire, Centre Régional AGRHYMET, Département Formation et Recherche, BP 11011 Niamey, Niger E-mail: m.kaire@agrhymet.ne
• Sinsin, Laboratory of Applied Ecology, Faculty of Agronomic Sciences, University of Abomey-Calavi, 01 BP 526 Cotonou, Benin E-mail: bsinsin@gmail.com
• Cuni-Sanchez, University of Copenhagen, Center for Macroecology, Evolution and Climate, Nørregade 10, P.O. Box 2177, 1017 Copenhagen K, Denmark E-mail: aidacuni@hotmail.com

• Tuominen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: sakari.tuominen@metla.fi
• Pitkänen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: juho.pitkanen@metla.fi
• Balazs, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: andras.balazs@metla.fi
• Korhonen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: kari.t.korhonen@metla.fi
• Hyvönen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: pekka.hyvonen@metla.fi
• Muinonen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: eero.muinonen@metla.fi

• Gobakken, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, Ås, Norway E-mail: terje.gobakken@umb.no
• Korhonen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: lauri.korhonen@uef.fi
• Næsset, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, Ås, Norway E-mail: erik.naesset@umb.no

• Magnussen, Canadian Forest Service, Natural Resources Canada, 505 West Burnside Road, Victoria BC V8Z 1M5 Canada E-mail: steen.magnussen@nrcan.gc.ca

• Pulkkinen, E-mail: minna.pulkkinen@iki.fi

• Coggins, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, B.C., Canada V6T 1Z4 E-mail: scoggins@interchange.ubc.ca
• Coops, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, B.C., Canada V6T 1Z4 E-mail: ncc@nn.ca
• Wulder, Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Rd., Victoria, B.C., Canada V8Z 1M5 E-mail: maw@nn.ca

• Korhonen, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland E-mail: lauri.korhonen@joensuu.fi
• Korhonen, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland E-mail: ktk@nn.fi
• Rautiainen, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland E-mail: mr@nn.fi
• Stenberg, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland E-mail: ps@nn.fi

• Talvitie, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: mervi.talvitie@helsinki.fi
• Leino, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ol@nn.fi
• Holopainen, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ah@nn.fi

• Cancino, Facultad de Ciencias Forestales, Universidad de Concepción, Chile E-mail: jcancino@udec.cl
• Saborowski, Institut für Forstliche Biometrie und Informatik, Georg-August-Universität Göttingen, Germany E-mail: js@nn.de

• 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

• Tuominen, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland E-mail: sakari.tuominen@metla.fi
• Poso, Department of Forest Resource Management, P.O. Box 27, FIN-00014 University of Helsinki, Finland E-mail: sp@nn.fi

• Poso, Department of Forest Resource Management, P.O. Box 24 (Unioninkatu 40 B), FIN-00014 University of Helsinki, Finland E-mail: simo.poso@helsinki.fi
• Wang, Department of Forest Resource Management, P.O. Box 24 (Unioninkatu 40 B), FIN-00014 University of Helsinki, Finland E-mail: gw@nn.fi
• Tuominen, Department of Forest Resource Management, P.O. Box 24 (Unioninkatu 40 B), FIN-00014 University of Helsinki, Finland E-mail: st@nn.fi

• Fridman, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden E-mail: jonas.fridman@slu.se
• Holm, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden E-mail: soren.holm@slu.se
• Nilsson, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden E-mail: mats.nilsson@slu.se
• Nilsson, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden E-mail: per.nilsson@slu.se
• Ringvall, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden E-mail: Anna.Ringvall@slu.se
• Ståhl, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden E-mail: goran.stahl@slu.se

Dieback of the common ash (Fraxinus excelsior L.) has been spreading throughout Europe since the 1990s, causing severe ecological and economical consequences; however, detailed statistics on its dynamics have been published rarely. This paper presents the dynamics of mature ash-dominated stands in Latvia for the period 2005–2015. Data from the national forest inventory and a permanent sampling plot network were summarised. According to the official statistics, the dieback has caused a twofold decrease in area of the ash stands (from 21 891 to 13 011 ha, which respectively comprised ca. 0.8 to ca. 0.4% of the total forest area). The official statistics on standing volume appeared biased, as they did not account for increased mortality. According to the permanent sampling plots, standing volume and stand density have been affected even more, having decreased by 53.1 and 69.9%, respectively, compared to 2005 (the stand density and standing volume of ash in 2015 was 77 individuals ha^–1 and 151 m³ ha^–1, respectively). The mortality of the trees has not been stable. Stand density decreased faster during 2005–2009 compared to 2010–2015, with mortality rates of 9.6 and 8.2% year^–1, respectively. In contrast, the decrease in standing volume in 2005–2009 was slower than in 2010–2015 (mortality rates were 4.7 and 7.7% year^–1, respectively) because trees with smaller dimensions were more susceptible to the dieback. Nevertheless, the observed mortality rates clearly indicate negative prospects for ash stands in Latvia.

• Matisone, Latvian State Forest Research Institute (LSFRI) Silava, Rigas str. 111, Salaspils, Latvia, LV2169 E-mail: ilze.matisone@silava.lv
• Matisons, Latvian State Forest Research Institute (LSFRI) Silava, Rigas str. 111, Salaspils, Latvia, LV2169 E-mail: robism@inbox.lv
• Laiviņš, Latvian State Forest Research Institute (LSFRI) Silava, Rigas str. 111, Salaspils, Latvia, LV2169 E-mail: maris.laivins@silava.lv
• Gaitnieks, Latvian State Forest Research Institute (LSFRI) Silava, Rigas str. 111, Salaspils, Latvia, LV2169 E-mail: talis.gaitnieks@silava.lv