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The stand level gross volume increment models are used to estimate the future production of tree stands. Very often, the stand growth and yield in the models used in practice are described by the tree volume increment that includes the diameter growth function with the tree height together with stem taper as the input variables. The currently used function of stand volume increment in Estonia included also stand relative density as an additional input variable. In the current study, we developed a basal area increment function based on the periodic measurement data of the Estonian Network of Forest Research Plots (ENFRP). As in the earlier model of stand volume increment developed by Priit Kohava, in the current model the basal area increment of tree species is developed for a pure stand, and for mixed stands, the proportion of the tree species’ basal area is used. The tests in our data indicated that the periodic increment prognosis had good fit in the case of variable share of tree species in the main storey and coincide with the earlier studies by Finnish and Swedish colleagues. The developed model of basal area increment predictions are expectedly higher than the earlier model predictions for the most tree species and stand relative densities.

Knowledge about the seasonal dynamics of tree growth and its relationship with environmental factors is necessary to eliminate the uncertainty due to ongoing climate change and for more precise growth modelling when re-measurements are done periodically. Despite the increasing number of studies monitoring seasonal wood formation, a considerable part of European forests, including Estonia, lacks such information. In this article, we present a date-dependent model for determining the share of seasonal radial growth for the three most common tree species in the region (Scots pine, Norway spruce and silver birch) for Estonian conditions. Since seasonal tree growth monitoring data were unavailable for Estonia, we used published seasonal radial growth data from Lithuania by Dr Adomas Vitas (2011). We tested four functions (Kumaraswamy, Weibull, Gompertz and logistic) on obtained data to approximate the seasonal development of radial growth. Kumaraswamy’s function could track the course of seasonal radial growth gains the best; thus, this function was chosen for further use. We obtained data on intra-annual radial growth from published research studies from neighbouring countries and determined the dates of growth initiation and cessation for Estonian conditions. Finally, we combined Kumaraswamy’s function and the predicted radial growth onset and cessation dates into the model that could predict the seasonal growth course and thus were able to estimate the share of newly formed increment from the dates.

The study area is in the Järvselja Training and Experimental Forest Centre, Estonia. The conservation of Järvselja old-growth forest started in 1924 when the area was excluded from all management activities and left to natural development. The aim of this study is to analyse the methods for calculating single tree height, tree stem lateral surface area, tree volume and carbon content for standing live trees, standing dead trees and for downed deadwood in old-growth forests. The study used the data of 6205 live trees, 1119 snags, 270 standing dead trees and 2983 deadwood trunks from the measured area. The most abundant tree species in Järvselja old-growth forest were Norway spruce and linden. During the last hundred years, the number of dominating tree species has increased slightly. The standing volume of birch, common aspen and Scots pine have been declining while for linden and black alder it has been increasing. In the comparison of tree height curves, the best results were obtained with the Näslund function, however, the Chapman-Richards function with fitting showed slightly better results for two tree species.

2007. aastal rajati Järvseljal kolm ühe hektari suurust katseala, kui kaardistati ja mõõdeti üle kõik puud simulatsioon eksperimentide korraldamiseks (Kuusk, et al., 2013; Widlowski et al., 2015). Need kolm puistut (vt fotod lisas 1) esindavad tüüpilist liitunud võrastikuga kuusikut, kaasikut ja siirdesoo männikut. Kaasikus oli tehtud 2004. aastal harvendusraie, 2018. aastal puhastati katseala alusmetsast, et valmistada ala ette maapealse laser skanneriga mõõtmisteks. Kuusikus ja männikus teadaolevalt viimase 30 aasta jooksul raieid tehtud ei ole. Katsealade (joonised 1, 3, 5) nurkade koordinaadid on mõõdetud diferentsiaal-GPS meetodiga peale mahamärkimist (tabel 1). 2019. aasta kordus mõõtmiste tulemusena ilmnes, et puistute rinnaspindala, keskmine kõrgus ning keskmise puu rinnasläbimõõt olid kasvanud (tabelid 2–4). Puude arv oli kahanenud kõigis puistutes, välja arvatud kaasikus, kus 2018. aasta puhastus raie käigus jäeti alles selleks ajaks 4 cm rinnasdiameetri saavutanud puud. Kuusikus saadi tulemuseks, et võrade raadiused olid võrreldes 2007. aastaga kahanenud. Kas tegemist on võra projektsiooni välispiiri erineva tõlgendamise või tegelikult toimunud muutusega, võiks edaspidi selguda 2013. (Kuusk et al., 2015) ja 2019. aastal tehtud maapealse laserskanneri mõõtmiste andmete analüüsist.

Since 1999, Estonia has conducted the National Forest Inventory (NFI) on the basis of sample plots. This paper presents a new module, incorporating remote-sensing feature variables from airborne laser scanning (ALS) and from multispectral satellite images, for the construction of maps of forest height, standing-wood volume, and tree species composition for the entire country. The models for sparse ALS point clouds yield coefficients of determination of 89.5–94.8% for stand height and 84.2–91.7% for wood volume. For the tree species prediction, the models yield Cohen's kappa values (taking 95% confidence intervals) of 0.69–0.72 upon comparing model results against a previous map, and values of 0.51–0.54 upon comparing model results against NFI sample plots. This paper additionally examines the influence of foliage phenology on the predictions and discusses options for further enhancement of the system.

The availability of a large amount of data from reliable sources is important for forest growth modelling. A permanent plot where trees are repeatedly measured provides a clearer picture of stand alterations. Various factors, including forest management, affect forest growth and accuracy of its assessment. In Estonia, mean height as a regression height prediction at mean square diameter is commonly used in forest management practice. Alternatively, dominant height can be used. The main advantage of using dominant height instead of mean height is that the growth of dominant trees is not so strongly affected by stand density (thinning). The aim of our research was to investigate the difference between mean height and dominant height when used as stand height. The research was based on the Estonian Network of Forest Research Plots (ENFRP). As a result, we found that the average mean height change was significantly greater in the case of thinning when compared to undisturbed stand development, whereas, the average dominant height change in the case of thinning compared to undisturbed development was less significant. As a side result, we developed a regression model that can be used for calculating the dominant height of the main tree species using stand attributes (mean height, quadratic mean diameter and density) with a residual standard deviation of 0.466 m.

Forest height increment rate is related to the forest growth conditions. Data bases of previous forest inventories contain information about forest heightage relationship on large number of forest stands while repeated measurements of permanent sample plots provide an excellent reference for comparison. Repeated airborne laser scanning of forest stands is an additional source for the estimation of change in forest structure. In this study, height growth of middle-aged and older forest stands for about 10 year period was compared to an algebraic difference model on permanent sample plots (66) and for a sample of forest stands with repeated airborne laser scanning data (61). The model was based on a large dataset of forest inventory records from the period of 1984–1993. Statistically significant increased forest height growth was found in permanent sample plots based on tree height measurements (9 cm yr−1) as well in stands with repeated laser scanning data (4.5 cm yr−1) in South-East Estonia compared to the algebraic difference model. The difference between the two data sets was explained by their mean age and site class, but the increased forest height growth compared to the old forest inventory data indicates improved growth conditions of forests in the test area. The results hint also that empirical data-based forest growth models need to be updated to avoid biased growth estimates.

A new paradigm in forest management using a streaming input of public participation needs effective online solutions. The process should be real-time, secure, effective and efficient. People are expected to share their data and thoughts on forest management with forest owners for improving forest management and planning. The participatory approach supports communication within society and can be designed as an interactive web-based solution. Many pre-requisites have already been met and society is ready for a successful start of an interactive participatory forest planning system in Estonia. People use digital identification for various purposes and the state already maintains an online public forest register. Motivating people to participate in the planning process is always challenging yet important for the successful implementation of the system. The system should allow simulating the development and management of forest stands following the participatory input and using ecosystem models and economic calculations. The outputs from the system include management alternatives, risk assessments and financial reports. The system requires a reliable financial compensation scheme to ensure overall long-term stability of the system and agreements between interested persons or groups and forest owners.

A generic regression model for above-ground biomass of forest stands was constructed based on published data (R2 = 0.88, RSE = 32.8 t/ha). The model was used 1) to verify two allometric regression models of trees from Scandinavia applied to repeated measurements of 275 sample plots from database of Estonian Network of Forest Research (FGN) in Estonia, 2) to analyse impact of between-tree competition on biomass, and 3) compare biomass estimates made with different European biomass models applied on standardized forest structures. The model was verified with biomass measurements from hemiboreal and tropical forests. The analysis of two Scandinavian models showed that older allometric regression models may give biased estimates due to changed growth conditions. More biomass can be stored in forest stands where competition between trees is stronger. The tree biomass calculation methods used in different countries have also substantial influence on the estimates at stand-level. A common database of forest biomass measurements from Europe in similar to pan-tropical tree measurement data may be helpful to harmonise carbon accounting methods.

Growth assessment of young stands gives the possibility of assessing forest site potential, tree species-dependent competition and developing realistic predictions for the following periods. The study is conducted in naturally regenerated broadleaves dominated stands in 2005 at Järvselja Training and Experimental Forest Center. The current study material is collected from 9 study plots established in three forest stands (regeneration felling years respectively 1996, 2000 and 2002). The study plots were re-measured 4–6 times respectively between the years of 2006 and 2012. The Weibull distribution function fit for empirical height distributions in consecutive years was tested and the estimated Weibull parameters were analysed. Results indicate that empirical height distributions of young regenerated forests do not fit well to theoretical distributions, but in many cases, empirical and theoretical distribution are similar. The Weibull distribution shape parameter was related to the maximum height and range of the height, and the scale parameter was related to the mean, quadratic mean and median height.

Structural indices and characteristics have often been employed for assessing different aspects of forest stands. In order to assess the performance of such measures in forest sample plots of different size and shape, the current study is based on a data set for a relatively large (1 ha) silver birch dominated stand, and five simulated planar point patterns (a Poisson process, two clustered and two regular patterns) with similar intensity of points distributed on an area equal to the silver birch stand as reference stands. The analyses was based on repeated samplings of the stands, with randomly placed circular or square shaped plots of different sizes, with area ranging from 0.007 to 0.636 ha. Similar centre positions were considered for plots of different shapes, but the locations of the plot centres differed with size, so that plots of different sizes were able to cover the maximum possible area of reference stands. Some structural indices accounting for one or four nearest neighbours, and also the Point-pair correlation function was then quantified for each random sample plot. We used standard deviation and the differences of the mean estimates from the expected values to assess the sensitivity of the structural measures to the size and shape of sampling plots. The results indicated the significant effect of plot size and shape on structural indices. The correlation between plot size and estimates precision was positive, and small plots, regardless of their shapes, showed big variation among them while circular plots often provided more accurate estimates. Even though, as expected, expanding the plots increased the precision of the neighbourhood-based indices’ estimates (spatial measures), and also resulted in inaccurate estimates for some reference stands, depending on the arrangement of trees/points within that stand.

Forest research has long traditions in Estonia that can be traced back to the 19th century. Data from long-term forest experiments are available since 1921. The first studies mainly focused on silvicultural treatments and application of such data for understanding and modeling ecological processes was limited. The Department of Forest Management of the Estonian University of Life Sciences started to develop the Estonian Network of Forest Research Plots (ENFRP) in 1995. Since then, plots have been continuously re-measured with 5-year interval. Approximately 100-150 permanent sample plots were measured annually. In 2014, the long-term research network consisted of 729 permanent sample plots, of which 699 have been re-measured at least once, 667 plots - twice and 367 plots - three times. The total number of trees recorded in the network database amounts to 130,479. The plots are systematically distributed throughout the country. Detailed dendrometric measurements including tree spatial distribution are part of the survey protocol. Initially the network was set up to produce suitable data for development of individual tree growth models for Estonia. The significance of the network for the Estonian forest research is continuously increasing and nowadays ENFRP is recognized as an important national research infrastructure.

Forest management has become a more complex issue than it has ever been before. Foresters need to fulfill the demands of several interest groups, often which are conflicting. Finding the balance between different management objectives can be facilitated with the use of decision support systems. Since no decision support systems have been developed in Estonia, the aim of this study is to assess the applicability of the Finnish stand growth simulator MOTTI in Estonia. The evaluation focuses on the basal area growth models; the data used originates from the Estonian network of permanent forest growth plots. Tree-level bias models were constructed for all major tree species in order to assess model performance. Also, bias was examined visually with the use of residual plots. Results show that bias levels and variables which contribute to bias differ by species. Based on the fit statistics of the bias models, Common aspen shows the highest bias level whereas the growth of Gray alder seems to be predicted most accurately. Although model performance is decent for a model that is used outside of its application limits, calibration should still be considered as a prerequisite to implement the MOTTI system in Estonian forestry practice.

Altogether 197 grafts were studied in Pauska seed orchard in South-Estonia to find out the effect of the fertilization on Norway spruce grafts. The fertilization trials were carried out in May 1988 and 2006. The grafts of 4 different clones with 5 different fertilization treatments (N, P, K, NPK, control) were under study. The effect of three factors (fertilization, clone and year) on different characteristics of spruce grafts was studied. The linear methods with R software were used to find out relationships between variables. In addition to the morphological features and the content of nutrients in needles, the quantities and qualities of the mean cone and the weight of 1000 seeds were measured. Furthermore, the variation of quantities of needles (density, weight, length) and the content of nutrients in needles between years 1988 and 2007 were compared, using the linear methods with R software package. The morphological characteristics and nutrient content of needles, the mass of cones and seeds have depended the most on a calendar year. During the last research period (2003−2007), the needles of grafts under study were longer, lighter and with lower density compared to earlier research period (1988-1993). The effect of a clone was also essential. Needles of younger grafts were longer, heavier and set sparser than needles of older grafts. The needle nutrient content of younger grafts was also higher compared to the older ones. The effect of fertilizers on the grafts was dependent on the period of time. Nitrogen fertilizers increased the N-content in their needles during the first four years and also after repetitive fertilization. Phosphate fertilizers increased the P-content in their needles starting from the third year after their fertilization. The impact of potassium fertilizers on the K-content of their needles appeared 2−4 years after their fertilization. Combined fertilizers increased the N- and P-content in the needles to some extent, whereas it decreased their Ca- and Mg-content.

Growth assessment of young stands gives the possibility of assessing forest site potential, tree species-dependent competition and developing realistic predictions for the following periods. The study is conducted in naturally regenerated broadleaves dominated stands in 2005 at Järvselja Training and Experimental Forest Center. The current study material is collected from 9 study plots established in three forest stands (regeneration felling years respectively 1996, 2000 and 2002). The study plots were re-measured 4-6 times respectively between the years of 2006 and 2012. The Weibull distribution function fit for empirical height distributions in consecutive years was tested and the estimated Weibull parameters were analysed. Results indicate that empirical height distributions of young regenerated forests do not fit well to theoretical distributions, but in many cases, empirical and theoretical distribution are similar. The Weibull distribution shape parameter was related to the maximum height and range of the height, and the scale parameter was related to the mean, quadratic mean and median height. [ABSTRACT FROM AUTHOR]