Andres Kiviste

Construction of site index equations for Pinus sylvestris L. using permanent plot data in Sweden

Abstract Three general methods for construction of site index equations (the guide curve method, the parameter prediction method and the difference equation method) and 13 growth functions were tested on data from permanent plots in 156 Scots pine ( Pinus sylvestris ) stands. Most stands were of cultivated origin with known year of establishment. Data consisted of measured top height and total age at the start and at the end of observation periods of different lengths. Functions and construction methods were compared with respect to residual variation (root mean square error (RMSE), meter) from original data. The guide curve method gave RMSE ∼ 0.56 while the difference equation method with the anamorphic formulation gave RMSE ∼ 0.46, with appropriate functions. The difference equation method gave a higher RMSE with polymorphic than with anamorphic formulation. The special formulation of the Hossfeld function for the difference equation method proposed by Cieszewski and Bella [Cieszewski, C.J., Bella, I.E., 1989. Polymorphic height and site index curves for lodgepole pine in Alberta. Can. J. Res. 19, 1151–1160] gave a simple and straigtforward, polymorphic solution with RMSE = 0.40. The parameter prediction method, in combination with the deviation method proposed by Tveite [Tveite, B., 1969. A method for construction of site-index curves. Meddelelser fra Det Norske skogforsoksvesen 27, 134–159] and a four-parameter growth model, gave the lowest RMSE, but this solution had patterns of overfitting. Parameter prediction with the Mitscherlich function gave an equation with almost the same accuracy as the polymorphic difference equation with the Hossfeld function. These functions deviate much at higher ages, but too few observations in old stands in primary data prevented their separation. Published data from yield plots in old, natural stands supported the Hossfeld function. But, indications of a changed growth pattern in later decades still leave open the question of height growth pattern in old pine stands of cultivated origin. The presented Hossfeld equation can only be recommended for use in 10–80-year-old pine stands of cultivated origin.

Forest Structure and Diversity

This contribution presents methods that can be used to describe and analyse forest structure and diversity with particular reference to CCF management. Despite advances in remote sensing, mapped tree data in large observation windows are very rarely available in CCF management situations. Thus, although we present methods of second order statistics (SOC), the emphasis is on nearest neighbor statistics (NNS). The first section gives a general introduction and lists the objectives of the chapter. Methods of analysing non-spatial structure and diversity are presented in the second section. The third section introduces procedures for analysing unmarked and marked patterns of forest structure and diversity. Relevant R codes are provided to facilitate application of the methods. Examples of measuring differences between patterns and of reconstructing forests from samples are also presented. Finally, in Sect. 4 we discuss some important issues and summarize the main findings of this chapter.

A site‐index model for pure and mixed stands of Betula pendula and Betula pubescens in Sweden

A site‐index model was constructed based on stem analysis data for 266 top‐height trees of Betula pendula Roth and Betula pubescens Ehrh. growing on 155 temporary sample plots and 12 remeasured, permanent sample plots in pure and mixed stands scattered throughout Sweden. Different growth functions and techniques for modelling the top‐height growth over breast‐height age were assessed. A difference model based on the Hossfeld IV growth equation performed best, and its practical application was therefore recommended. For birch stands over 40 yrs of age, top‐height growth predicted by the new model was significantly slower than that predicted by a site‐index model used previously.

A spatially explicit height–diameter model for Scots pine in Estonia

This contribution presents an approach to model individual tree height–diameter relationships for Scots pine (Pinus sylvestris) in multi-size and mixed-species stands in Estonia using the Estonian Permanent Forest Research Plot Network. The dataset includes 22,347 trees. The main focus of the study was to use an approach that is spatially explicit allowing for high accuracy prediction from a minimum set of predictor variables that can be easily derived. Consequently, the height–diameter relationship is modeled as a function of only the stand quadratic mean diameter (dg) and the plot geographical coordinates. A specific generalized additive model gam is employed that allows for the integration of a varying coefficient term and 2-dimensional surface estimators representing a spatial trend and a spatially varying coefficient term. The high flexibility of the model is needed due to the very few predictor variables that subsume a variety of potential influential factors. Subsequently, a linear mixed model is used that quantifies the random variation between plots and between measurement occasions within plots, respectively. Hence, our model is based on the theory of structured additive regression models (Fahrmeir et al. 2007) and separates a structured (correlated) spatial effect from an unstructured (uncorrelated) spatial effect. Additionally, the linear mixed model allows for calibration of the model using height measurements as pre-information. Model bias is small, despite the somewhat irregular distribution of experimental areas within the country. The overall model shows some similarity with earlier applications in Finland. However, there are important differences involving the model form, the predictors and the method of parameter estimation.

Estimating tree survival: a study based on the Estonian Forest Research Plots Network

Tree survival, as affected by tree and stand variables, was studied using the Estonian database of permanent forest research plots. The tree survival was examined on the basis of remeasurements during the period 1995–2004, covering the most common forest types and all age groups. In this study, the influence of 35 tree and stand variables on tree survival probability was analyzed using the data of 31 097 trees from 236 research plots. For estimating individual tree survival probability, a logistic model using the logit-transformation was applied. Tree relative height had the greatest effect on tree survival. However, different factors were included into the logistic model for different development stages: tree relative height, tree relative diameter, relative basal area of larger trees and relative sparsity of a stand for young stands; tree relative height, relative basal area of larger trees and stand density for middle-aged and maturing stands; and tree relative height and stand density for mature and overmature stands. The models can be used as preliminary sub-components for elaboration of a new individual tree based growth simulator.

A conceptual model of forest stand development based on permanent sample-plot data in Estonia

Abstract Ecosystem management assumes that management practices based on natural disturbance patterns are likely to preserve both natural biodiversity and ecosystem functions. Ecosystem management thus combines traditional natural resource management and forestry practices together with classical notions of protection that are focused on sustaining a naturally evolving ecosystem. Increased knowledge and understanding of natural disturbance dynamics in boreal forest ecosystems allow for the creation of a template for sustainable forest management that is based on mimicking disturbances that are thought to contribute to the biodiversity of the ecosystem. The observed trends of natural development are discussed in this paper. Permanent sample-plot data are used to develop a conceptual model of stand succession following natural disturbance. The distinctive characteristics of disturbances that are relevant to forest management planning are identified and modelled.

Monitoring and modeling of forest ecosystems: the Estonian Network of Forest Research Plots / Metsaökosüsteemide seire ja modelleerimine metsa kasvukäigu püsiproovitükkide võrgustiku abil

Abstract 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.

Estimation of change in forest height growth

Abstract 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.

Online streaming public participation in forest management planning

Abstract 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.

Estimation of above-ground biomass in forest stands from regression on their basal area and height

Abstract 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.