Klaus von Gadow

Modelling forest development

1. Introduction. 2. Projecting Regional Timber Resources. 3. Modelling Stand Development. 4. Size Class Models. 5. Individual Tree Growth. 6. Model Evaluation. List of Symbols. Glossary. Literature.

An analysis of spatial forest structure using neighbourhood-based variables

Abstract The study presents an analysis of forest spatial structure and diversity in the Federal State of Durango where the majority of the forests consist of pure pine stands or pine mixed with oak. Natural forests of greater diversity and of high ecological significance are found only in a few isolated localities in the Santa Barbara valley. These forests, with rare conifers including the genera Picea, Abies and Pseudotsuga are found on particular sheltered, humid sites. For one such rare site, a detailed analysis of forest spatial structure was made, based on three one-quarter hectare plots where all the trees and their coordinates had been assessed. The objective of the study was to provide a quantitative description of the spatial structure of the plots, using new parameters of spatial diversity and to present a method for comparative analysis of the three forest sites. The analysis is using a new approach for describing complex forest structures in a straightforward manner. To evaluate the spatial attributes, it is not necessary to measure distances between trees or to establish tree coordinates. The spatial characteristics can be established merely on the basis of evaluating the immediate neighbourhood of a given number of reference trees. The variables describe the distributions of spatial mingling, size differentiation and contagion, which can be easily interpreted allowing quantitative comparisons between complex forest structures.

Continuous Cover Forestry

1 Historical Emergence and Current Application of CCF.- 2 Forest Structure and Diversity.- 3 Continuous Cover Forestry in Finland - Recent Research Results.- 4 Regulation of Timber Yield Sustainability for Tropical and Subtropical Moist Forests: Ecosilvicultural Paradigms and Economic Constraints.- 5 The Economics of Continuous Cover Forestry.- 6 Optimizing Continuous Cover Forest Management .- 7 Modelling Continuous Cover Forests.- 8 Bootstrap simulation, Markov decision process models, and role of discounting in the valuation of ecological criteria in uneven-aged forest management.- 9 Resource Assessment Techniques for Continuous Cover Forestry.

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.

Modeling stem profiles for Pinus densiflora in Korea

A new taper model is presented for Pinus densiflora in Korea. The new variable-exponent model describes well the gradually changing tree form along the stem. The changing exponent of the new model can be used to graphically compare different stem forms among tree groups. And various form indices numerically expressing stem form are derived from the new model. Five form indices: (1) taper rate of the butt section, (2) inflection point, (3) parabolic or paraconic range, (4) minimum exponent, and (5) relative height at the minimum exponent, are useful analytical tools for numerically comparing stem forms and stratifying trees into different form groups.

Modelling the relationship between tree diameters and heights using SBB distribution

Abstract The median regression and the 5- and 95-percentile curves of the bivariate S BB distribution were fitted to the diameter and height data of two forest stands. One data set represented Acacia tortilis trees in a pure stand, the other Fraxinus excelsior trees in a mixed forest. A median regression was established between heights and diameters and this was taken as the basis for calculating percentile lines which were used to set bounds on the heights. In the two examples, the greatest variation in height occurred around the mean diameter. The percentile lines obtained through the S BB distribution function indicate that the variation in height for a given diameter is less pronounced in the larger trees.

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.

Historical Emergence and Current Application of CCF

Although the majority of the world’s forest ecosystems are dominated by uneven-sized mixed species stands, forest management practice and theory have focused on the development of plantation monocultures to maximize the supply of timber at low cost. Societal expectations are changing, however, and uneven-aged multi-species ecosystems are often believed to be superior to monocultures in addressing a wide range of expectations. This chapter attempts to clarify terminology and define, albeit somewhat simplistically, continuous cover forestry (CCF) as opposed to rotation management (RFM). RFM is characterized by three distinct development phases: planting–thinning–clearfelling. At least two of these phases, and sometimes all three, occur simultaneously in CCF. The second section of this chapter describes the development of the European Plenter Forest system, which, being based on a sound theory of sustainable use and an extended period of practical applications, is often considered to be the “Archetype” of CCF. Prompted by a rising interest in continuous cover forestry, specific methods have been developed in many other regions. Accordingly, the third section briefly covers some approaches in China, Chile, Mexico, the United States and South Africa. The forth section introduces adaptive approaches to CCF. The ideal J-shaped target structure is an artificial construct which is easy to implement and thus useful for management. The problem is to define it. This problem is aggravated when foresters wish to (a) mimic natural structures which do not resemble inverse J-shaped diameter distributions and (b) when there is a need to respond to changing economic and environmental conditions.

Timber harvest planning with spatial objectives, using the method of simulated annealing

Summary:Consideration of the spatial distribution of timber operations is an important feature of new harvest scheduling models. Different combinations of stand treatment options exhibit quite different spatial patterns of harvesting and regeneration at a given point in time. Specific arrangements of such operations will benefit a variety of economic and conservation objectives. The present paper presents an example of how spatial arrangement and timber production objectives may be considered simultaneously, using the method of simulated annealing. After discussing the theoretical background of the spatial scheduling problem, the paper presents an example of a forest consisting of 1480 stands of different age, site index, density and area. Several treatment options are generated for each stand and timber output is calculated using a comprehensive growth model. The objective function consists of a timber component and a spatial component. It is shown that a great variety of spatial patterns can be generated by adjusting the adjacency matrix.Zusammenfassung:Die räumliche Anordnung forstlicher Massnahmen ist ein wichtiger Aspekt bei der Modellierung der Waldentwicklung. Verschiedene Kombinationen von Bestandesentwicklungspfaden ergeben, zu ganz bestimmten Zeitpunkten, unterschiedliche räumliche Muster der Nutzung und Verjüngung, die wiederum ökonomische und naturschutzfachliche Zielsetzungen auf unterschiedliche Weise erfüllen. Der vorliegende Beitrag zeigt anhand eines Beispiels wie räumliche Zielsetzungen und Nutzungsstrategien vereint werden können, unter Verwendung der Methode des simulated annealing. Nach einer kurzen theoretischen Einführung wird die Anwendung anhand eines Waldgebietes mit 1400 Beständen unterschiedlicher Flächenausdehnung, Alter, Bonitäten und Bestandesgrundflächen demonstriert. Mehrere waldbauliche Optionen werden für jeden Bestand erzeugt und die Nutzung und Fortschreibung der Bestandesparameter basiert auf einem umfassenden Wuchsmodell. Die Zielfunktion enthält eine Nutzungs- und eine räumliche Komponente. Die Untersuchung unterschiedlicher Varianten zeigt u.a. die hohe Flexibilität des Verfahrens bei der Implementierung bestimmter räumlicher Zielsetzungen.

Stem Number Guide Curves for Uneven-Aged Forests Development and Limitations

The paper presents a method for calculating an ideal diameter distribution for uneven-aged forests by means of a negative exponential distribution. The approach is practical for determining periodic harvest levels in forests where the ideal diameter structure is assumed to be known. This is demonstrated by means of examples from various parts of the world. However, the concept of an ideal diameter distribution has no biological foundation and the economic benefits of maintaining a forest in some equilibrium state, which requires a constant equable harvest rate, are doubtful. The application of the guide curve method for managing forest ecosystems can therefore be recommended only for situations where there is a lack of analytical tools required for generating and evaluating alternative treatment options.