Modelling Forest DevelopmentSpringer Science & Business Media, 30 nov 2001 - 213 pagine In an lUlffianaged woodland, forest development follows a succession of periods of undisturbed natural growth, interrupted by intermediate loss or damage of trees caused by fire or wind or other natural hazards. In a managed woodland, the most important periodic disturbances are the thinning operations, which are often carried out at regular intervals and which usually have a significant effect on the future evolution of the resource. Thus, a realistic model of forest development includes both natural growth and thinnings. The key to successful timber management is a proper understanding of growth processes, and one of the objectives of modelling forest development is to provide the tools that enable foresters to compare alternative silvicultural treatments. Foresters need to be able to anticipate the consequences of a particular thinning operation. In most cases, total timber volume is not a very appropriate measure for quantifying growth or yields, or changes caused by thinning operations. Yield in economic terms is defined by the dimensions and quality attributes of the harvestable logs, and estimating timber products is a central issue of production-oriented growth and yield research. Introduction 2 Growth modelling is also an essential prerequisite for evaluating the consequences of a particular management action on the future development of an important natural resource, such as a woodland ecosystem. |
Sommario
Introduction | |
Types of forest models | 1 |
Data requirements | 4 |
Permanent plots | 7 |
Temporary plots | 9 |
Interval plots | 10 |
Projecting regional timber resources | 13 |
Empirical yield functions | 14 |
Bivariate DiameterHeight Distributions | 84 |
Estimating Product Yields | 90 |
Volume Ratio Methods | 91 |
Form Quotients Splines and Polynomials | 92 |
Parameterparsimonious Stem Profile Functions | 94 |
Generalized Stem Profile Functions | 98 |
Stem Quality Assessment and Prediction | 101 |
Modelling Thinnings | 107 |
Fully stocked forests | 15 |
Nonfully Stocked Forests | 19 |
Yield Functions based on MAI Estimates | 21 |
Modelling stand development | 24 |
Anamorphic height models | 26 |
Disjoint Polymorphic Height Models | 29 |
Nondisjoint Polymorphic Height Models | 34 |
Basal area | 37 |
Potential Density | 40 |
The Limiting Line | 41 |
Estimating potential density | 42 |
Natural decline of stem number | 44 |
State space models | 45 |
Stand Volume and Product Yields | 48 |
Thinning Models | 51 |
Classical Description of Thinning Operations | 52 |
Thinning Weight | 55 |
Type of Thinning | 57 |
Sizeclass Models | 59 |
Diameter Growth | 60 |
Projecting Diameter Distributions | 61 |
Stand Table Projection | 65 |
Diameter Growth as a Function of Diameter | 66 |
Growth Modifiers | 68 |
Change of Relative Basal Area | 73 |
A Worked Example | 75 |
Transition Matrices | 77 |
DiameterHeight Relations | 81 |
Movement of the Diameter Distribution after Thinning | 112 |
Separation Parameters | 114 |
Modelling Foresters TreeSelection Behavior | 119 |
Individual Tree Growth | 127 |
Generating Spatial Structures | 128 |
Variables for Describing Spatial Structure | 129 |
Size Differentiation | 130 |
Species Segregation and Mingling | 131 |
Aggregation | 135 |
Using Structural Variables to Generate Positions with Attributes | 138 |
Competition Indices | 141 |
Overlapping Influence Zones | 143 |
Distanceweighted Size Ratios | 146 |
Available Growing Space | 149 |
Shading and Constriction | 151 |
Spatial Growth Models | 157 |
FOREST WASIM and MOSES | 158 |
SILVA | 163 |
Spatial Thinning Models | 166 |
Prescription | 173 |
Model evaluation | 179 |
Quantitative Evaluations | 183 |
Statistical Tests | 187 |
Symbols used | 189 |
Literature | 193 |
Index | 203 |
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Parole e frasi comuni
a₁ Acacia mangium Acacia tortilis attributes average basal area basal area growth Beech beech forest breast height diameter buttlog calculated cell competition index crown radius Cunninghamia lanceolata curves defined describing diameter class diameter cm diameter distribution diameter growth diameter-height dominant height dominant stand height Equation estimated evaluating example Fagus sylvatica Figure forest forest development frequencies Gadow growth models height growth high thinning increment individual tree influence zone ISBN Jiangxi low thinning m³/ha mean annual increment measure method nearest neighbors neighboring trees number of trees observed obtained parameter values Picea abies Pinus Pinus radiata Pinus sylvestris plantations polymorphic potential predicted Pretzsch quadratic mean diameter ratio reference tree relative removed root mean square Scots pine shading silvicultural simulated size-class spatial species Spruce stand age stem profile structure subject tree t₂ thinning operation tree diameter tree growth tree height tree positions variables yield table Z-tree