Modelling Forest Development

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.

There are many theoretical approaches to modelling forest systems, but not all of them have valid practical applications. This book reviews current thinking on various models and presents applications in various contexts. Papers have been selected and developed from those presented at aworkshop held in Portugal in June 2002. Topics covered include: Forest reality and modelling strategies Mathematical approaches and reasoning Estimation processes Models, validation and decision under uncertainty Model archives and metadata

Forest Growth and Yield Modeling synthesizes current scientific literature and provides insights in how models are constructed. Giving suggestions for future developments, and outlining keys for successful implementation of models the book provides a thorough and up-to-date, single source reference for students, researchers and practitioners requiring a current digest of research and methods in the field. The book describes current modelling approaches for predicting forest growth and yield and explores the components that comprise the various modelling approaches. It provides the reader with the tools for evaluating and calibrating growth and yield models and outlines the steps necessary for developing a forest growth and yield model. Single source reference providing an evaluation and synthesis of current scientific literature Detailed descriptions of example models Covers statistical techniques used in forest model construction Accessible, reader-friendly style

Drawing upon a wealth of past research and results, this book provides a comprehensive summary of state-of-the-art methods for empirical modeling of forest trees and stands. It opens by describing methods for quantifying individual trees, progresses to a thorough coverage of whole-stand, size-class and individual-tree approaches for modeling forest stand dynamics, growth and yield, moves on to methods for incorporating response to silvicultural treatments and wood quality characteristics in forest growth and yield models, and concludes with a discussion on evaluating and implementing growth and yield models. Ideal for use in graduate-level forestry courses, this book also provides ready access to a plethora of reference material for researchers working in growth and yield modeling.

This book provides an introduction to growth modeling in mixed forests, with emphasis on the tropics. It is not intended as a 'how-to' manual with step-by-step instructions, as there is no single best way to model such forests. Rather it reviews different approaches, highlighting their strengths and limitations. It emphasizes empirical-statistical models rather than physiological-process type models, because of the proven utility of the former in forest management. Each chapter includes exercises that can be completed manually or on PC and spreadsheet. The book will serve as a reference manual for practitioners and as a text for advanced level students taking courses in forest modeling.

Whole stand models. Size class models. Single-tree and tree list models. Data Requirements. Constructing growth models. Forest site evaluation. Diameter increment. Mortality and merchantability. Regeneration and recruitment. Model evaluation and re-calibration. Implementation and use. Future directions.

This book demonstrates the measurement, monitoring, mapping, and modeling of forest resources. It explores state-of-the-art techniques based on open-source software & R statistical programming and modeling specifically, with a focus on the recent trends in data mining/machine learning techniques and robust modeling in forest resources. Discusses major topics such as forest health assessment, estimating forest biomass & carbon stock, land use forest cover (LUFC), dynamic vegetation modeling (DVM) approaches, forest-based rural livelihood, habitat suitability analysis, biodiversity and ecology, and biodiversity, the book presents novel advances and applications of RS-GIS and R in a precise and clear manner. By offering insights into various concepts and their importance for real-world applications, it equips researchers, professionals, and policy-makers with the knowledge and skills to tackle a wide range of issues related to geographic data, including those with scientific, societal, and environmental implications.