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An ecologically based model of forest succession is presented. In the model, trees compete for a share of limited growth resources available from their environment. Competition is reflected by each tree's effect on the resource pool and is not explicitly modeled. Model parameters were fit to field data from subalpine forests of the Rocky Mountains. A technique for estimating model parameters from understory-tolerance rankings and silvical characteristics of each species is also presented. The model's output was consistent with our current understanding of forest dynamics. Emergent properties of the model also mimicked natural processes such as self-thinning, release, and maximum stand basal area as a function of species present and site quality.
The aim of this book is to improve the understanding of forest dynamics and the sustainable management of forest ecosystems. How do tree crowns, trees or entire forest stands respond to thinning in the long term? What effect do tree species mixtures and multi-layering have on the productivity and stability of trees, stands or forest enterprises? How do tree and stand growth respond to stress factors such as climate change or air pollution? Furthermore, in the event that one has acquired knowledge about the effects of thinning, mixture and stress, how can one make that knowledge applicable to decision-making in forestry practice? The experimental designs, analytical methods, general relationships and models for answering questions of this kind are the focus of this book. Given the structures dealt with, which range from plant organs to the tree, stand and enterprise levels, and the processes analysed in a time frame of days or months to decades or even centuries, this book is directed at all readers interested in trees, forest stands and forest ecosystems. This work has been compiled for students, scientists, lecturers, forest planners, forest managers, and consultants.
The book is designed to be a textbook for university students (MSc-PhD level) and a reference for researchers and practitioners. It is an introduction to dynamic modelling of forest growth based on ecological theory but aiming for practical applications for forest management under environmental change. It is largely based on the work and research findings of the authors, but it also covers a wide range of literature relevant to process-based forest modelling in general. The models presented in the book also serve as tools for research and can be elaborated further as new research findings emerge. The material in the book is arranged such that the student starts from basic concepts and formulations, then moves towards more advanced theories and methods, finally learning about parameter estimation, model testing, and practical application. Exercises with solutions and hands-on R-code are provided to help the student digest the concepts and become proficient with the methods. The book should be useful for both forest ecologists who want to become modellers, and for applied mathematicians who want to learn about forest ecology. The basic concepts and theory are formulated in the first four chapters, including a review of traditional descriptive forest models, basic concepts of carbon balance modelling applied to trees, and theories and models of tree and forest structure. Chapter 5 provides a synthesis in the form of a core model which is further elaborated and applied in the subsequent chapters. The more advanced theories and methods in Chapters 6 and 7 comprise aspects of competition through tree interactions, and eco-evolutionary modelling, including optimisation and game theory, a topical and fast developing area of ecological modelling under climate change. Chapters 8 and 9 are devoted to parameter estimation and model calibration, showing how empirical and process-based methods and related data sources can be bridged to provide reliable predictions. Chapter 10 demonstrates some practical applications and possible future development paths of the approach. The approach in this book is unique in that the models presented are based on ecological theory and research findings, yet sufficiently simple in structure to lend themselves readily to practical application, such as regional estimates of harvest potential, or satellite-based monitoring of growth. The applicability is also related to the objective of bridging empirical and process-based approaches through data assimilation methods that combine research-based ecological measurements with standard forestry data. Importantly, the ecological basis means that it is possible to build on the existing models to advance the approach as new research findings become available.
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 study modelled the risk of fire at the stand and forest level to aid management decisions on the effect of such occurrences on annual allowable cut and future timber supplies; determined the frequency of large-scale insect and disease occurrences, and derived a model to assess their impact on the present and future forest yields; and tested, reviewed, and modified the fire, insect and disease, and other risk factor models for application over boreal forest ecoregions in western Canada. The program involved probabilistic (a preliminary version of the FOrestry RIsk Model (FORIM) based on Hinton leasehold and East Slopes fire risk data), deterministic (FORMAN model selected, modified, and tested for impacts in the Footner Lake and the Peace River volume sampling regions in northern Alberta), and dynamic (Markov decision support model applied to optimal forest management strategies for the Peace River and Footner Lake forests in northwestern Alberta) modelling approaches to give a comparative assessment of their merits.
Modelling is an important tool for understanding the complexity of forest ecosystems and the variety of interactions of ecosystem components, processes and values. This book describes the hybrid approach to modelling forest ecosystems and their possible response to natural and management-induced disturbance. The book describes the FORECAST family of ecosystem management models at three different spatial scales (tree, stand and landscape), and compares them with alternative models at these three spatial scales. The book will help forest managers to understand what to expect from ecosystem-based forest models; serve as a tool for use in teaching about sustainability, scenario analysis and value trade-offs in natural resources management; and assist policy makers, managers and researches working in assessment of sustainable forest management and ecosystem management. Several real-life examples of using the FORECAST family of models in forest management and other applications are presented from countries including Canada, China, Spain and the USA, to illustrate the concepts described in the text. The book also demonstrates how these models can be extended for scenario and value trade-off analysis through visualization and educational or management games.
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
Decision Methods for Forest Resource Management focuses on decision making for forests that are managed for both ecological and economic objectives. The essential modern decision methods used in the scientific management of forests are described using basic algebra, computer spreadsheets, and numerous examples and applications. Balanced treatment is given throughout the book to the ecological and economic impacts of alternative management decisions in both even-aged and uneven-aged forests. In-depth coverage of both ecological and economic issues Hands-on examples with Excel spreadsheets; electronic versions available on the authors' website Many related exercises with solutions Instructor's Manual available upon request
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.