by Arne Pommerening (Author), Pavel Grabarnik (Author)
Model-driven individual-based forest ecology and individual-based methods in forest management are of increasing importance in many parts of the world. For the first time this book integrates three main fields of forest ecology and management, i.e. tree/plant interactions, biometry of plant growth and human behaviour in forests. Individual-based forest ecology and management is an interdisciplinary research field with a focus on how the individual behaviour of plants contributes to the formation of spatial patterns that evolve through time. Key to this research is a strict bottom-up approach where the shaping and characteristics of plant communities are mostly the result of interactions between plants and between plants and humans. This book unites important methods of individual-based forest ecology and management from point process statistics, individual-based modelling, plant growth science and behavioural statistics. For ease of access, better understanding and transparency the methods are accompanied by R code and worked examples.
Back Jacket
Model-driven individual-based forest ecology has emerged in the 1990s and has given rise to a wealth of publications. At the same time, individual-based methods in forest management have been refined in a number of different countries and steadily grow in importance. For the first time this book integrates three main fields of forest ecology and management, i.e. tree/plant interactions, biometry of plant growth and human behaviour in forests. Individual-based forest ecology and management is an interdisciplinary research field with a focus on how the individual behaviour of plants contributes to the formation of spatial patterns that evolve through time. Key to this research is a strict bottom-up approach where the shaping and characteristics of plant communities are understood to be mostly the result of interactions between plants and between plants and humans. Written in a highly accessible style, the book provides essential information on theories and concepts of individual-based forest ecology and management and introduces point process statistics for analysing plant interactions. This is followed by methods of spatial modelling with a focus on individual-based models. The text is complemented by key concepts of modern plant growth science. Finally new methods of measuring, analysing and modelling human interaction with trees in forest ecosystems are introduced and discussed. For better access and understanding, all methods introduced in this book are accompanied by example code ready to use in the statistical software R and by worked examples. Additional technical details are given in three appendices.
Author Biography
Arne Pommerening works as Professor in Mathematical Statistics Applied to Forest Sciences at the Swedish University of Agricultural Sciences (SLU) in Umeå. He is a theoretical forest scientist and biometrician specialised in quantitative forest ecology and management. Arne Pommerening is particularly known for his research in woodland structure analysis and modelling, spatio-temporal dynamics of plant point patterns, individual-based modelling, plant growth analysis and methods for quantifying and monitoring biodiversity. More recently he has also developed an interest in the analysis of human behaviour in selecting trees. Much of his research involves combinations of field trials and computer-based simulation experiments.
Pavel Grabarnik is a Professor of Mathematical Modelling in Ecology at Pushchino University in Russia. Currently he serves as the Director of the Pushchino Scientific Centre of Biological Research of the Russian Academy of Sciences and heads the Laboratory of Ecosystems Modelling. His research work includes ecological modelling focussed on the spatial structure of forest ecosystems. His main achievements in statistics are in parameter estimation and hypothesis testing for spatial point processes. Pavel Grabarnik has also developed computational tools for different aspects of applications in spatial statistics.