Ecological modelling and ecophysics : agricultural and environmental applications
 Responsibility
 Hugo Fort.
 Edition
 Second Edition.
 Publication
 Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2024]
 Physical description
 1 online resource (various pagings) : illustrations (some color).
Online
More options
Description
Creators/Contributors
 Author/Creator
 Fort, Hugo, author.
 Contributor
 Institute of Physics (Great Britain), publisher.
Contents/Summary
 Bibliography
 Includes bibliographical references.
 Contents

 0. Introduction
 0.1. The goal of ecology : understanding the distribution and abundance of organisms from their interactions
 0.2. Mathematical models
 0.3. Community and population ecology modeling
 part I. Classical population and community ecology. 1. From growth equations for a single species to LotkaVolterra equations for two interacting species
 1.1. Summary
 1.2. From the Malthus to the logistic equation of growth for a single species
 1.3. General models for single species populations and analysis of local equilibrium stability
 1.4. The LotkaVolterra predatorprey equations
 1.5. The LotkaVolterra competition equations for a pair of species
 1.6. The LotkaVolterra equations for two mutualist species
 1.7. Worked example : Niche overlap and traits of nectarproducing plant species and nectar searching animal species
 1.8. Exercises
 A1. Extensive livestock farming : a quantitative management model in terms of a predatorprey dynamical system
 A1.1. Background information : the growing demand for quantitative livestock models
 A1.2. A predatorprey model for grassland livestock or PPGL
 A1.3. Model validation
 A1.4. Uses of PPGL by farmers : estimating gross margins in different productive scenarios
 A1.5. How can we improve our model?
 2. LotkaVolterra models for multispecies communities and their usefulness as quantitative predicting tools
 2.1. Summary
 2.2. Many interacting species : the LotkaVolterra generalized linear model
 2.3. The LotkaVolterra linear model for single trophic communities
 2.4. Food webs and trophic chains
 2.5. Quantifying the accuracy of the linear model for predicting species yields in single trophic communities
 2.6. Working with imperfect information
 2.7. Beyond equilibrium : testing the generalized linear model for predicting species trajectories
 2.8. Conclusion
 2.9. Exercises
 A2. Predicting optimal mixtures of perennial crops by combining modelling and experiments
 A2.1. Background information
 A2.2. Overview
 A2.3. Experimental design and data
 A2.4. Modelling
 A2.5. Metrics for overyielding and equitability
 A2.6. Model validation : theoretical versus experimental quantities
 A2.7. Predictions : results from simulation of not sown treatments
 A2.8. Using the model attempting to elucidate the relationship between yield and diversity
 A2.9. Possible extensions and some caveats
 A2.10. Bottom line
 part II. Ecophysics : methods from physics applied to ecology. 3. The maximum entropy method and the statistical mechanics of populations
 3.1. Summary
 3.2. Basics of statistical physics
 3.3. MaxEnt in terms of Shannon's information theory as a general inference approach
 3.4. The statistical mechanics of populations
 3.5. Neutral theories of ecology
 3.6. Conclusion
 3.7. Exercises
 A3. Combining the generalized LotkaVolterra model and MaxEnt method to predict changes of tree species composition in tropical forests
 A3.1. Background information
 A3.2. Overview
 A3.3. Data for Barro Colorado Island (BCI) 50 ha tropical Forest Dynamics Plot
 A3.4. Modeling
 A3.5. Model validation using time series forecasting analysis
 A3.6. Predictions
 A3.7. Extensions, improvements and caveats
 A3.8. Conclusion
 4. Catastrophic shifts in ecology, early warnings and the phenomenology of phase transitions
 4.1. Summary
 4.2. Catastrophes
 4.3. When does a catastrophic shift take place? Maxwell versus delay conventions
 4.4. Early warnings of catastrophic shifts
 4.5. Beyond the mean field approximation
 4.6. A comparison with the phenomenology of the liquidvapor phase transition
 4.7. Final comments
 A4. Modelling eutrophication, early warnings and remedial actions in a lake
 A4.1. Background information
 A4.2. Overview
 A4.3. Data for Lake Mendota
 A4.4. Modelling
 A4.5. Model validation
 A4.6. Usefulness of the early warnings
 A4.7. Extensions, improvements and caveats
 5. Stochastic processes in ecology and nonequilibrium statistical mechanics
 5.1. Summary
 5.2. Quasiequilibrium states, far from equilibrium states and the evolution toward equilibrium
 5.3. Random walk
 5.4. Markov chains
 5.5. Markovian simulation algorithms inspired in statistical physics
 5.6. Monte Carlo algorithms as an optimization tool : simulated annealing
 5.7. Exercises
 A5. Forecasting changes in land use/land cover (LULC)
 A5.1. Background information
 A5.2. Overview
 A5.3. Data for LULC in two regions of Uruguay
 A5.4. Modeling
 A5.5. Model validation
 A5.6. Usefulness of forecasting future LULC changes
 A5.7. Extensions, improvements and caveats
 Appendix I. Equilibrium stability
 Appendix II. Fermi problems or backoftheenvelope calculations.
 Summary
 The book aims to bridge the gap between conventional ecological modelling and 'ecophysics', a neologism that stands for approaching ecological and environmental problems using ideas and techniques from physics. Such an approach to the involved complex systems has demonstrated its usefulness to enhance our understanding of intrinsically interdisciplinary problems and inform sustainable practices in agriculture, conservation and environmental management. The motivation behind this book is twofold: to enhance comprehension and to bolster our capacity to tackle practical challenges using rigorous quantitative methods. This is why the structure of the book is designed such that each chapter dedicated to methods in community/population ecology is accompanied by an Application chapter, which presents the practical implementation of the discussed methods. A main objective of these latter chapters is to actively involve readers interested in devising tools and strategies to address their own issues. Among the Applications provided, the first two focus on optimizing agricultural production, specifically livestock production and polyculture crops. The other Applications centre around environmental concerns, including the dynamics of tree species in tropical forests, the identification of early warning signals for catastrophic shifts in lakes and the dynamics of land use/land cover (LULC), i.e. the categorization or classification of human activities and natural elements on the landscape. What unites these diverse problems is their reliance on population dynamics models.
Subjects
Bibliographic information
 Publication date
 2024
 Note
 "Version: 20240401"Title page verso.
 Access
 Fulltext restricted to subscribers or individual document purchasers.
 Audience
 Professional and scholarly.
 Note
 Also available in print.
 Format
 Mode of access: World Wide Web.
 System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
 Note
 Hugo Fort is a Professor at the Physics Department of the Faculty of Sciences of the Republic University (Montevideo, Uruguay) and Head of the Complex System Group. After earning his PhD in physics from the Autonomous University of Barcelona in 1994, he conducted research on quantum field theory. Since 2001, his scientific interests evolved from theoretical physics to complex systems and mathematical modelling applied to problems in biology, with a focus in ecology and evolution. A main goal of his research is to develop quantitative methods and tools for a wide variety of practical problems in fields ranging from agroeconomy to environmental and realtime evolution. Fort is currently involved in several international research collaborations pursuing usedinspired basic science. A central aim is to connect ecological and evolutionary problems with wellstudied phenomena in physics to gain deeper insight into these problems, to identify novel questions and problems, and to get access to alternative powerful computational tools. Professor Fort has previously published two books with IOP, the first edition of Ecological Modelling and Ecophysics and Forecasting with Maximum Entropy: The Interface Between Physics, Biology, Economics and Information Theory.
 ISBN
 9780750361590 ebook
 9780750361583 mobi
 9780750361576 print
 9780750361606 myPrint
 DOI
 10.1088/9780750361590