Ecological modelling and ecophysics : agricultural and environmental applications / Hugo Fort.

Format:

Book

Author/Creator:

Fort, Hugo, author.

Contributor:

Institute of Physics (Great Britain), publisher.

Series:

IOP (Series). Release 24.

IOP ebooks. 2024 collection.

[IOP release $release]

IOP ebooks. [2024 collection]

Language:

English

Subjects (All):

Ecology--Simulation methods.

Ecology.

Biophysics--Simulation methods.

Biophysics.

Physics--Simulation methods.

Physics.

Physical Description:

1 online resource (various pagings) : illustrations (some color).

Edition:

Second Edition.

Place of Publication:

Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2024]

System Details:

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.

Biography/History:

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 agro-economy to environmental and real-time evolution. Fort is currently involved in several international research collaborations pursuing used-inspired basic science. A central aim is to connect ecological and evolutionary problems with well-studied 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.

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.

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 Lotka-Volterra 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 Lotka-Volterra predator-prey equations

1.5. The Lotka-Volterra competition equations for a pair of species

1.6. The Lotka-Volterra equations for two mutualist species

1.7. Worked example : Niche overlap and traits of nectar-producing plant species and nectar searching animal species

1.8. Exercises

A1. Extensive livestock farming : a quantitative management model in terms of a predator-prey dynamical system

A1.1. Background information : the growing demand for quantitative livestock models

A1.2. A predator-prey 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. Lotka-Volterra models for multispecies communities and their usefulness as quantitative predicting tools

2.1. Summary

2.2. Many interacting species : the Lotka-Volterra generalized linear model

2.3. The Lotka-Volterra 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 Lotka-Volterra 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 liquid-vapor 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 non-equilibrium statistical mechanics

5.1. Summary

5.2. Quasi-equilibrium 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 back-of-the-envelope calculations.

Notes:

"Version: 20240401"--Title page verso.

Includes bibliographical references.

Title from PDF title page (viewed on May 1, 2024).

Other Format:

Print version:

ISBN:

9780750361590

9780750361583

OCLC:

1432612069

Access Restriction:

Restricted for use by site license.