10114nam a2200733 i 45000010014000000030004000140050017000180060019000350070015000540080041000690200025001100200024001350200025001590200027001840240035002110350025002460350022002710400040002930500029003330720017003620720023003791000025004022450101004272500020005282640098005483000071006463360021007173370026007383380032007644900027007964900034008235000043008575040041009005050210009415050676011515050424018275050610022515050555028615050406034165050442038225050412042645050294046765050405049705050302053755050107056775060075057845201590058595210032074495300029074815380036075105380078075465451277076245880055089016500033089566500036089896500033090256500047090586500048091057100054091537760049092078300031092568300034092878560059093219780750361590IOP20251030124834.0m    eo  d        cr cn |||m|||a240501s2024    enka   fob    000 0 eng d  a9780750361590qebook  a9780750361583qmobi  z9780750361576qprint  z9780750361606qmyPrint7 a10.1088/978-0-7503-6159-02doi  a(CaBNVSL)thg00083933  a(OCoLC)1432612069  aCaBNVSLbengerdacCaBNVSLdCaBNVSL 4aQH541.15.S5bF674 2024eb 7aPSAF2bicssc 7aSCI0200002bisacsh1 aFort, Hugo,eauthor.1 aEcological modelling and ecophysics :bagricultural and environmental applications /cHugo Fort.  aSecond Edition. 1aBristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :bIOP Publishing,c[2024]  a1 online resource (various pagings) :billustrations (some color).  atext2rdacontent  aelectronic2isbdmedia  aonline resource2rdacarrier1 a[IOP release $release]1 aIOP ebooks. [2024 collection]  a"Version: 20240401"--Title page verso.  aIncludes bibliographical references.  a0. 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 modeling8 apart 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. Exercises8 aA1. 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?8 a2. 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. Exercises8 aA2. 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 line8 apart 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. Exercises8 aA3. 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. Conclusion8 a4. 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 comments8 aA4. 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 caveats8 a5. 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. Exercises8 aA5. 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 caveats8 aAppendix I. Equilibrium stability -- Appendix II. Fermi problems or back-of-the-envelope calculations.  aFull-text restricted to subscribers or individual document purchasers.3 aThe 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.  aProfessional and scholarly.  aAlso available in print.  aMode of access: World Wide Web.  aSystem requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.  aHugo 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.  aTitle from PDF title page (viewed on May 1, 2024).  aEcologyxSimulation methods.  aBiophysicsxSimulation methods.  aPhysicsxSimulation methods. 7aEcological science, the Biosphere.2bicssc 7aSCIENCE / Life Sciences / Ecology.2bisacsh2 aInstitute of Physics (Great Britain),epublisher. 8iPrint version:z9780750361576z9780750361606 0aIOP (Series).pRelease 24.  aIOP ebooks.p2024 collection.4 uhttps://iopscience.iop.org/book/mono/978-0-7503-6159-0