Modeling Populations Of Adaptive Individuals
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| Author | : Steven F. Railsback |
| Publisher | : Princeton University Press |
| Total Pages | : 195 |
| Release | : 2020-05-19 |
| Genre | : Science |
| ISBN | : 0691195374 |
Ecologists now recognize that the dynamics of populations, communities, and ecosystems are strongly affected by adaptive individual behaviors. Yet until now, we have lacked effective and flexible methods for modeling such dynamics. Traditional ecological models become impractical with the inclusion of behavior, and the optimization approaches of behavioral ecology cannot be used when future conditions are unpredictable due to feedbacks from the behavior of other individuals. This book provides a comprehensive introduction to state- and prediction-based theory, or SPT, a powerful new approach to modeling trade-off behaviors in contexts such as individual-based population models where feedbacks and variability make optimization impossible. Modeling Populations of Adaptive Individuals features a wealth of examples that range from highly simplified behavior models to complex population models in which individuals make adaptive trade-off decisions about habitat and activity selection in highly heterogeneous environments. Steven Railsback and Bret Harvey explain how SPT builds on key concepts from the state-based dynamic modeling theory of behavioral ecology, and how it combines explicit predictions of future conditions with approximations of a fitness measure to represent how individuals make good—not optimal—decisions that they revise as conditions change. The resulting models are realistic, testable, adaptable, and invaluable for answering fundamental questions in ecology and forecasting ecological outcomes of real-world scenarios.
| Author | : Richard K. Belew |
| Publisher | : Routledge |
| Total Pages | : 552 |
| Release | : 2018-05-04 |
| Genre | : Social Science |
| ISBN | : 0429971451 |
This book is out of a workshop organized to address questions like these. The meeting was sponsored by the Santa Fe Institute and held at Sol y Sam- bra in Santa Fe, New Mexico, during July, 1993. It brought together a group of about 20 scientists from the disciplines of biology, psychology, and computer science, all studying interactions between the evolution of populations and individuals’ adaptations in those populations, and all of whom make some use of computational tools in their work.
| Author | : Steven F. Railsback |
| Publisher | : Princeton University Press |
| Total Pages | : 195 |
| Release | : 2020-05-19 |
| Genre | : Science |
| ISBN | : 0691180490 |
"This book offers a new theory for modeling how organisms make tradeoff decisions and how these decisions affect both individuals and populations. Tradeoff decisions (or behaviors) are those that are optimize survival and include behaviors like foraging and reproduction. Existing theories have not painted a complete picture of tradeoff decisions because they only observe how the decisions of an individual affect them rather than how individuals impact, and are impacted by, the behavior of their communities. The authors' theory-which they call state and prediction based theory-uses individual-based models since these models show the complex ways that organisms relate to their environment. The authors' broader approach, one that integrates behavior and population dynamics, allows ecologists to see how individuals make adaptive tradeoff decisions. In simpler terms, this theory does not assume, as the previous models do, that future conditions are fixed, known, and unaffected by the behavior of others. Instead, the authors assume individuals make decisions like people do, which is by forecasting future conditions, using approximation to make good decisions, and updating their choices as conditions change"--
| Author | : Richard K. Belew |
| Publisher | : Westview Press |
| Total Pages | : 550 |
| Release | : 1996-05-22 |
| Genre | : Science |
| ISBN | : 9780201483697 |
The theory of evolution has been most successful explaining the emergence of new species in terms of their morphological traits. Ethologists teach that behaviors, too, qualify as first-class phenotypic features, but evolutionary accounts of behaviors have been much less satisfactory. In part this is because maturational ”programs” transforming genotype to phenotype are ”open” to environmental influences affected by behaviors. Further, many organisms are able to continue to modify their behavior, i.e., learn, even after fully mature. This creates an even more complex relationship between the genotypic features underlying the mechanisms of maturation and learning and the adapted behaviors ultimately selected.A meeting held at the Santa Fe Institute during the summer of 1993 brought together a small group of biologists, psychologists, and computer scientists with shared interests in questions such as these. This volume consists of papers that explore interacting adaptive systems from a range of interdisciplinary perspectives. About half of the articles are classic, seminal references on the subject, ranging from biologists like Lamarck and Waddington to psychologists like Piaget and Skinner. The other half represent new work by the workshop participants. The role played by mathematical and computational tools, both as models of natural phenomena and as algorithms useful in their own right, is particularly emphasized in these new papers. In all cases, the prefaces help to put the older papers in a modern context. For the new papers, the prefaces have been written by colleagues from a discipline other than the paper's authors, and highlight, for example, what a computer scientist can learn from a biologist's model, or vice versa. Through these cross-disciplinary ”dialogues” and a glossary collecting multidisciplinary connotations of pivotal terms, the process of interdisciplinary investigation itself becomes a central theme.
| Author | : Volker Grimm |
| Publisher | : Princeton University Press |
| Total Pages | : 445 |
| Release | : 2013-11-28 |
| Genre | : Science |
| ISBN | : 1400850622 |
Individual-based models are an exciting and widely used new tool for ecology. These computational models allow scientists to explore the mechanisms through which population and ecosystem ecology arises from how individuals interact with each other and their environment. This book provides the first in-depth treatment of individual-based modeling and its use to develop theoretical understanding of how ecological systems work, an approach the authors call "individual-based ecology.? Grimm and Railsback start with a general primer on modeling: how to design models that are as simple as possible while still allowing specific problems to be solved, and how to move efficiently through a cycle of pattern-oriented model design, implementation, and analysis. Next, they address the problems of theory and conceptual framework for individual-based ecology: What is "theory"? That is, how do we develop reusable models of how system dynamics arise from characteristics of individuals? What conceptual framework do we use when the classical differential equation framework no longer applies? An extensive review illustrates the ecological problems that have been addressed with individual-based models. The authors then identify how the mechanics of building and using individual-based models differ from those of traditional science, and provide guidance on formulating, programming, and analyzing models. This book will be helpful to ecologists interested in modeling, and to other scientists interested in agent-based modeling.
| Author | : Michael Doebeli |
| Publisher | : Princeton University Press |
| Total Pages | : 345 |
| Release | : 2011-08-21 |
| Genre | : Science |
| ISBN | : 0691128944 |
"Adaptive biological diversification occurs when frequency-dependent selection generates advantages for rare phenotypes and induces a split of an ancestral lineage into multiple descendant lineages. Using adaptive dynamics theory, individual-based simulations, and partial differential equation models, this book illustrates that adaptive diversification due to frequency-dependent ecological interaction is a theoretically ubiquitous phenomenon"--Provided by publisher.
| Author | : Michael Schaub |
| Publisher | : Academic Press |
| Total Pages | : 640 |
| Release | : 2021-11-12 |
| Genre | : Science |
| ISBN | : 0128209151 |
Integrated Population Models: Theory and Ecological Applications with R and JAGS is the first book on integrated population models, which constitute a powerful framework for combining multiple data sets from the population and the individual levels to estimate demographic parameters, and population size and trends. These models identify drivers of population dynamics and forecast the composition and trajectory of a population. Written by two population ecologists with expertise on integrated population modeling, this book provides a comprehensive synthesis of the relevant theory of integrated population models with an extensive overview of practical applications, using Bayesian methods by means of case studies. The book contains fully-documented, complete code for fitting all models in the free software, R and JAGS. It also includes all required code for pre- and post-model-fitting analysis. Integrated Population Models is an invaluable reference for researchers and practitioners involved in population analysis, and for graduate-level students in ecology, conservation biology, wildlife management, and related fields. The text is ideal for self-study and advanced graduate-level courses. Offers practical and accessible ecological applications of IPMs (integrated population models) Provides full documentation of analyzed code in the Bayesian framework Written and structured for an easy approach to the subject, especially for non-statisticians
| Author | : National Academies of Sciences, Engineering, and Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 147 |
| Release | : 2017-05-04 |
| Genre | : Science |
| ISBN | : 0309440513 |
Marine mammals face a large array of stressors, including loss of habitat, chemical and noise pollution, and bycatch in fishing, which alone kills hundreds of thousands of marine mammals per year globally. To discern the factors contributing to population trends, scientists must consider the full complement of threats faced by marine mammals. Once populations or ecosystems are found to be at risk of adverse impacts, it is critical to decide which combination of stressors to reduce to bring the population or ecosystem into a more favorable state. Assessing all stressors facing a marine mammal population also provides the environmental context for evaluating whether an additional activity could threaten it. Approaches to Understanding the Cumulative Effects of Stressors on Marine Mammals builds upon previous reports to assess current methodologies used for evaluating cumulative effects and identify new approaches that could improve these assessments. This review focuses on ways to quantify exposure-related changes in the behavior, health, or body condition of individual marine mammals and makes recommendations for future research initiatives.
| Author | : Mingtao Xia |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2023 |
| Genre | : |
| ISBN | : |
Structured population models are fundamental in the fields of biology, ecology, and social sciences, as they provide both theoretical insights and practical applications. Different structured population models range from modeling cellular population proliferation and population dynamics to simulating disease spread on social networks. However, there has been little work on modeling populations across different scales that could link individual behavior to population dynamics. Additionally, for existing mathematical models on structured populations, several computational challenges arise as how to develop efficient numerical solvers to simulate those models and to control the dynamics of those models. Overall, my dissertation covers three related topics: modeling structured populations, developing efficient numerical solvers to simulate these models, and developing control algorithms to control population dynamics. Specifically, my dissertation focuses on modeling and devising algorithms for two types of structured populations: i) age, size, or added size-structured cell population for describing cellular proliferation and ii) the structured infected-time- or number-of-contact-based human population for describing disease spread. Regarding the structured cellular population, we derive mathematical models at both the macroscopic population dynamics level and microscopic individual behavior level, leading to structured partial differential equation (PDE) models for cellular proliferation with different structure variables such as cellular age, size, or added size. Next, we develop an efficient adaptive spectral method for numerically solving spatiotemporal PDEs, which was inspired by simulating the blowup behavior in the unbounded-domain PDE model for cellular populations. In addition to the structured population models, the adaptive spectral method proves efficient and accurate in solving a wide range of spatiotemporal PDEs in unbounded domains such as the Schr dinger equations in quantum mechanics. Regarding the structured human population, we introduce an infected-time-structured PDE model and a number-of-contact-structured ODE model for simulating disease spread, e.g., COVID-19, in the population. Then, for the number-of-contact-structured ODE model, we develop classic Pontryagin-maximum-principle-based and reinforcement-learning-based optimal control algorithms. These two algorithms can effectively mitigate the spread of disease by appropriately allocating limited test kits or vaccination resources.
| Author | : John C. Moore |
| Publisher | : Cambridge University Press |
| Total Pages | : 445 |
| Release | : 2018 |
| Genre | : Business & Economics |
| ISBN | : 1107182115 |
This book presents new approaches to studying food webs, using practical and policy examples to demonstrate the theory behind ecosystem management decisions.
