ECOLOGICAL MODELS AND DATA IN R

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Ecological Models And Data In R

Author : Benjamin M. Bolker
ISBN : 9781400840908
Genre : Nature
File Size : 22.11 MB
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Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive experience teaching these techniques to graduate students in ecology, Benjamin Bolker shows how to choose among and construct statistical models for data, estimate their parameters and confidence limits, and interpret the results. The book also covers statistical frameworks, the philosophy of statistical modeling, and critical mathematical functions and probability distributions. It requires no programming background--only basic calculus and statistics. Practical, beginner-friendly introduction to modern statistical techniques for ecology using the programming language R Step-by-step instructions for fitting models to messy, real-world data Balanced view of different statistical approaches Wide coverage of techniques--from simple (distribution fitting) to complex (state-space modeling) Techniques for data manipulation and graphical display Companion Web site with data and R code for all examples
Category: Nature

Mixed Effects Models And Extensions In Ecology With R

Author : Alain Zuur
ISBN : 0387874585
Genre : Science
File Size : 38.84 MB
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This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. The book starts by revising regression, additive modelling, GAM and GLM, and then discusses dealing with spatial or temporal dependencies and nested data.
Category: Science

Ecological Statistics

Author : Gordon A. Fox
ISBN : 9780191652882
Genre : Science
File Size : 32.76 MB
Format : PDF, Kindle
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The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have created a new generation of statistical techniques. These have resulted in major recent developments in both our understanding and practice of ecological statistics. This novel book synthesizes a number of these changes, addressing key approaches and issues that tend to be overlooked in other books such as missing/censored data, correlation structure of data, heterogeneous data, and complex causal relationships. These issues characterize a large proportion of ecological data, but most ecologists' training in traditional statistics simply does not provide them with adequate preparation to handle the associated challenges. Uniquely, Ecological Statistics highlights the underlying links among many statistical approaches that attempt to tackle these issues. In particular, it gives readers an introduction to approaches to inference, likelihoods, generalized linear (mixed) models, spatially or phylogenetically-structured data, and data synthesis, with a strong emphasis on conceptual understanding and subsequent application to data analysis. Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology who are interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language.
Category: Science

A Practical Guide To Ecological Modelling

Author : Karline Soetaert
ISBN : 9781402086236
Genre : Science
File Size : 84.36 MB
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Mathematical modelling is an essential tool in present-day ecological research. Yet for many ecologists it is still problematic to apply modelling in their research. In our experience, the major problem is at the conceptual level: proper understanding of what a model is, how ecological relations can be translated consistently into mathematical equations, how models are solved, steady states calculated and interpreted. Many textbooks jump over these conceptual hurdles to dive into detailed formulations or the mathematics of solution. This book attempts to fill that gap. It introduces essential concepts for mathematical modelling, explains the mathematics behind the methods, and helps readers to implement models and obtain hands-on experience. Throughout the book, emphasis is laid on how to translate ecological questions into interpretable models in a practical way. The book aims to be an introductory textbook at the undergraduate-graduate level, but will also be useful to seduce experienced ecologists into the world of modelling. The range of ecological models treated is wide, from Lotka-Volterra type of principle-seeking models to environmental or ecosystem models, and including matrix models, lattice models and sequential decision models. All chapters contain a concise introduction into the theory, worked-out examples and exercises. All examples are implemented in the open-source package R, thus taking away problems of software availability for use of the book. All code used in the book is available on a dedicated website.
Category: Science

Hierarchical Modeling And Inference In Ecology

Author : J. Andrew Royle
ISBN : 9780080559254
Genre : Science
File Size : 47.38 MB
Format : PDF
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A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics * Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) * Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis * Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS * Computing support in technical appendices in an online companion web site
Category: Science

Applied Hierarchical Modeling In Ecology Analysis Of Distribution Abundance And Species Richness In R And Bugs

Author : Marc Kery
ISBN : 9780128097274
Genre : Nature
File Size : 63.65 MB
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Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS, Volume Two: Dynamic and Advanced Models provides a synthesis of the state-of-the-art in hierarchical models for plant and animal distribution, also focusing on the complex and more advanced models currently available. The book explains all procedures in the context of hierarchical models that represent a unified approach to ecological research, thus taking the reader from design, through data collection, and into analyses using a very powerful way of synthesizing data. Makes ecological modeling accessible for people who are struggling to use complex or advanced modeling programs Synthesizes current ecological models and explains how they are inter-connected Contains examples throughout the book, walking the reading through scenarios with both real and simulated data Presents an ideal resource for ecologists working in R, an open source version of S known for its exceptional ecology analyses, and in BUGS for more flexible Bayesian analyses
Category: Nature

Spatial Data Analysis In Ecology And Agriculture Using R

Author : Richard E. Plant
ISBN : 9781439819142
Genre : Mathematics
File Size : 49.46 MB
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Assuming no prior knowledge of R, Spatial Data Analysis in Ecology and Agriculture Using R provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology and agriculture. Written in terms of four data sets easily accessible online, this book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Based on the author’s spatial data analysis course at the University of California, Davis, the book is intended for classroom use or self-study by graduate students and researchers in ecology, geography, and agricultural science with an interest in the analysis of spatial data.
Category: Mathematics

Stochastic Population Dynamics In Ecology And Conservation

Author : Russell Lande
ISBN : 0198525257
Genre : Philosophy
File Size : 89.89 MB
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1. Demographic and environmental stochasticity -- 2. Extinction dynamics -- 3. Age structure -- 4. Spatial structure -- 5. Population viability analysis -- 6. Sustainable harvesting -- 7. Species diversity -- 8. Community dynamics.
Category: Philosophy

Ecological Modeling For Resource Management

Author : Virginia H. Dale
ISBN : 9780387954936
Genre : Computers
File Size : 50.15 MB
Format : PDF
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This book will serve as a readable introduction to ecological modeling for people involved in resource management and will also review models for specific applications of interest to more experienced modelers. Successful uses of ecological models as well as discussions of important issues in modeling are addressed. The authors of this volume hope to close the gap between the state of the art in ecological modeling and the state of the practice in the use of models in management decision making.
Category: Computers

Simulation Of Ecological And Environmental Models

Author : Miguel F. Acevedo
ISBN : 9781439885062
Genre : Science
File Size : 83.23 MB
Format : PDF
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Given the importance of interdisciplinary work in sustainability, Simulation of Ecological and Environmental Models introduces the theory and practice of modeling and simulation as applied in a variety of disciplines that deal with earth systems, the environment, ecology, and human–nature interactions. Based on the author’s many years of teaching graduate and undergraduate students in the United States, Spain, and Latin America, the textbook shows how to implement simulations and analyze the results using an open-source software platform. Learn How to Use a Broad Range of Environmental Models The textbook is organized into three parts to allow greater flexibility using the material in various countries and types of curricula. The first part provides a tutorial-style mathematical review and a gentle introduction to the basics of R software. The second part explains the fundamentals of modeling methodology through one-dimensional models. After a review of matrix algebra, the third part progresses to multidimensional models, focusing on structured populations, communities, and ecosystems. The final chapters show how simple models are hooked together to generate more comprehensive models. Build from Fundamental Concepts to Problem Solving Each chapter starts with conceptual and theoretical material to give a firm foundation in how the methods work. Examples and exercises illustrate the applications and demonstrate how to go from concepts to problem solving. Hands-on computer sessions let students grasp the practical implications and learn by doing. Throughout, the computer examples and exercises use seem, an open-source R package developed by the author, which lets students quickly produce simulations and explore the effects of changing conditions in the model. This practical book is a comprehensive, unified presentation of ecological and environmental models. It describes the mathematical fundamentals to analyze models and the methodology to simulate them, with a focus on understanding environmental change—a key element of environmental management and problem solving.
Category: Science