[PDF] Models Of The Ecological Hierarchy eBook

Author :
Publisher : Newnes
Page : 595 pages
File Size : 49,37 MB
Release : 2012-12-31
Category : Science
ISBN : 0444594051

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In the application of statistics to ecological inference problems, hierarchical models combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are applied in this book to a wide range of problems ranging from the molecular level, through populations, ecosystems, landscapes, networks, through to the global ecosphere. Provides an excellent introduction to modelling Collects together in one source a wide range of modelling techniques Covers a wide range of topics, from the molecular level to the global ecosphere

Author : J. Andrew Royle
Publisher : Elsevier
Page : 463 pages
File Size : 45,20 MB
Release : 2008-10-15
Category : Science
ISBN : 0080559255

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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

Author : Ferenc Jordan
Publisher : Newnes
Page : 596 pages
File Size : 30,97 MB
Release : 2012-11-29
Category : Science
ISBN : 0444593969

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"Based on selected papers covering the presentations at the 7th European Conference on Ecological Modelling, organized by ISEM and hosted by The Microsoft Research--University of Trento Center for Computational and Systems Biology from 30 May to 2 June, 2011 in Riva del Garde, Italy"--P. xi.

Author : Robert V. O'Neill
Publisher : Princeton University Press
Page : 266 pages
File Size : 40,45 MB
Release : 2021-09-14
Category : Science
ISBN : 0691236607

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"Ecosystem" is an intuitively appealing concept to most ecologists, but, in spite of its widespread use, the term remains diffuse and ambiguous. The authors of this book argue that previous attempts to define the concept have been derived from particular viewpoints to the exclusion of others equally possible. They offer instead a more general line of thought based on hierarchy theory. Their contribution should help to counteract the present separation of subdisciplines in ecology and to bring functional and population/community ecologists closer to a common approach. Developed as a way of understanding highly complex organized systems, hierarchy theory has at its center the idea that organization results from differences in process rates. To the authors the theory suggests an objective way of decomposing ecosystems into their component parts. The results thus obtained offer a rewarding method for integrating various schools of ecology.

Author : Grant Garrison Thompson
Publisher :
Page : 293 pages
File Size : 31,37 MB
Release : 1984
Category : Biological control systems
ISBN :

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A generalized mathematical model of ecosystems is developed. The model begins with the general class of systems known as state-determined systems, in which the time-derivative of each state variable is a function of some subset of the set of all system state variables and .environmental parameters. A formal basis is presented for considering the steady-state behavior of such systems in terms of isoclines, drawing upon the fields of graph theory, linear algebra, and differential equations. The simplifying capabilities of hierarchy theory are invoked to mitigate the adverse effects of model complexity. Like the theory of isocline analysis, the particular formulation of hierarchy theory presented is phrased in graph-theoretic terms, enabling the model to be developed as a technique for analyzing the steady-state behavior of hierarchical systems. The role of inter-level time scale heterogeneity in hierarchical organization is discussed. As an illustration of its ability to portray the behavior of spatially-nested hierarchies, the model is used to provide a perspective on data from the climax vegetation of the Great Smoky Mountains. The effects of time scale heterogeneity are also illustrated by using the model to organize data sets from several vegetation/avian communities across the United States. The vegetation is taken to behave with a lower characteristic frequency than the relatively rapidly-developing avian subcommunity, thus constraining the latter in a hierarchical fashion. In order to understand in a more general way the role such a model might play in advancing ecological understanding, a broad framework is presented for analyzing the role of conceptual structures in science and the place of models in these structures. A view of models as scientific metaphors is advanced as an alternative to the pictorial/realist interpretation of models. Given this understanding of models in general, the proposed model and its underlying assumptions are compared and contrasted with a set of four partial conceptual structures drawn from the fields of systems ecology, plant ecology, natural resource economics, and organismic systems theory.

Author : T. F. H. Allen
Publisher : University of Chicago Press
Page : 424 pages
File Size : 36,22 MB
Release : 2017-11-10
Category : Philosophy
ISBN : 022648968X

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Ecosystems are incredibly complex, non-linear structures and self-organized entities; they cannot be described by simple models or by statistical approaches. Within each ecosystem are scores of individuals interacting continuously with others and with their biotic and abiotic surroundings, over vast geographic spaces, and over varying time scales as well. To approach the enormity of this complexity, ecologists have developed tools to simplify and aggregate information, and among them is Hierarchy Theory. Instead of analyzing the whole structure to understand the functions of the system, Hierarchy Theory analyzes hierarchical levels only and the interactions between them. It draws upon two different paradigms of complexity, reductionism and holism, adapting the most useful features of each into a viable means of studying ecosystems. It reduces the amount of data the researcher has to deal with, and it explicitly considers the relevant entities and interconnections of a larger complex system according to a specific research question. Originally published in 1982, Hierarchy was the first book to apply the tool to ecological systems. In the three decades since its publication, the work has influenced myriad large scale research initiatives in ecology, and this new, thoroughly revised edition reflects the assimilation of the theory in ecological research, and its successful application to the understanding of complex systems.

Author : Franz Hölker
Publisher : Peter Lang Gmbh, Internationaler Verlag Der Wissenschaften
Page : 0 pages
File Size : 22,25 MB
Release : 2002
Category : Biological models
ISBN : 9783631389249

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Mathematical and computational approaches provide powerful tools in the study of problems in population biology and ecosystem science. Recent analytical advances, coupled with the enhanced potential of high-speed computation, have opened up new sights and presented new challenges especially in those fields of ecological theory which met methodological restrictions in the past: For many years scales and hierarchies have been considered an important research topic in ecology. Nevertheless, the prevailing methodological constraints frequently reduced the analysis to conceptual considerations. Conceptual structuring remains to be the primary practical contribution of scale and hierarchy to the development of ecological theory. In this volume we attempt to demonstrate to what extent this is currently changing. The application of models which are capable to represent precisely the relations of different scales and integration levels have made a remarkable progress and let us observe how a wide range of emergent properties can be analysed in the output of ecological models. By linking empirical findings and similar model specifications with the implementation of self-organisation processes on the level of model components, the analytical and synthetic power of modelling can be extended to a new, synergistic level. The contributions of this volume provide background, examples and current results. The volume starts with concept articles, then presents an example of artificial networks, provides papers concerning genetic aspects and ends with articles dealing with botanical features.

Author : Marc Kéry
Publisher : Academic Press
Page : 810 pages
File Size : 23,82 MB
Release : 2015-11-14
Category : Science
ISBN : 0128014865

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Applied Hierarchical Modeling in Ecology: Distribution, Abundance, Species Richness offers a new synthesis of the state-of-the-art of hierarchical models for plant and animal distribution, abundance, and community characteristics such as species richness using data collected in metapopulation designs. These types of data are extremely widespread in ecology and its applications in such areas as biodiversity monitoring and fisheries and wildlife management. This first volume explains static models/procedures in the context of hierarchical models that collectively represent a unified approach to ecological research, taking the reader from design, through data collection, and into analyses using a very powerful class of models. Applied Hierarchical Modeling in Ecology, Volume 1 serves as an indispensable manual for practicing field biologists, and as a graduate-level text for students in ecology, conservation biology, fisheries/wildlife management, and related fields. Provides a synthesis of important classes of models about distribution, abundance, and species richness while accommodating imperfect detection Presents models and methods for identifying unmarked individuals and species Written in a step-by-step approach accessible to non-statisticians and provides fully worked examples that serve as a template for readers' analyses Includes companion website containing data sets, code, solutions to exercises, and further information

Author : Charles Draper William Canham
Publisher : Princeton University Press
Page : 500 pages
File Size : 36,61 MB
Release : 2003-11-30
Category : Science
ISBN : 9780691092898

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Quantitative models are crucial to almost every area of ecosystem science. They provide a logical structure that guides and informs empirical observations of ecosystem processes. They play a particularly crucial role in synthesizing and integrating our understanding of the immense diversity of ecosystem structure and function. Increasingly, models are being called on to predict the effects of human actions on natural ecosystems. Despite the widespread use of models, there exists intense debate within the field over a wide range of practical and philosophical issues pertaining to quantitative modeling. This book--which grew out of a gathering of leading experts at the ninth Cary Conference--explores those issues. The book opens with an overview of the status and role of modeling in ecosystem science, including perspectives on the long-running debate over the appropriate level of complexity in models. This is followed by eight chapters that address the critical issue of evaluating ecosystem models, including methods of addressing uncertainty. Next come several case studies of the role of models in environmental policy and management. A section on the future of modeling in ecosystem science focuses on increasing the use of modeling in undergraduate education and the modeling skills of professionals within the field. The benefits and limitations of predictive (versus observational) models are also considered in detail. Written by stellar contributors, this book grants access to the state of the art and science of ecosystem modeling.

Author : Marc Kery
Publisher : Academic Press
Page : 820 pages
File Size : 34,30 MB
Release : 2020-10-10
Category : Nature
ISBN : 0128097272

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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 to people who are struggling to use complex or advanced modeling programs Synthesizes current ecological models and explains how they are inter-connected Contains numerous examples throughout the book, walking the reading through scenarios with both real and simulated data Provides an ideal resource for ecologists working in R software and in BUGS software for more flexible Bayesian analyses