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The Review And Application Of New Methods For Species Distribution Modeling
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Book Synopsis The Review and Application of New Methods for Species Distribution Modeling by : Samuel Dylan Veloz
Download or read book The Review and Application of New Methods for Species Distribution Modeling written by Samuel Dylan Veloz and published by . This book was released on 2008 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Forest Ecosystems by : Richard H. Waring
Download or read book Forest Ecosystems written by Richard H. Waring and published by Academic Press. This book was released on 1998 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cycles, water, carbon.
Book Synopsis Joint Species Distribution Modelling by : Otso Ovaskainen
Download or read book Joint Species Distribution Modelling written by Otso Ovaskainen and published by Cambridge University Press. This book was released on 2020-06-11 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive account of joint species distribution modelling, covering statistical analyses in light of modern community ecology theory.
Book Synopsis Mapping Species Distributions by : Janet Franklin
Download or read book Mapping Species Distributions written by Janet Franklin and published by Cambridge University Press. This book was released on 2010-01-07 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Maps of species' distributions or habitat suitability are required for many aspects of environmental research, resource management and conservation planning. These include biodiversity assessment, reserve design, habitat management and restoration, species and habitat conservation plans and predicting the effects of environmental change on species and ecosystems. The proliferation of methods and uncertainty regarding their effectiveness can be daunting to researchers, resource managers and conservation planners alike. Franklin summarises the methods used in species distribution modeling (also called niche modeling) and presents a framework for spatial prediction of species distributions based on the attributes (space, time, scale) of the data and questions being asked. The framework links theoretical ecological models of species distributions to spatial data on species and environment, and statistical models used for spatial prediction. Providing practical guidelines to students, researchers and practitioners in a broad range of environmental sciences including ecology, geography, conservation biology, and natural resources management.
Book Synopsis Habitat Suitability and Distribution Models by : Antoine Guisan
Download or read book Habitat Suitability and Distribution Models written by Antoine Guisan and published by Cambridge University Press. This book was released on 2017-09-14 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the key stages of niche-based habitat suitability model building, evaluation and prediction required for understanding and predicting future patterns of species and biodiversity. Beginning with the main theory behind ecological niches and species distributions, the book proceeds through all major steps of model building, from conceptualization and model training to model evaluation and spatio-temporal predictions. Extensive examples using R support graduate students and researchers in quantifying ecological niches and predicting species distributions with their own data, and help to address key environmental and conservation problems. Reflecting this highly active field of research, the book incorporates the latest developments from informatics and statistics, as well as using data from remote sources such as satellite imagery. A website at www.unil.ch/hsdm contains the codes and supporting material required to run the examples and teach courses.
Book Synopsis Invasive Species by : Andrew P. Robinson
Download or read book Invasive Species written by Andrew P. Robinson and published by Cambridge University Press. This book was released on 2017-06-08 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the latest risk-based techniques to protect national interests from invasive pests and pathogens before, at and within national borders.
Book Synopsis Ecological Niches and Geographic Distributions (MPB-49) by : A. Townsend Peterson
Download or read book Ecological Niches and Geographic Distributions (MPB-49) written by A. Townsend Peterson and published by Princeton University Press. This book was released on 2011-11-20 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Terminology, conceptual overview, biogeography, modeling.
Book Synopsis Spatial Complexity, Informatics, and Wildlife Conservation by : Samuel A. Cushman
Download or read book Spatial Complexity, Informatics, and Wildlife Conservation written by Samuel A. Cushman and published by Springer Science & Business Media. This book was released on 2009-12-21 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: As Earth faces the greatest mass extinction in 65 million years, the present is a moment of tremendous foment and emergence in ecological science. With leaps in advances in ecological research and the technical tools available, scientists face the critical task of challenging policymakers and the public to recognize the urgency of our global crisis. This book focuses directly on the interplay between theory, data, and analytical methodology in the rapidly evolving fields of animal ecology, conservation, and management. The mixture of topics of particular current relevance includes landscape ecology, remote sensing, spatial modeling, geostatistics, genomics, and ecological informatics. The greatest interest to the practicing scientist and graduate student will be the synthesis and integration of these topics to provide a composite view of the emerging field of spatial ecological informatics and its applications in research and management.
Book Synopsis Predictive Species and Habitat Modeling in Landscape Ecology by : C. Ashton Drew
Download or read book Predictive Species and Habitat Modeling in Landscape Ecology written by C. Ashton Drew and published by Springer Science & Business Media. This book was released on 2010-11-25 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most projects in Landscape Ecology, at some point, define a species-habitat association. These models are inherently spatial, dealing with landscapes and their configurations. Whether coding behavioral rules for dispersal of simulated organisms through simulated landscapes, or designing the sampling extent of field surveys and experiments in real landscapes, landscape ecologists must make assumptions about how organisms experience and utilize the landscape. These convenient working postulates allow modelers to project the model in time and space, yet rarely are they explicitly considered. The early years of landscape ecology necessarily focused on the evolution of effective data sources, metrics, and statistical approaches that could truly capture the spatial and temporal patterns and processes of interest. Now that these tools are well established, we reflect on the ecological theories that underpin the assumptions commonly made during species distribution modeling and mapping. This is crucial for applying models to questions of global sustainability. Due to the inherent use of GIS for much of this kind of research, and as several authors’ research involves the production of multicolored map figures, there would be an 8-page color insert. Additional color figures could be made available through a digital archive, or by cost contributions of the chapter authors. Where applicable, would be relevant chapters’ GIS data and model code available through a digital archive. The practice of data and code sharing is becoming standard in GIS studies, is an inherent method of this book, and will serve to add additional research value to the book for both academic and practitioner audiences.
Book Synopsis Machine Learning for Ecology and Sustainable Natural Resource Management by : Grant Humphries
Download or read book Machine Learning for Ecology and Sustainable Natural Resource Management written by Grant Humphries and published by Springer. This book was released on 2018-11-05 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology, digitization, online data availability, historic legacy datasets, remote sensors and the ability to collect data on animal movements via satellite and GPS have given rise to large, highly complex datasets. These datasets could be utilized for making critical management decisions, but are often “messy” and difficult to interpret. Basic artificial intelligence algorithms (i.e., machine learning) are powerful tools that are shaping the world and must be taken advantage of in the life sciences. In ecology, machine learning algorithms are critical to helping resource managers synthesize information to better understand complex ecological systems. Machine Learning has a wide variety of powerful applications, with three general uses that are of particular interest to ecologists: (1) data exploration to gain system knowledge and generate new hypotheses, (2) predicting ecological patterns in space and time, and (3) pattern recognition for ecological sampling. Machine learning can be used to make predictive assessments even when relationships between variables are poorly understood. When traditional techniques fail to capture the relationship between variables, effective use of machine learning can unearth and capture previously unattainable insights into an ecosystem's complexity. Currently, many ecologists do not utilize machine learning as a part of the scientific process. This volume highlights how machine learning techniques can complement the traditional methodologies currently applied in this field.
Book Synopsis Predicting Species Occurrences by : J. Michael Scott
Download or read book Predicting Species Occurrences written by J. Michael Scott and published by Island Press. This book was released on 2002-02 with total page 940 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictions about where different species are, where they are not, and how they move across a landscape or respond to human activities -- if timber is harvested, for instance, or stream flow altered -- are important aspects of the work of wildlife biologists, land managers, and the agencies and policymakers that govern natural resources. Despite the increased use and importance of model predictions, these predictions are seldom tested and have unknown levels of accuracy.Predicting Species Occurrences addresses those concerns, highlighting for managers and researchers the strengths and weaknesses of current approaches, as well as the magnitude of the research required to improve or test predictions of currently used models. The book is an outgrowth of an international symposium held in October 1999 that brought together scientists and researchers at the forefront of efforts to process information about species at different spatial and temporal scales. It is a comprehensive reference that offers an exhaustive treatment of the subject, with 65 chapters by leading experts from around the world that: review the history of the theory and practice of modeling and present a standard terminology examine temporal and spatial scales in terms of their influence on patterns and processes of species distribution offer detailed discussions of state-of-the-art modeling tools and descriptions of methods for assessing model accuracy discuss how to predict species presence and abundance present examples of how spatially explicit data on demographics can provide important information for managers An introductory chapter by Michael A. Huston examines the ecological context in which predictions of species occurrences are made, and a concluding chapter by John A. Wiens offers an insightful review and synthesis of the topics examined along with guidance for future directions and cautions regarding misuse of models. Other contributors include Michael P. Austin, Barry R. Noon, Alan H. Fielding, Michael Goodchild, Brian A. Maurer, John T. Rotenberry, Paul Angermeier, Pierre R. Vernier, and more than a hundred others.Predicting Species Occurrences offers important new information about many of the topics raised in the seminal volume Wildlife 2000 (University of Wisconsin Press, 1986) and will be the standard reference on this subject for years to come. Its state-of-the-art assessment will play a key role in guiding the continued development and application of tools for making accurate predictions and is an indispensable volume for anyone engaged in species management or conservation.
Book Synopsis Species Distribution Modeling by : Lifei Wang
Download or read book Species Distribution Modeling written by Lifei Wang and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Hierarchical Modeling and Inference in Ecology by : J. Andrew Royle
Download or read book Hierarchical Modeling and Inference in Ecology written by J. Andrew Royle and published by Elsevier. This book was released on 2008-10-15 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis The Use of Multivariate Statistics in Studies of Wildlife Habitat by : David E. Capen
Download or read book The Use of Multivariate Statistics in Studies of Wildlife Habitat written by David E. Capen and published by . This book was released on 1981 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Species Distribution Modelling by : Miguel B. Araújo
Download or read book Species Distribution Modelling written by Miguel B. Araújo and published by . This book was released on 2006 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pest Risk Modelling and Mapping for Invasive Alien Species by : Robert C Venette
Download or read book Pest Risk Modelling and Mapping for Invasive Alien Species written by Robert C Venette and published by CABI. This book was released on 2015-03-26 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past century, the number of species that have been transported to areas outside their native range has increased steadily. New pests and pathogens place biological pressure on valuable resident species, but strict bans may conflict with trading and travel needs. An overview of how the conflict can be managed using pest risk mapping and modelling, this book uses worked examples to explain modelling and help development of tool kits for assessment.
Book Synopsis Ensemble Methods in Data Mining by : Giovanni Seni
Download or read book Ensemble Methods in Data Mining written by Giovanni Seni and published by Morgan & Claypool Publishers. This book was released on 2010 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Ensemble methods have been called the most influential development in Data Mining and Machine Learning in the past decade. They combine multiple models into one usually more accurate than the best of its components. Ensembles can provide a critical boost to industrial challenges -- from investment timing to drug discovery, and fraud detection to recommendation systems -- where predictive accuracy is more vital than model interpretability. Ensembles are useful with all modeling algorithms, but this book focuses on decision trees to explain them most clearly. After describing trees and their strengths and weaknesses, the authors provide an overview of regularization -- today understood to be a key reason for the superior performance of modern ensembling algorithms. The book continues with a clear description of two recent developments: Importance Sampling (IS) and Rule Ensembles (RE). IS reveals classic ensemble methods -- bagging, random forests, and boosting -- to be special cases of a single algorithm, thereby showing how to improve their accuracy and speed. REs are linear rule models derived from decision tree ensembles. They are the most interpretable version of ensembles, which is essential to applications such as credit scoring and fault diagnosis. Lastly, the authors explain the paradox of how ensembles achieve greater accuracy on new data despite their (apparently much greater) complexity."--Publisher's website.