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Remote Sensing And Gis For Ecologists

Author: Martin Wegmann
Publisher: Pelagic Publishing Ltd
ISBN: 1784270245
Size: 47.81 MB
Format: PDF, Kindle
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This is a book about how ecologists can integrate remote sensing and GIS in their daily work. It will allow ecologists to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions.All practical examples in this book rely on OpenSource software and freely available data sets. Quantum GIS (QGIS) is introduced for basic GIS data handling, and in-depth spatial analytics and statistics are conducted with the software packages R and GRASS.Readers will learn how to apply remote sensing within ecological research projects, how to approach spatial data sampling and how to interpret remote sensing derived products. The authors discuss a wide range of statistical analyses with regard to satellite data as well as specialised topics such as time-series analysis. Extended scripts on how to create professional looking maps and graphics are also provided.This book is a valuable resource for students and scientists in the fields of conservation and ecology interested in learning how to get started in applying remote sensing in ecological research and conservation planning.

Statistics For Ecologists Using R And Excel

Author: Mark Gardener
Publisher: Pelagic Publishing Ltd
ISBN: 1784271411
Size: 80.10 MB
Format: PDF, ePub, Mobi
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This is a book about the scientific process and how you apply it to data in ecology. You will learn how to plan for data collection, how to assemble data, how to analyze data and finally how to present the results. The book uses Microsoft Excel and the powerful Open Source R program to carry out data handling as well as producing graphs.Statistical approaches covered include: data exploration; tests for difference – t-test and U-test; correlation – Spearman’s rank test and Pearson product-moment; association including Chi-squared tests and goodness of fit; multivariate testing using analysis of variance (ANOVA) and Kruskal–Wallis test; and multiple regression.Key skills taught in this book include: how to plan ecological projects; how to record and assemble your data; how to use R and Excel for data analysis and graphs; how to carry out a wide range of statistical analyses including analysis of variance and regression; how to create professional looking graphs; and how to present your results.New in this edition: a completely revised chapter on graphics including graph types and their uses, Excel Chart Tools, R graphics commands and producing different chart types in Excel and in R; an expanded range of support material online, including; example data, exercises and additional notes & explanations; a new chapter on basic community statistics, biodiversity and similarity; chapter summaries and end-of-chapter exercises.Praise for the first edition:This book is a superb way in for all those looking at how to design investigations and collect data to support their findings. – Sue Townsend, Biodiversity Learning Manager, Field Studies Council[M]akes it easy for the reader to synthesise R and Excel and there is extra help and sample data available on the free companion webpage if needed. I recommended this text to the university library as well as to colleagues at my student workshops on R. Although I initially bought this book when I wanted to discover R I actually also learned new techniques for data manipulation and management in Excel – Mark Edwards, EcoBloggingA must for anyone getting to grips with data analysis using R and excel. – Amazon 5-star reviewIt has been very easy to follow and will be perfect for anyone. – Amazon 5-star reviewA solid introduction to working with Excel and R. The writing is clear and informative, the book provides plenty of examples and figures so that each string of code in R or step in Excel is understood by the reader. – Goodreads, 4-star review

Remote Sensing Of Vegetation

Author: Hamlyn G Jones
Publisher: Oxford University Press
ISBN: 0199207798
Size: 41.71 MB
Format: PDF, Kindle
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An accessible yet rigorous introduction to remote sensing and its application to the study of vegetation for advanced undergraduate and graduate students. The underlying physical and mathematical principles of the techniques disucussed are explained in a way readily understood by those without a strong mathematical background.

Habitat Suitability And Distribution Models

Author: Antoine Guisan
Publisher: Cambridge University Press
ISBN: 0521765137
Size: 33.76 MB
Format: PDF, ePub, Mobi
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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.

Foundation Papers In Landscape Ecology

Author: John A. Wiens
Publisher: Columbia University Press
ISBN: 9780231126816
Size: 49.29 MB
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Landscape ecology focuses on spatial heterogeneity, or the idea that where things are and where they are in relation to other things can have important consequences for a wide range of phenomena. Landscape ecology integrates humans with natural ecosystems and brings a spatial perspective to such fields as natural resource management, conservation, and urban planning. The thirty-seven papers included in this volume present the origins and development of landscape ecology and encompass a variety of perspectives, approaches, and geographies. The editors begin with articles that illuminate the discipline's diverse scientific foundations, such as L. S. Berg's keystone paper outlining a geoecological analysis based on soil science, physical geography, and geology. Next they include selections exemplifying landscape ecologists' growing awareness of spatial pattern, the different ways they incorporated scale into their work, the progression of landscape ecology from a qualitative to a quantitative discipline, and how concepts from landscape ecology have come to permeate ecological research and influence land-use policy, conservation practices, landscape architecture, and geography. Together these articles provide a solid introduction to what is now widely recognized as an important area of research and application that encourages new ways of thinking about natural and human-dominated ecosystems

Community Ecology

Author: Mark Gardener
Publisher: Pelagic Publishing Ltd
ISBN: 1907807632
Size: 52.80 MB
Format: PDF, ePub
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Interactions between species are of fundamental importance to all living systems and the framework we have for studying these interactions is community ecology. This is important to our understanding of the planets biological diversity and how species interactions relate to the functioning of ecosystems at all scales. Species do not live in isolation and the study of community ecology is of practical application in a wide range of conservation issues. The study of ecological community data involves many methods of analysis. In this book you will learn many of the mainstays of community analysis including: diversity, similarity and cluster analysis, ordination and multivariate analyses. This book is for undergraduate and postgraduate students and researchers seeking a step-by-step methodology for analysing plant and animal communities using R and Excel. Microsoft's Excel spreadsheet is virtually ubiquitous and familiar to most computer users. It is a robust program that makes an excellent storage and manipulation system for many kinds of data, including community data. The R program is a powerful and flexible analytical system able to conduct a huge variety of analytical methods, which means that the user only has to learn one program to address many research questions. Its other advantage is that it is open source and therefore completely free. Novel analytical methods are being added constantly to the already comprehensive suite of tools available in R. Mark Gardener is both an ecologist and an analyst. He has worked in a range of ecosystems around the world and has been involved in research across a spectrum of community types. His knowledge of R is largely self-taught and this gives him insight into the needs of students learning to use R for complicated analyses.

An Introduction To R For Spatial Analysis And Mapping

Author: Chris Brunsdon
Publisher: SAGE
ISBN: 1473911192
Size: 75.13 MB
Format: PDF
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"In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using 'out of the box' software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical 'how to' guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses." - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive 'how to' that takes students - of any discipline - from coding to actual applications and uses of R.

Urban Ecology

Author: Kevin J. Gaston
Publisher: Cambridge University Press
ISBN: 1139536060
Size: 66.70 MB
Format: PDF, Docs
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This is the urban century in which, for the first time, the majority of people live in towns and cities. Understanding how people influence, and are influenced by, the 'green' component of these environments is therefore of enormous significance. Providing an overview of the essentials of urban ecology, the book begins by covering the vital background concepts of the urbanisation process and the effect that it can have on ecosystem functions and services. Later sections are devoted to examining how species respond to urbanisation, the many facets of human-ecology interactions, and the issues surrounding urban planning and the provision of urban green spaces. Drawing on examples from urban settlements around the world, it highlights the progress to date in this burgeoning field, as well as the challenges that lie ahead.

Circular Statistics In R

Author: Arthur Pewsey
Publisher: OUP Oxford
ISBN: 0191650765
Size: 48.16 MB
Format: PDF, ePub
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Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such as: observed compass directions of departure of radio-collared migratory birds from a release point; bond angles measured in different molecules; wind directions at different times of year at a wind farm; direction of stress-fractures in concrete bridge supports; longitudes of earthquake epicentres or seasonal and daily activity patterns, for example: data on the times of day at which animals are caught in a camera trap, or in 911 calls in New York, or in internet traffic; variation throughout the year in measles incidence, global energy requirements, TV viewing figures or injuries to athletes. The natural way of representing such data graphically is as points located around the circumference of a circle, hence their name. Importantly, circular variables are periodic in nature and the origin, or zero point, such as the beginning of a new year, is defined arbitrarily rather than necessarily emerging naturally from the system. This book will be of value both to those new to circular data analysis as well as those more familiar with the field. For beginners, the authors start by considering the fundamental graphical and numerical summaries used to represent circular data before introducing distributions that might be used to model them. They go on to discuss basic forms of inference such as point and interval estimation, as well as formal significance tests for hypotheses that will often be of scientific interest. When discussing model fitting, the authors advocate reduced reliance on the classical von Mises distribution; showcasing distributions that are capable of modelling features such as asymmetry and varying levels of kurtosis that are often exhibited by circular data. The use of likelihood-based and computer-intensive approaches to inference and modelling are stressed throughout the book. The R programming language is used to implement the methodology, particularly its "circular" package. Also provided are over 150 new functions for techniques not already covered within R. This concise but authoritative guide is accessible to the diverse range of scientists who have circular data to analyse and want to do so as easily and as effectively as possible.