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An introductory text that offers a survey of ecology, this work presents examples from natural history, coverage of evolution, and quantitative approach. It includes 20 data analysis modules that introduce students to ecological data and quantitative methods used by ecologists.
Now in its seventh edition, this landmark textbook has helped to define introductory ecology courses for over four decades. With a dramatic transformation from previous editions, this text helps lecturers embrace the challenges and opportunities of teaching ecology in a contemporary lecture hall. The text maintains its signature evolutionary perspective and emphasis on the quantitative aspects of the field, but it has been completely rewritten for today’s undergraduates. Modernised in a new streamlined format, from 27 to 23 chapters, it is manageable now for a one-term course. Chapters are organised around four to six key concepts that are repeated as major headings and repeated again in streamlined summaries. Ecology: The Economy of Nature is available with SaplingPlus.An online solution that combines an e-book of the text, Ricklef’s powerful multimedia resources, and the robust problem bank of Sapling Learning. Every problem entered by a student will be answered with targeted feedback, allowing your students to learn with every question they answer.
The classic introductory text offers a balanced survey of Ecology. It is best known for its vivid examples from natural history, comprehensive coverage of evolution and quantitative approach. Due to popular demand, the fifth edition update brings twenty new data analysis modules that introduce students to ecological data and quantitative methods used by ecologists.
Social problems affect everyone. Because so many actual and potential problems confront us, it is often difficult to decide which ones affect us most severely. Is it the threat of death or injury during a terrorist attack? Is it the threat caused by industrial pollution that may poison us or destroy our physical environment? Or does quiet but viciously damaging gender, age, class, racial, or ethnic discrimination have the most far-reaching effect? Do the problems of cities affect us if we live in the suburbs? Do poorer nations′ problems with overpopulation affect our quality of life? The Encyclopedia of Social Problems offers an interdisciplinary perspective into many social issues that are a continuing concern in our lives, whether we confront them on a personal, local, regional, national, or global level. With more than 600 entries, these two volumes cover all of the major theories, approaches, and contemporary issues in social problems and also provide insight into how social conditions get defined as social problems, and the ways different people and organizations view and try to solve them. Key Features · Provides as comprehensive an approach as possible to this multifaceted field by using experts and scholars from 19 disciplines: anthropology, biology, business, chemistry, communications, criminal justice, demography, economics, education, environmental studies, geography, health, history, languages, political science, psychology, social work, sociology, and women′s studies · Presents a truly international effort with contributors from 17 countries: Argentina, Australia, Canada, England, France, Germany, Greece, Hong Kong, India, Ireland, Italy, Kenya, New Zealand, Romania, Scotland, Turkey, and the United States · Addresses social problems that are fairly new, such as computer crimes and identity theft, and others that are centuries old, such as poverty and prostitution · Examines social problems differently from place to place and from one era to another · Explains the perspectives and foundations of various social theories and offers different lenses to view the same reality Key Themes · Aging and the Life Course · Community, Culture, and Change · Crime and Deviance · Economics and Work · Education · Family · Gender Inequality and Sexual Orientation · Health · Housing and Urbanization · Politics, Power, and War · Population and Environment · Poverty and Social Class · Race and Ethnic Relations · Social Movements · Social Theory · Substance Abuse Readers investigating virtually any social problem will find a rich treasure of information and insights in this reference work, making it a must-have resource for any academic library.
Ecological data has several special properties: the presence or absence of species on a semi-quantitative abundance scale; non-linear relationships between species and environmental factors; and high inter-correlations among species and among environmental variables. The analysis of such data is important to the interpretation of relationships within plant and animal communities and with their environments. In this corrected version of Data Analysis in Community and Landscape Ecology, without using complex mathematics, the contributors demonstrate the methods that have proven most useful, with examples, exercises and case-studies. Chapters explain in an elementary way powerful data analysis techniques such as logic regression, canonical correspondence analysis, and kriging.
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.
Key features: Unique in its combination of serving as an introduction to spatial statistics and to modeling agricultural and ecological data using R Provides exercises in each chapter to facilitate the book's use as a course textbook or for self-study Adds new material on generalized additive models, point pattern analysis, and new methods of Bayesian analysis of spatial data. Includes a completely revised chapter on the analysis of spatiotemporal data featuring recently introduced software and methods Updates its coverage of R software including newly introduced packages Spatial Data Analysis in Ecology and Agriculture Using R, 2nd Edition provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology, agriculture, and environmental science. Readers have praised the book's practical coverage of spatial statistics, real-world examples, and user-friendly approach in presenting and explaining R code, aspects maintained in this update. Using data sets from cultivated and uncultivated ecosystems, the 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. Additional material to accompany the book, on both analyzing satellite data and on multivariate analysis, can be accessed at https: //www.plantsciences.ucdavis.edu/plant/additionaltopics.htm.
The 3rd edition of this popular textbook introduces the reader to the investigation of vegetation systems with an emphasis on data analysis. The book succinctly illustrates the various paths leading to high quality data suitable for pattern recognition, pattern testing, static and dynamic modelling and model testing including spatial and temporal aspects of ecosystems. Step-by-step introductions using small examples lead to more demanding approaches illustrated by real world examples aimed at explaining interpretations. All data sets and examples described in the book are available online and are written using the freely available statistical package R. This book will be of particular value to beginning graduate students and postdoctoral researchers of vegetation ecology, ecological data analysis, and ecological modelling, and experienced researchers needing a guide to new methods. A completely revised and updated edition of this popular introduction to data analysis in vegetation ecology. Includes practical step-by-step examples using the freely available statistical package R. Complex concepts and operations are explained using clear illustrations and case studies relating to real world phenomena. Emphasizes method selection rather than just giving a set of recipes.
Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions—including all R codes—that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types. - Introduces Bayesian data analysis, allowing users to obtain uncertainty measurements easily for any derived parameter of interest - Written in a step-by-step approach that allows for eased understanding by non-statisticians - Includes a companion website containing R-code to help users conduct Bayesian data analyses on their own data - All example data as well as additional functions are provided in the R-package blmeco
From the preface by Joel E. Cohen: "A century from now humanity will live in a managed - or mismanaged - global garden. We are debating the need to preserve tropical forests. Farming of the sea is providing an increasing part of our fish supply. We are beginning to control atmospheric emissions. In 100 years, we shall use novel farming practices and genetic engineering of bacteria to manipulate the methane production of rice fields. The continental shelf will be providing food, energy, possibly even living space. To make such intensive management possible will require massive improvements in data collection and analysis, and especially in our concepts. A century hence we will live on a wired earth: the oceans and the crust of the earth will receive the same comprehensive monitoring now devoted to weather. As the peoples of currently developing countries increase their levels of wealth, the need for global management will become irresistible as impatience with the accidents of nature and intolerance of mismanagement of the environment - especially of living resources - grow. Our control of physical perturbations and chemical inputs to the environment will be judged by the consequences to living organisms and biological communities. How can we obtain the factual and theoretical foundation needed to move from our present, fragmented knowledge and limited abilities to a managed, global garden?" This problem was addressed in the lectures and workshops of a summer school on patch dynamics at Cornell University. The school emphasized the analysis and interpretation of spatial patterns in terrestrial and marine environments. This book contains the course material of this school, combining general reviews with specific applications.