This multi-author book deals with ‘resource ecology’, which is the ecology of trophic interactions between consumers and their resources. All the chapters were subjected to intense group discussions; comments and critiques were subsequently used for writing new versions, which were peer-reviewed. Each chapter is followed by a comment. This makes the book ideal for teaching and course work, because it highlights the fact that ecology is a living and active research field.
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.
This book explores the theory and methods of systems analysis and computer modeling as applied to problems in ecology and natural resource management. It reflects the problems and conflicts between competing uses of limited space and the need for quantitative predictors of the outcome of various management strategies.
Unlike other natural resource management volumes that focus solely on the ecological aspects of resources and with an overly pessimistic view of the future this volume explores natural resource management in context in a functional, applied framework by integrating ecology, history, planning, economics, and policy into coverage of each natural resource, and by providing a balanced, guarded optimistic view of the most current research and technology's capability to overcome natural resource problems. Exceptionally straightforward and readable, it is easily accessible to readers with limited background in ecology, biology, and economics. The volume provides an overview of natural resources, and a complete analysis of management foundations, air, water, and land resources, the land-based renewable resources, the wild living resources, the mineral and energy resources, plus an integration of natural resources management. For foresters, wildlife biologists, geologists, range managers, and environmental scientists. "
Choosing the optimal management option requires environmental risk managers and decision makers to evaluate diverse, and not always congruent, needs and interests of multiple stakeholders. Understanding the trade-offs of different options as well as their legal, economic, scientific, and technological implications is critical to performing accurate
Sacred Ecology examines bodies of knowledge held by indigenous and other rural peoples around the world, and asks how we can learn from this knowledge and ways of knowing. Berkes explores the importance of local and indigenous knowledge as a complement to scientific ecology, and its cultural and political significance for indigenous groups themselves. This third edition further develops the point that traditional knowledge as process, rather than as content, is what we should be examining. It has been updated with about 150 new references, and includes an extensive list of web resources through which instructors can access additional material and further illustrate many of the topics and themes in the book. Winner of the Ecological Society of America's 2014 Sustainability Science Award.
Although Bissonette (Utah Cooperative Fish and Wildlife Research Unit, Utah State U., U.S.) and Storch (Weihenstephan Center of Life Sciences, Technische U. Munchen, Germany) state that a cohesive theory of landscape ecology is not yet possible, they present 17 papers they see as providing elements of theoretical framework, specifically as related to problems of resource management practice. Separate sections address linkages between conceptual and quantitative issues, between people and the landscape, and between theory and management in the field. Annotation copyrighted by Book News, Inc., Portland, OR.
The groundbreaking Encyclopedia of Ecology provides an authoritative and comprehensive coverage of the complete field of ecology, from general to applied. It includes over 500 detailed entries, structured to provide the user with complete coverage of the core knowledge, accessed as intuitively as possible, and heavily cross-referenced. Written by an international team of leading experts, this revolutionary encyclopedia will serve as a one-stop-shop to concise, stand-alone articles to be used as a point of entry for undergraduate students, or as a tool for active researchers looking for the latest information in the field. Entries cover a range of topics, including: Behavioral Ecology Ecological Processes Ecological Modeling Ecological Engineering Ecological Indicators Ecological Informatics Ecosystems Ecotoxicology Evolutionary Ecology General Ecology Global Ecology Human Ecology System Ecology The first reference work to cover all aspects of ecology, from basic to applied Over 500 concise, stand-alone articles are written by prominent leaders in the field Article text is supported by full-color photos, drawings, tables, and other visual material Fully indexed and cross referenced with detailed references for further study Writing level is suited to both the expert and non-expert Available electronically on ScienceDirect shortly upon publication
An innovative introduction to ecology and evolution This unique textbook introduces undergraduate students to quantitative models and methods in ecology, behavioral ecology, evolutionary biology, and conservation. It explores the core concepts shared by these related fields using tools and practical skills such as experimental design, generating phylogenies, basic statistical inference, and persuasive grant writing. And contributors use examples from their own cutting-edge research, providing diverse views to engage students and broaden their understanding. This is the only textbook on the subject featuring a collaborative "active learning" approach that emphasizes hands-on learning. Every chapter has exercises that enable students to work directly with the material at their own pace and in small groups. Each problem includes data presented in a rich array of formats, which students use to answer questions that illustrate patterns, principles, and methods. Topics range from Hardy-Weinberg equilibrium and population effective size to optimal foraging and indices of biodiversity. The book also includes a comprehensive glossary. In addition to the editors, the contributors are James Beck, Cawas Behram Engineer, John Gaskin, Luke Harmon, Jon Hess, Jason Kolbe, Kenneth H. Kozak, Robert J. Robertson, Emily Silverman, Beth Sparks-Jackson, and Anton Weisstein. Provides experience with hypothesis testing, experimental design, and scientific reasoning Covers core quantitative models and methods in ecology, behavioral ecology, evolutionary biology, and conservation Turns "discussion sections" into "thinking labs" Professors: A supplementary Instructor's Manual is available for this book. It is restricted to teachers using the text in courses. For information on how to obtain a copy, refer to: http://press.princeton.edu/class_use/solutions.html
