Today's natural resource managers must be able to navigate among the complicated interactions and conflicting interests of diverse stakeholders and decisionmakers. Technical and scientific knowledge, though necessary, are not sufficient. Science is merely one component in a multifaceted world of decision making. And while the demands of resource management have changed greatly, natural resource education and textbooks have not. Until now. Ecosystem Management represents a different kind of textbook for a different kind of course. It offers a new and exciting approach that engages students in active problem solving by using detailed landscape scenarios that reflect the complex issues and conflicting interests that face today's resource managers and scientists. Focusing on the application of the sciences of ecology and conservation biology to real-world concerns, it emphasizes the intricate ecological, socioeconomic, and institutional matrix in which natural resource management functions, and illustrates how to be more effective in that challenging arena. Each chapter is rich with exercises to help facilitate problem-based learning. The main text is supplemented by boxes and figures that provide examples, perspectives, definitions, summaries, and learning tools, along with a variety of essays written by practitioners with on-the-ground experience in applying the principles of ecosystem management. Accompanying the textbook is an instructor's manual that provides a detailed overview of the book and specific guidance on designing a course around it. Ecosystem Management grew out of a training course developed and presented by the authors for the U.S. Fish and Wildlife Service at its National Training Center in Shepherdstown, West Virginia. In 20 offerings to more than 600 natural resource professionals, the authors learned a great deal about what is needed to function successfully as a professional resource manager. The book offers important insights and a unique perspective dervied from that invaluable experience.

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.

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.

Brings scientists, policy makers, land and water managers and citizen stakeholders together to resolve natural resource and environmental problems.

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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.

The Systems Ecology Paradigm (SEP) incorporates humans as integral parts of ecosystems and emphasizes issues that have significant societal relevance such as grazing land, forestland, and agricultural ecosystem management, biodiversity and global change impacts. Accomplishing this societally relevant research requires cutting-edge basic and applied research. This book focuses on environmental and natural resource challenges confronting local to global societies for which the SEP methodology must be utilized for resolution. Key elements of SEP are a holistic perspective of ecological/social systems, systems thinking, and the ecosystem approach applied to real world, complex environmental and natural resource problems. The SEP and ecosystem approaches force scientific emphasis to be placed on collaborations with social scientists and behavioral, learning, and marketing professionals. The SEP has given environmental scientists, decision makers, citizen stakeholders, and land and water managers a powerful set of tools to analyse, integrate knowledge, and propose adoption of solutions to important local to global problems.