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Ecosystem Management

United States. Congress. Senate. Committee on Agriculture, Nutrition, and Forestry. Subcommittee on Agricultural Research, Conservation, Forestry, and General Legislation

Published: 1995

Total Pages: 88


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Distributed to some depository libraries in microfiche.
Even as they increase the beauty of our surroundings, trees provide us with a great many ecosystem services, incl. air quality improvement, energy conservation, stormwater interception, and carbon dioxide reduction. These benefits must be weighed against the costs of maintaining trees, including planting, pruning, irrigation, admin., pest control, liability, cleanup, and removal. This report presents benefits and costs for representative small, medium, and large trees in the Tropical region based on research carried out in Honolulu, Hawaii. Average annual net benefits increase with tree size and differ based on location:. Two hypothetical examples of planting projects are described to illustrate how the data in this guide can be adapted to local uses.
"Southern forests provide innumerable benefits. Forest scientists, managers, owners, and users have in common the desire to improve the condition of these forests and the ecosystems they support. A first step is to understand the contributions science has made and continues to make to the care and management of forests. This book represents a celebration of past accomplishments, summarizes the current state of knowledge, and creates a vision for the future of southern forestry research and management. Chapters are organized into seven sections: "Looking Back," "Productivity," "Forest Health," "Water and Soils," "Socioeconomic," "Biodiversity," and "Climate Change." Each section is preceded by a brief introductory chapter. Authors were encouraged to focus on the most important aspects of their topics; citations are included to guide readers to further information."
Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.