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Ecological Informatics: Data Management and Knowledge Discovery [Hardcover]

Item : Ecological Informatics: Data Management and Knowledge Discovery [Hardcover]
Price : $242.99 (see below)
Category : Books
ISBN-10 ISBN-10 : 3319599267
ISBN-13 ISBN-13 : 9783319599267
Publisher Publisher : Springer
Binding Binding : Hardcover
Item ID : 100636700

This book introduces readers to ecological informatics as an emerging discipline that takes into account the data-intensive nature of ecology, the valuable information to be found in ecological data, and the need to communicate results and inform decisions, including those related to research, conservation and resource management. At its core, ecological informatics combines developments in information technology and ecological theory with applications that facilitate ecological research and the dissemination of results to scientists and the public. Its conceptual framework links ecological entities (genomes, organisms, populations, communities, ecosystems, landscapes) with data management, analysis and synthesis, and communicates new findings to inform decisions by following the course of a loop.

In comparison to the 2nd edition published in 2006, the 3rd edition of Ecological Informatics has been completely restructured on the basis of the generic conceptual f

ramework provided in Figure 1. It reflects the significant advances in data management, analysis and synthesis that have been made over the past 10 years, including new remote and in situ sensing techniques, the emergence of ecological and environmental observatories, novel evolutionary computations for knowledge discovery and forecasting, and new approaches to communicating results and informing decisions.

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Ecological Informatics: An Introduction.- Project Data Management Planning.- Scientific Databases for Environmental Research.- Quality Assurance and Quality Control (QA/QC).- Creating and Managing Metadata.- Preserve: Protecting Data for Long-term Use.- Data Discovery.- Data Integration: Principles and Practice.- Inferential Modelling of Population Dynamics.- Process-based Modeling of Nutrient Cycles and Food-web Dynamics.- Uncertainty Analysis by Bayesial≥÷

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