Ecological Forecasting

Ecological Forecasting
Author :
Publisher : Princeton University Press
Total Pages : 285
Release :
ISBN-10 : 9781400885459
ISBN-13 : 1400885450
Rating : 4/5 (450 Downloads)

Book Synopsis Ecological Forecasting by : Michael C. Dietze

Download or read book Ecological Forecasting written by Michael C. Dietze and published by Princeton University Press. This book was released on 2017-05-30 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative and accessible introduction to the concepts and tools needed to make ecology a more predictive science Ecologists are being asked to respond to unprecedented environmental challenges. How can they provide the best available scientific information about what will happen in the future? Ecological Forecasting is the first book to bring together the concepts and tools needed to make ecology a more predictive science. Ecological Forecasting presents a new way of doing ecology. A closer connection between data and models can help us to project our current understanding of ecological processes into new places and times. This accessible and comprehensive book covers a wealth of topics, including Bayesian calibration and the complexities of real-world data; uncertainty quantification, partitioning, propagation, and analysis; feedbacks from models to measurements; state-space models and data fusion; iterative forecasting and the forecast cycle; and decision support. Features case studies that highlight the advances and opportunities in forecasting across a range of ecological subdisciplines, such as epidemiology, fisheries, endangered species, biodiversity, and the carbon cycle Presents a probabilistic approach to prediction and iteratively updating forecasts based on new data Describes statistical and informatics tools for bringing models and data together, with emphasis on: Quantifying and partitioning uncertainties Dealing with the complexities of real-world data Feedbacks to identifying data needs, improving models, and decision support Numerous hands-on activities in R available online


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