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Ecological Forecasting

By (author) Michael Dietze
Format: Hardback
Publisher: Princeton University Press, New Jersey, United States
Published: 30th May 2017
Dimensions: w 179mm h 266mm d 24mm
Weight: 775g
ISBN-10: 0691160570
ISBN-13: 9780691160573
Barcode No: 9780691160573
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Synopsis
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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"Shortlisted for the 2018 TWS Wildlife Publication Awards, The Wildlife Society" "This book is unique in its scope, and it will be for many years, until ecologists embrace its message: to understand how nature works, we have to propose mechanistic models and test them. Their uncertainties reveal what we do not know, and where prediction error can be minimised by future work. . . . [This book] will give any reader a wider view of the data-model tandem, and dense information on how to step up to the next level of ecological forecasting."---Carsten F. Dormann, Basic and Applied Ecology "[Dietze] does a great job of clearly explaining complex statistical procedures . . . . ecological modelers will find this book invaluable, and students who want to deepen their understanding of these topics will find it worthwhile." * Conservation Biology *