| 000 -LEADER |
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| fixed length control field |
nam a22 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
240213b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780691160573 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
577.0112 |
| Item number |
DIE |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Dietze, Michael Christopher |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Ecological forecasting |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
Princeton University Press, |
| Date of publication, distribution, etc |
2017 |
| Place of publication, distribution, etc |
Princeton : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
x, 270 p., |
| Other physical details |
ill., |
| Dimensions |
26 cm. |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
72.00 |
| Price type code |
$ |
| Unit of pricing |
86.50 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
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 dataDescribes statistical and informatics tools for bringing models and data together, with emphasis on:Quantifying and partitioning uncertaintiesDealing with the complexities of real-world dataFeedbacks to identifying data needs, improving models, and decision supportNumerous hands-on activities in R available online. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Ecological forecasting |
|
|---|
| Topical term or geographic name as entry element |
Monte Carlo Methods |
|
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| Topical term or geographic name as entry element |
Epidemiology |
|
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| Topical term or geographic name as entry element |
Fisheries |
|
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| Topical term or geographic name as entry element |
Endangered species |
|
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| Topical term or geographic name as entry element |
Biodiversity |
|
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| Topical term or geographic name as entry element |
Carbon cycle |
|
|---|
| Topical term or geographic name as entry element |
Ecosystem health forecasting |
|
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| Topical term or geographic name as entry element |
Nature ecology |
|
|---|
| Topical term or geographic name as entry element |
Environmental science |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |