Ecological Forecasting
eBook - PDF

Ecological Forecasting

  1. 288 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Ecological Forecasting

About this book

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

    Frequently asked questions

    Yes, you can cancel anytime from the Subscription tab in your account settings on the Perlego website. Your subscription will stay active until the end of your current billing period. Learn how to cancel your subscription.
    No, books cannot be downloaded as external files, such as PDFs, for use outside of Perlego. However, you can download books within the Perlego app for offline reading on mobile or tablet. Learn more here.
    Perlego offers two plans: Essential and Complete
    • Essential is ideal for learners and professionals who enjoy exploring a wide range of subjects. Access the Essential Library with 800,000+ trusted titles and best-sellers across business, personal growth, and the humanities. Includes unlimited reading time and Standard Read Aloud voice.
    • Complete: Perfect for advanced learners and researchers needing full, unrestricted access. Unlock 1.4M+ books across hundreds of subjects, including academic and specialized titles. The Complete Plan also includes advanced features like Premium Read Aloud and Research Assistant.
    Both plans are available with monthly, semester, or annual billing cycles.
    We are an online textbook subscription service, where you can get access to an entire online library for less than the price of a single book per month. With over 1 million books across 1000+ topics, we’ve got you covered! Learn more here.
    Look out for the read-aloud symbol on your next book to see if you can listen to it. The read-aloud tool reads text aloud for you, highlighting the text as it is being read. You can pause it, speed it up and slow it down. Learn more here.
    Yes! You can use the Perlego app on both iOS or Android devices to read anytime, anywhere — even offline. Perfect for commutes or when you’re on the go.
    Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
    Yes, you can access Ecological Forecasting by Michael C. Dietze in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Ecology. We have over one million books available in our catalogue for you to explore.

    Table of contents

    1. Cover
    2. Title
    3. Copyright
    4. Contents
    5. Preface
    6. Acknowledgments
    7. 1. Introduction
    8. 2. From Models to Forecasts
    9. 3. Data, Large and Small
    10. 4. Scientific Workflows and the Informatics of Model-Data Fusion
    11. 5. Introduction to Bayes
    12. 6. Characterizing Uncertainty
    13. 7. Case Study: Biodiversity, Populations, and Endangered Species
    14. 8. Latent Variables and State-Space Models
    15. 9. Fusing Data Sources
    16. 10. Case Study: Natural Resources
    17. 11. Propagating, Analyzing, and Reducing Uncertainty
    18. 12. Case Study: Carbon Cycle
    19. 13. Data Assimilation 1: Analytical Methods
    20. 14. Data Assimilation 2: Monte Carlo Methods
    21. 15. Epidemiology
    22. 16. Assessing Model Performance
    23. 17. Projection and Decision Support
    24. 18. Final Thoughts
    25. References
    26. Index