Ecological forecasting
Enregistré dans:
| Auteur principal: | |
|---|---|
| Support: | E-Book |
| Langue: | Anglais |
| Publié: |
Princeton, NJ :
Princeton University Press,
[2017].
|
| Autres localisations: | Voir dans le Sudoc |
| Résumé: | 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 |
| Accès en ligne: | Accès à l'E-book |
| Résumé: | 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 |
|---|---|
| Description: | Description based on online resource; title from PDF title page (publisher's Web site, viewed May. 17, 2017) La pagination de l'édition imprimée correspondante est de 284 p. |
| Support: | Nécessite un navigateur et un lecteur de fichier PDF. |
| ISBN: | 9781400885459 |
| Accès: | L'accès complet à la ressource est réservé aux usagers des établissements qui en ont fait l'acquisition |