Ecological Forecasting
Michael C. Dietze
Princeton University Press
<b>An authoritative and accessible introduction to the concepts and tools needed to make ecology a more predictive science</b><br /><br />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?<i>Ecological Forecasting</i>is the first book to bring together the concepts and tools needed to make ecology a more predictive science.<br /><br /><i>Ecological Forecasting</i>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.<br /><br /><br /><br />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<br />Presents a probabilistic approach to prediction and iteratively updating forecasts based on new data<br />Describes statistical and informatics tools for bringing models and data together, with emphasis on:<br /><br />Quantifying and partitioning uncertainties<br /><br />Dealing with the complexities of real-world data<br /><br />Feedbacks to identifying data needs, improving models, and decision support<br /><br /><br />Numerous hands-on activities in R available online