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008 161028t20172017njua b 001 0 eng
020 _a9780691160573 (hardcover : acidfree paper)
040 _erda
050 0 0 _aQH 541.15.E265
_b.D568 2017
100 1 _aDietze, Michael Christopher,
_d1976-
_eauthor.
_924117
245 1 0 _aEcological forecasting /
_cMichael C. Dietze.
260 _aPrinceton :
_bPrinceton University Press,
_c[2017].
264 1 _aPrinceton :
_bPrinceton University Press,
_c[2017].
265 _aFFB
300 _ax, 270 pages :
_billustrations ;
_c27 cm.
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
504 _aIncludes bibliographical references (pages 245-259) and index.
520 _aEcologists 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.
650 0 _aEcosystem health
_xForecasting.
_924118
650 0 _aEcology
_xForecasting.
_924119
942 _2lcc
_cGS
984 _a066295
_blac