BEST PRACTICES IN PREDICTION FOR DECISION-MAKING: LESSONS FROM THE ATMOSPHERIC AND EARTH SCIENCES

BEST PRACTICES IN PREDICTION FOR DECISION-MAKING: LESSONS FROM THE ATMOSPHERIC AND EARTH SCIENCES Predictions that result from scientific research hold great appeal for decision-makers who are grappling with complex and controversial environmental issues, by promising to enhance their ability to determine a need for and outcomes of alternative decisions. A problem exists in that decision-makers and scientists in the public and private sectors solicit, produce, and use such predictions with little understanding of their accuracy or utility, and often without systematic evaluation or mechanisms of accountability. In order to contribute to a more effective role for ecological science in support of decision-making, this paper discusses three ““best practices”” for quantitative ecosystem modeling and prediction gleaned from research on modeling, prediction, and decision-making in the atmospheric and earth sciences. The lessons are distilled from a series of case studies and placed into the specific context of examples from ecological science. Corresponding Editor: J. S. Clark http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Ecology Ecological Society of America

BEST PRACTICES IN PREDICTION FOR DECISION-MAKING: LESSONS FROM THE ATMOSPHERIC AND EARTH SCIENCES

Ecology, Volume 84 (6) – Jun 1, 2003

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Publisher
Ecological Society of America
Copyright
Copyright © 2003 by the Ecological Society of America
Subject
Special Feature
ISSN
0012-9658
D.O.I.
10.1890/0012-9658%282003%29084%5B1351:BPIPFD%5D2.0.CO%3B2
Publisher site
See Article on Publisher Site

Abstract

Predictions that result from scientific research hold great appeal for decision-makers who are grappling with complex and controversial environmental issues, by promising to enhance their ability to determine a need for and outcomes of alternative decisions. A problem exists in that decision-makers and scientists in the public and private sectors solicit, produce, and use such predictions with little understanding of their accuracy or utility, and often without systematic evaluation or mechanisms of accountability. In order to contribute to a more effective role for ecological science in support of decision-making, this paper discusses three ““best practices”” for quantitative ecosystem modeling and prediction gleaned from research on modeling, prediction, and decision-making in the atmospheric and earth sciences. The lessons are distilled from a series of case studies and placed into the specific context of examples from ecological science. Corresponding Editor: J. S. Clark

Journal

EcologyEcological Society of America

Published: Jun 1, 2003

Keywords: atmospheric sciences ; best practices ; decision-makers ; earth sciences ; prediction ; quantitative ecosystem modeling

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