Best practices in prediction for decision-making : lessons from the atmospheric and earth sciences

Pielke, Roger A. & Conant, Richard T. (2003) Best practices in prediction for decision-making : lessons from the atmospheric and earth sciences. Ecology, 84(6), pp. 1351-1358.

View at publisher


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.

Impact and interest:

31 citations in Scopus
31 citations in Web of Science®
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

157 since deposited on 07 Oct 2010
8 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 37782
Item Type: Journal Article
Refereed: Yes
Additional URLs:
DOI: 10.1890/0012-9658(2003)084
ISSN: 0012-9658
Divisions: Past > Institutes > Institute for Sustainable Resources
Copyright Owner: Copyright 2003 Ecological Society of America
Deposited On: 07 Oct 2010 22:33
Last Modified: 25 Mar 2015 02:32

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page