统一
计算机科学
基础(证据)
钥匙(锁)
开发(拓扑)
比例(比率)
生态学
发展理论
管理科学
数据科学
数学
政治学
地理
工程类
生物
地图学
计算机安全
数学分析
经济
程序设计语言
法学
市场经济
作者
Pablo A. Marquet,Andrew P. Allen,James H. Brown,Jennifer A. Dunne,Brian J. Enquist,James F. Gillooly,Patricia Adair Gowaty,Jessica L. Green,John Harte,Steve P. Hubbell,James P. O’Dwyer,Jordan G. Okie,Annette Ostling,Mark E. Ritchie,David Štorch,Geoffrey B. West
出处
期刊:BioScience
[Oxford University Press]
日期:2014-07-11
卷期号:64 (8): 701-710
被引量:223
标识
DOI:10.1093/biosci/biu098
摘要
We argue for expanding the role of theory in ecology to accelerate scientific progress, enhance the ability to address environmental challenges, foster the development of synthesis and unification, and improve the design of experiments and large-scale environmental-monitoring programs. To achieve these goals, it is essential to foster the development of what we call efficient theories, which have several key attributes. Efficient theories are grounded in first principles, are usually expressed in the language of mathematics, make few assumptions and generate a large number of predictions per free parameter, are approximate, and entail predictions that provide well-understood standards for comparison with empirical data. We contend that the development and successive refinement of efficient theories provide a solid foundation for advancing environmental science in the era of big data.
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