Finding generality in ecology: a model for globally distributed experiments

被引:383
作者
Borer, Elizabeth T. [1 ]
Harpole, W. Stanley [2 ]
Adler, Peter B. [3 ,4 ]
Lind, Eric M. [1 ]
Orrock, John L. [5 ]
Seabloom, Eric W. [1 ]
Smith, Melinda D. [6 ]
机构
[1] Univ Minnesota, St Paul, MN 55018 USA
[2] Iowa State Univ, Ames, IA 50011 USA
[3] Utah State Univ, Dept Wildland Resources, Logan, UT 84322 USA
[4] Utah State Univ, Ctr Ecol, Logan, UT 84322 USA
[5] Univ Wisconsin, Dept Zool, Madison, WI 53704 USA
[6] Colorado State Univ, Ft Collins, CO 80523 USA
来源
METHODS IN ECOLOGY AND EVOLUTION | 2014年 / 5卷 / 01期
基金
美国国家科学基金会;
关键词
collaborative experimental network; distributed experiment; meta-analysis; metadata; Nutrient Network; relational data base; POOR PREDICTOR; PRODUCTIVITY; HETEROGENEITY; PATTERNS; SCALE; ROOT;
D O I
10.1111/2041-210X.12125
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Advancing the field of ecology relies on understanding generalities and developing theories based on empirical and functional relationships that integrate across organismal to global spatial scales and span temporal scales. Significant advances in predicting responses of ecological communities to globally extensive anthropogenic perturbations, for example, require understanding the role of environmental context in determining outcomes, which in turn requires standardized experiments across sites and regions. Distributed collaborative experiments can lead to high-impact advances that would otherwise be unachievable. Here, we provide specific advice and considerations relevant to researchers interested in employing this emerging approach using as a case study our experience developing and running the Nutrient Network, a globally distributed experimental network (currently >75 sites in 17 countries) that arose from a grassroots, cooperative research effort. We clarify the design, goals and function of the Nutrient Network as a model to empower others in the scientific community to employ distributed experiments to advance our predictive understanding of global-scale ecological trends and responses. Our experiences to date demonstrate that globally distributed experimental science need not be prohibitively expensive or time-consuming on a per capita basis and is not limited to senior scientists or countries where science is well funded. While distributed experiments are not a panacea for understanding ecological systems, they can substantially complement existing approaches.
引用
收藏
页码:65 / +
页数:10
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