Collaboration across Time and Space in the LTER Network. (4th March 2020)

• Record Type: Journal Article
• Authors: Huang, Tian-Yuan; Downs, Martha R; Ma, Jun; Zhao, Bin
• Is Part Of: BioScience. Volume 70:Number 4(2020:Apr.)
• Page Start: 353
• Page End: 364
• Publication Date: 2020-03-04
• Subjects: collaboration -- data sharing -- LTER -- Monte Carlo method -- social network analysis; Life sciences -- Periodicals; Life sciences -- Research -- Periodicals; Life sciences -- United States -- Periodicals; Life sciences -- Government policy -- United States -- Periodicals; Biology -- Periodicals; Biotechnology industries -- Periodicals; 570
• DOI: 10.1093/biosci/biaa014
• Languages: English
• ISSNs: 0006-3568

Abstract

Abstract: The scale of ecological research is getting larger and larger. At such scales, collaboration is indispensable, but there is little consensus on what factors enable collaboration. In the present article, we investigated the temporal and spatial pattern of institutional collaboration within the US Long Term Ecological Research (LTER) Network on the basis of the bibliographic database. Social network analysis and the Monte Carlo method were applied to identify the characteristics of papers published by LTER researchers within a baseline of papers from 158 leading ecological journals. Long-term and long-distance collaboration were more frequent in the LTER Network, and we investigate and discuss the underlying mechanisms. We suggest that the maturing infrastructure and environment for collaboration within the LTER Network could encourage scientists to make large-scale hypotheses and to ask big questions in ecology.