Bibliometric review of ecological network analysis: 2010–2016

Published

Journal Article (Review)

© 2018 Elsevier B.V. Ecological Network Analysis (ENA) combines modeling and analysis used to investigate the structure, function, and evolution of ecosystems and other complex systems. ENA is applied to network models that trace the movement of thermodynamically conserved energy or matter through the system. Investigators use ENA to answer a range of questions such as the following. What is the impact of fishing on the marine food web? Which species control the flux of nitrogen in an estuary? What is the ecological relationship among species in the food web when direct and indirect influences are considered? Would a proposed regulation make a city more sustainable? The field has grown since its inception in the 1970s, but it has rarely been systematically reviewed. This absence of reviews likely hinders the development of the field as a whole, obscures the diversity of its applications, and makes it difficult for new investigators to learn, develop, and apply the techniques. The objective of the work presented in this paper was to systematically review ENA research published in 2010 through 2016 to (1) identify the topic diversity, (2) expose methodological development, (3) highlight applications, and (4) assess collaboration among ENA scholars. To accomplish this, we used a combination of bibliometric, network (e.g., social network), and feature analyses. Our search identified 186 records. A topic network built from the bibliographic records revealed eight major topic clusters. The largest groups centered on food webs, urban metabolism, and ecosystem theory. Co-author analysis identified 387 authors in a collaboration network with eight larger components. The largest component contained 56% of the authors. This review shows ENA to be a topically diverse and collaborative science domain, and suggests opportunities to further develop ENA to better address issues in theoretical ecology and for environmental impact assessment and management.

Full Text

Duke Authors

Cited Authors

  • Borrett, SR; Sheble, L; Moody, J; Anway, EC

Published Date

  • August 24, 2018

Published In

Volume / Issue

  • 382 /

Start / End Page

  • 63 - 82

International Standard Serial Number (ISSN)

  • 0304-3800

Digital Object Identifier (DOI)

  • 10.1016/j.ecolmodel.2018.04.020

Citation Source

  • Scopus