Skip to Main Content (Press Enter)

Logo CNR
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills

UNI-FIND
Logo CNR

|

UNI-FIND

cnr.it
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills
  1. Outputs

Toward a cohesive understanding of ecological complexity

Academic Article
Publication Date:
2023
abstract:
Ecological systems are quintessentially complex systems. Understanding and being able to predict phenomena typical of complex systems is, therefore, critical to progress in ecology and conservation amidst escalating global environmental change. However, myriad definitions of complexity and excessive reliance on conventional scientific approaches hamper conceptual advances and synthesis. Ecological complexity may be better understood by following the solid theoretical basis of complex system science (CSS). We review features of ecological systems described within CSS and conduct bibliometric and text mining analyses to characterize articles that refer to ecological complexity. Our analyses demonstrate that the study of complexity in ecology is a highly heterogeneous, global endeavor that is only weakly related to CSS. Current research trends are typically organized around basic theory, scaling, and macroecology. We leverage our review and the generalities identified in our analyses to suggest a more coherent and cohesive way forward in the study of complexity in ecology.
Iris type:
01.09 Rassegna della letteratura scientifica in rivista (Literature review)
Keywords:
Complexity; Scientometrics; Network
List of contributors:
Mammola, Stefano
Authors of the University:
MAMMOLA STEFANO
Handle:
https://iris.cnr.it/handle/20.500.14243/464355
Published in:
SCIENCE ADVANCES
Journal
  • Overview

Overview

URL

http://www.scopus.com/record/display.url?eid=2-s2.0-85163061367&origin=inward
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.5.0.0 | Sorgente dati: PREPROD (Ribaltamento disabilitato)