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Toward a cohesive understanding of ecological complexity
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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284553/ https://www.ncbi.nlm.nih.gov/pubmed/37343095 http://dx.doi.org/10.1126/sciadv.abq4207 |
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author | Riva, Federico Graco-Roza, Caio Daskalova, Gergana N. Hudgins, Emma J. Lewthwaite, Jayme M. M. Newman, Erica A. Ryo, Masahiro Mammola, Stefano |
author_facet | Riva, Federico Graco-Roza, Caio Daskalova, Gergana N. Hudgins, Emma J. Lewthwaite, Jayme M. M. Newman, Erica A. Ryo, Masahiro Mammola, Stefano |
author_sort | Riva, Federico |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10284553 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-102845532023-06-22 Toward a cohesive understanding of ecological complexity Riva, Federico Graco-Roza, Caio Daskalova, Gergana N. Hudgins, Emma J. Lewthwaite, Jayme M. M. Newman, Erica A. Ryo, Masahiro Mammola, Stefano Sci Adv Earth, Environmental, Ecological, and Space Sciences 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. American Association for the Advancement of Science 2023-06-21 /pmc/articles/PMC10284553/ /pubmed/37343095 http://dx.doi.org/10.1126/sciadv.abq4207 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Earth, Environmental, Ecological, and Space Sciences Riva, Federico Graco-Roza, Caio Daskalova, Gergana N. Hudgins, Emma J. Lewthwaite, Jayme M. M. Newman, Erica A. Ryo, Masahiro Mammola, Stefano Toward a cohesive understanding of ecological complexity |
title | Toward a cohesive understanding of ecological complexity |
title_full | Toward a cohesive understanding of ecological complexity |
title_fullStr | Toward a cohesive understanding of ecological complexity |
title_full_unstemmed | Toward a cohesive understanding of ecological complexity |
title_short | Toward a cohesive understanding of ecological complexity |
title_sort | toward a cohesive understanding of ecological complexity |
topic | Earth, Environmental, Ecological, and Space Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284553/ https://www.ncbi.nlm.nih.gov/pubmed/37343095 http://dx.doi.org/10.1126/sciadv.abq4207 |
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