Shifting levels of ecological network's analysis reveals different system properties.


Journal

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
ISSN: 1471-2970
Titre abrégé: Philos Trans R Soc Lond B Biol Sci
Pays: England
ID NLM: 7503623

Informations de publication

Date de publication:
13 04 2020
Historique:
entrez: 25 2 2020
pubmed: 25 2 2020
medline: 3 2 2021
Statut: ppublish

Résumé

Network analyses applied to models of complex systems generally contain at least three levels of analyses. Whole-network metrics summarize general organizational features (properties or relationships) of the entire network, while node-level metrics summarize similar organization features but consider individual nodes. The network- and node-level metrics build upon the primary pairwise relationships in the model. As with many analyses, sometimes there are interesting differences at one level that disappear in the summary at another level of analysis. We illustrate this phenomenon with ecosystem network models, where nodes are trophic compartments and pairwise relationships are flows of organic carbon, such as when a predator eats a prey. For this demonstration, we analysed a time-series of 16 models of a lake planktonic food web that describes carbon exchanges within an autumn cyanobacteria bloom and compared the ecological conclusions drawn from the three levels of analysis based on inter-time-step comparisons. A general pattern in our analyses was that the closer the levels are in hierarchy (node versus network, or flow versus node level), the more they tend to align in their conclusions. Our analyses suggest that selecting the appropriate level of analysis, and above all regularly using multiple levels, may be a critical analytical decision. This article is part of the theme issue 'Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.

Identifiants

pubmed: 32089120
doi: 10.1098/rstb.2019.0326
pmc: PMC7061957
doi:

Banques de données

figshare
['10.6084/m9.figshare.c.4824033']

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

20190326

Références

Philos Trans R Soc Lond B Biol Sci. 2009 Jun 27;364(1524):1789-801
pubmed: 19451128
Ecology. 2015 Jan;96(1):291-303
pubmed: 26236914
Trends Ecol Evol. 2012 Dec;27(12):689-97
pubmed: 22959162
Philos Trans R Soc Lond B Biol Sci. 2020 Apr 13;375(1796):20190329
pubmed: 32089114
Philos Trans R Soc Lond B Biol Sci. 2020 Apr 13;375(1796):20190321
pubmed: 32089110
ISME J. 2018 Apr;12(4):1008-1020
pubmed: 29416126
J Theor Biol. 1976 Feb;56(2):363-80
pubmed: 944838
Nat Neurosci. 2017 Feb 23;20(3):353-364
pubmed: 28230844
Philos Trans R Soc Lond B Biol Sci. 2020 Apr 13;375(1796):20190316
pubmed: 32089119
Q Rev Biol. 2016 Sep;91(3):321-42
pubmed: 29558615

Auteurs

Nathalie Niquil (N)

CNRS/Normandie Université, Research Unit BOREA (Biology of Aquatic Organisms and Ecosystems), MNHN, CNRS 7208, IRD 207, Sorbonne Université, Université de Caen Normandie, Université des Antilles, team EcoFunc, CS 14032, 14000 Caen, France.

Matilda Haraldsson (M)

CNRS/Normandie Université, Research Unit BOREA (Biology of Aquatic Organisms and Ecosystems), MNHN, CNRS 7208, IRD 207, Sorbonne Université, Université de Caen Normandie, Université des Antilles, team EcoFunc, CS 14032, 14000 Caen, France.
Department of Marine Sciences, University of Gothenburg, Box 461, 405 30 Göteborg, Sweden.
Sorbonne Université, Université Paris Est Créteil, Université Paris Diderot, CNRS, INRA, IRD, Institute of Ecology and Environmental Sciences-Paris, IEES-Paris, 75005 Paris, France.

Télesphore Sime-Ngando (T)

LMGE, Laboratoire Microorganismes: Génome et Environnement, Université Clermont Auvergne, UMR CNRS 6023, Aubière, France.

Philippe Huneman (P)

Institut d'Histoire et de Philosophie des Sciences et des Techniques, CNRS/Université Paris I Sorbonne, 13 rue du Four, 75 006 Paris, France.

Stuart R Borrett (SR)

University of North Carolina, Wilmington, Wilmington, NC 28403, USA.
Duke Network Analysis Center, Duke University, Durham, NC 27708, USA.

Articles similaires

Photosynthesis Ribulose-Bisphosphate Carboxylase Carbon Dioxide Molecular Dynamics Simulation Cyanobacteria

High-throughput Bronchus-on-a-Chip system for modeling the human bronchus.

Akina Mori, Marjolein Vermeer, Lenie J van den Broek et al.
1.00
Humans Bronchi Lab-On-A-Chip Devices Epithelial Cells Goblet Cells
Lakes Salinity Archaea Bacteria Microbiota
Rivers Turkey Biodiversity Environmental Monitoring Animals

Classifications MeSH