The Eco-Evo Mandala: Simplifying Bacterioplankton Complexity into Ecohealth Signatures.

Mandala biocomplexity biogeochemical forcing climate change ecosystem health marine microbiome optimality

Journal

Entropy (Basel, Switzerland)
ISSN: 1099-4300
Titre abrégé: Entropy (Basel)
Pays: Switzerland
ID NLM: 101243874

Informations de publication

Date de publication:
08 Nov 2021
Historique:
received: 30 08 2021
revised: 30 10 2021
accepted: 05 11 2021
entrez: 27 11 2021
pubmed: 28 11 2021
medline: 28 11 2021
Statut: epublish

Résumé

The microbiome emits informative signals of biological organization and environmental pressure that aid ecosystem monitoring and prediction. Are the many signals reducible to a habitat-specific portfolio that characterizes ecosystem health? Does an optimally structured microbiome imply a resilient microbiome? To answer these questions, we applied our novel Eco-Evo Mandala to bacterioplankton data from four habitats within the Great Barrier Reef, to explore how patterns in community structure, function and genetics signal habitat-specific organization and departures from theoretical optimality. The Mandala revealed communities departing from optimality in habitat-specific ways, mostly along structural and functional traits related to bacterioplankton abundance and interaction distributions (reflected by ϵ and λ as power law and exponential distribution parameters), which are not linearly associated with each other. River and reef communities were similar in their relatively low abundance and interaction disorganization (low ϵ and λ) due to their protective structured habitats. On the contrary, lagoon and estuarine inshore reefs appeared the most disorganized due to the ocean temperature and biogeochemical stress. Phylogenetic distances (

Identifiants

pubmed: 34828169
pii: e23111471
doi: 10.3390/e23111471
pmc: PMC8625105
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Elroy Galbraith (E)

Graduate School of Information Science and Technology, Hokkaido University, Sapporo 060-0814, Japan.

Matteo Convertino (M)

bluEco Lab, Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.

Classifications MeSH