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Journal Article

Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters

MPS-Authors
/persons/resource/persons98923

Solly,  Emily
Department Biogeochemical Processes, Prof. S. E. Trumbore, Max Planck Institute for Biogeochemistry, Max Planck Society;
IMPRS International Max Planck Research School for Global Biogeochemical Cycles, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62545

Schrumpf,  Marion
Soil and Ecosystem Processes, Dr. M. Schrumpf, Department Biogeochemical Processes, Prof. S. E. Trumbore, Max Planck Institute for Biogeochemistry, Max Planck Society;
Soil Processes, Dr. Marion Schrumpf, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62544

Schöning,  Ingo
Soil and Ecosystem Processes, Dr. M. Schrumpf, Department Biogeochemical Processes, Prof. S. E. Trumbore, Max Planck Institute for Biogeochemistry, Max Planck Society;

External Resource

http://dx.doi.org/10.1371/journal.pone.0173765
(Publisher version)

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Fulltext (public)

BGC2608.pdf
(Publisher version), 2MB

Supplementary Material (public)

BGC2608s1.zip
(Supplementary material), 318KB

Citation

Shang, Y., Sikorski, J., Bonkowski, M., Fiore-Donno, A.-M., Kandeler, E., Marhan, S., et al. (2017). Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters. PLoS One, 12(3): e0173765. doi:10.1371/journal.pone.0173765.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002C-CCD4-E
Abstract
Interactions occur between two or more organisms affecting each other. Interactions are decisive for the ecology of the organisms. Without direct experimental evidence the analysis of interactions is difficult. Correlation analyses that are based on co-occurrences are often used to approximate interaction. Here, we present a new mathematical model to estimate the interaction strengths between taxa, based on changes in their relative abundances across environmental gradients.