Do modern theories of biodiversity fail to predict commonness and rarity among microbes?
- Published
- Accepted
- Subject Areas
- Biodiversity, Ecology, Microbiology
- Keywords
- biodiversity, macroecology, microbial ecology, maxent, zipf, broken-stick, earth microbiome project, human microbiome project, species abundance distribution, mg-rast
- Copyright
- © 2015 Shoemaker et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Do modern theories of biodiversity fail to predict commonness and rarity among microbes? PeerJ PrePrints 3:e1450v1 https://doi.org/10.7287/peerj.preprints.1450v1
Abstract
Ecological theories of biodiversity seek to predict and unify patterns of commonness and rarity across taxa. The maximum entropy theory of ecology (METE) is among the most unifying theories of biodiversity, explaining >90% of variation in abundance among species of plant animal using the total number of individuals (N0) and number of species as empirical inputs. However, METE has not been tested among the most abundant and diverse organisms on Earth, i.e., microorganisms. Using ~20,000 sites of microbial communities, we show that METE often explains <10% of variation in abundance and increasingly fails for larger N0. In contrast, a more uneven distribution with a maximum entropy solution, the Zipf, often explains >90% of variation among microbes and performs better as N0 increases. Our findings suggest that theories of biodiversity could produce accurate predictions across the tree of life and scales of abundance if they capture how disparities in abundance increase with N0.
Author Comment
We show that the maximum entropy theory of ecology (METE) often explains <10% of variation in abundance among microbial taxa and increasingly fails for larger N0. Our findings suggest that theories of biodiversity could produce accurate predictions across the tree of life and scales of abundance if they capture how disparities in abundance increase with N0. We plan to submit to a peer-reviewed journal. This work is not part of a conference proceeding.