Improved detection of changes in species richness in high diversity microbial communities
By A. Willis, John Bunge, T. Whitman. 2016
105 citations recorded by the source corpus.
Biodiversity is important for balance and function of a broad variety of ecosystems, and identifying factors that influence biodiversity can assist environmental management and maintenance. However, low abundance taxa are often missing from ecosystem surveys. These rare taxa, which may be critical to the ecosystem function, are not accounted for in existing methods for detecting changes in species richness. We introduce a model for total (observed and unobserved) biodiversity that explicitly accounts for these rare taxa. Our method permits rigorous testing for both heterogeneity and biodiversity changes, and simultaneously improves type I and II error rates compared with existing methods. To estimate model parameters we utilize the well‐developed literature of meta‐analysis. The problem of substantial low abundance taxa missing from samples is especially pronounced in microbiomes, which are the focus of our case‐studies.
Subfields: Ecology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/ed2767c37030891018ffa23e5b2356f93c126296
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In Ecology
In Molecular Biology
- Ellen Whitman
- T. Whitman
- Michael Flannigan
- Dan K. Thompson
- Marc-André Parisien
- Jamie Woolet
- Zhiyong Wang
Citations in the corpus
- Soil Bacterial and Fungal Response to Wildfires in the Canadian Boreal Forest Across a Burn Severity Gradient (2019, methodology): “We estimated richness and its associated standard error in each sample using the breakaway function in R (Willis et al., 2016).”