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Improved detection of changes in species richness in high diversity microbial communities
Author(s) -
Willis Amy,
Bunge John,
Whitman Thea
Publication year - 2017
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/rssc.12206
Subject(s) - biodiversity , species richness , abundance (ecology) , taxon , ecosystem , relative species abundance , ecology , global biodiversity , species diversity , geography , environmental resource management , biology , environmental science
Summary 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.