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No silver bullet: different soil handling techniques are useful for different research questions, exhibit differential type I and II error rates, and are sensitive to sampling intensity
Author(s) -
Cahill James F.,
Cale Jonathan A.,
Karst Justine,
Bao Tan,
Pec Gregory J.,
Erbilgin Nadir
Publication year - 2017
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.14141
Subject(s) - pooling , type i and type ii errors , biota , soil water , sampling (signal processing) , sample (material) , soil type , ecology , environmental science , sample size determination , statistics , soil science , computer science , mathematics , biology , chemistry , artificial intelligence , filter (signal processing) , computer vision , chromatography
The black box of soils has opened over the last decade, revealing critical microbe effects on plant growth, nutrient cycling, and community dynamics (Kardol et al., 2007; Hoeksema et al., 2010; Reinhart, 2012; Hodge & Fitter, 2013). In a recent issue of New Phytologist, Reinhart & Rinella (2016) highlight the importance of soil handling in experimental studies, and address the statistical implications of mixing soil samples from multiple experimental units (MSS) vs maintaining individual soil samples (ISS; Fig. 1 in Reinhart & Rinella, 2016). They use logical arguments and the results of a numerical simulation to support two statements: