Inventory, differentiation, and proportional diversity: a consistent terminology for quantifying species diversity

Jurasinski, Gerald; Retzer, Vroni; Beierkuhnlein, Carl

doi:10.1007/s00442-008-1190-z

Cited by 200 publications

(205 citation statements)

References 108 publications

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“…To directly compare the α-diversity [within-sample diversity or estimate of species richness (19)] of the samples with differing sequence counts/sampling efforts, we rarefied the data (i.e., randomly picked an equal number of sequence across samples) using QIIME (Quantitative Insights into Microbial Ecology) (20). Rarefaction curves, which show the observed operational taxonomic unit (OTU) richness as a function of pyrosequencing effort, indicated that the sequencing depth was insufficient to wholly capture the diversity present (Fig.…”

Section: S Rrna Gene Sequence Region Impacts Recovered Maize Rhizosmentioning

confidence: 99%

Diversity and heritability of the maize rhizosphere microbiome under field conditions

Peiffer

Spor

Koren

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

1,566

124

1,072

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The rhizosphere is a critical interface supporting the exchange of resources between plants and their associated soil environment. Rhizosphere microbial diversity is influenced by the physical and chemical properties of the rhizosphere, some of which are determined by the genetics of the host plant. However, within a plant species, the impact of genetic variation on the composition of the microbiota is poorly understood. Here, we characterized the rhizosphere bacterial diversity of 27 modern maize inbreds possessing exceptional genetic diversity grown under field conditions. Randomized and replicated plots of the inbreds were planted in five field environments in three states, each with unique soils and management conditions. Using pyrosequencing of bacterial 16S rRNA genes, we observed substantial variation in bacterial richness, diversity, and relative abundances of taxa between bulk soil and the maize rhizosphere, as well as between fields. The rhizospheres from maize inbreds exhibited both a small but significant proportion of heritable variation in total bacterial diversity across fields, and substantially more heritable variation between replicates of the inbreds within each field. The results of this study should facilitate expanded studies to identify robust heritable plant-microbe interactions at the level of individual polymorphisms by genome wide association, so that plant-microbiome interactions can ultimately be incorporated into plant breeding.

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Section: S Rrna Gene Sequence Region Impacts Recovered Maize Rhizosmentioning

confidence: 99%

Diversity and heritability of the maize rhizosphere microbiome under field conditions

Peiffer

Spor

Koren

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

1,566

124

1,072

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“…b-diversity can be a useful metric when trying to understand patterns of species diversity across spatial scales (e.g., Veech et al 2002, Crist and Veech 2006, Jost 2007, Tuomisto 2010a, b, Anderson et al 2011, and for example, can allow inference about the relative importance of community assembly processes such as those that are more deterministic (niche-related) relative to those that are more stochastic (e.g., Condit et al 2002, Tuomisto et al 2003, Gilbert and Lechowicz 2004, Dornelas et al 2006, Chase 2007. Unfortunately, a large number of the metrics and statistical analyses used to estimate b-diversity are confounded, are not always directly comparable, and may not produce conceptually meaningful values (Jost 2007, Jurasinski et al 2009, Tuomisto 2010a, b, Anderson et al 2011. For example, one of the biggest problems associated with analyses of b-diversity is that using either a multiplicative (c ¼ a 3 b) or additive (c ¼ a þ b) partition, b-diversity is linked to variation in c and a by definition, thus making statistical comparisons of b-diversity among sites or regions confounded by coincident variation in a or c (e.g., Wilson and Shmida 1984, Lande 1996, Koleff et al 2003, Jost 2007, Tuomisto 2010a.…”

Section: Introductionmentioning

confidence: 99%

Using null models to disentangle variation in community dissimilarity from variation in α-diversity

Chase

Kraft

Smith³

et al. 2011

Ecosphere

801

950

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Abstract. b-diversity represents the compositional variation among communities from site-to-site, linking local (a-diversity) and regional (c-diversity). Researchers often desire to compare values of bdiversity across localities or experimental treatments, and to use this comparison to infer possible mechanisms of community assembly. However, the majority of metrics used to estimate b-diversity, including most dissimilarity metrics (e.g., Jaccard's and Sørenson's dissimilarity index), can vary simply because of changes in the other two diversity components (a or c-diversity). Here, we overview the utility of taking a null model approach that allows one to discern whether variation in the measured dissimilarity among communities results more from changes in the underlying structure by which communities vary, or instead simply due to difference in a-diversity among localities or experimental treatments. We illustrate one particular approach, originally developed by Raup and Crick (1979) in the paleontological literature, which creates a re-scaled probability metric ranging from À1 to 1, indicating whether local communities are more dissimilar (approaching 1), as dissimilar (approaching 0), or less dissimilar (approaching À1), than expected by random chance. The value of this metric provides some indication of the possible underlying mechanisms of community assembly, in particular the degree to which deterministic processes create communities that deviate from those based on stochastic (null) expectations. We demonstrate the utility of this metric when compared to analyses of Jaccard's dissimilarity index with case studies from disparate empirical systems (coral reefs and freshwater ponds) that differ in the degree to which disturbance altered a-diversity, as well as the selectivity by which disturbance acted on members of the community.

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“…gamma/alpha; Lande, 1996;Veech et al, 2002;Jost, 2007). Recently, Jurasinski et al (2009) have named these measures 'differentiation diversity' and 'proportional diversity', respectively. The overwhelming majority of beta diversity functions from both groups apply to presence-absence data (Vellend, 2001;Koleff et al, 2003;Tuomisto, 2010a, b), including the well-known Jaccard similarity index adapted by Whittaker (1960, p. 320) to this purpose.…”

Section: Introductionmentioning

confidence: 99%

A general framework for analyzing beta diversity, nestedness and related community-level phenomena based on abundance data

Podani

Ricotta

Schmera

2013

Ecological Complexity

133

136

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We describe a procedure for evaluating the relative importance of beta diversity, nestedness, and similarity properties of ecological data matrices containing density, cover or biomass scores of species. Our goals are achieved by extension of the simplex approach-originally proposed for presence-absence data-to abundances.Basically, the method involves decomposition of the Marczewski-Steinhaus coefficient of dissimilarity between pairs of sites into two fractions, one derived from differences between total abundance and the other from differences due to abundance replacement. These are contrasted by the similarity function counterpart, known as the Ruzicka coefficient, and are displayed graphically using ternary (or 2D simplex) plots.Interpretation is aided by calculating percentage contributions from these components to the (dis)similarity structure. Measures of replacement and nestedness are new for 2 abundance data; these are considered complementary phenomena reflecting antithetic ecological processes that are analogous to those operating at the presence-absence level. The method is illustrated by artificial data and a range of actual ecological data sets representing different groups of organisms, different scales and different types of data. While the simplex diagrams and associated coefficients are meaningful by themselves, their comparison with presence-absence based results gives additional insight into data structure and background factors.

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Inventory, differentiation, and proportional diversity: a consistent terminology for quantifying species diversity

Abstract: Almost half a century after Whittaker (Ecol

Cited by 200 publications

References 108 publications

Diversity and heritability of the maize rhizosphere microbiome under field conditions

Diversity and heritability of the maize rhizosphere microbiome under field conditions

Using null models to disentangle variation in community dissimilarity from variation in α-diversity

A general framework for analyzing beta diversity, nestedness and related community-level phenomena based on abundance data

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