estimateEvenness {mia} | R Documentation

## Estimate Evenness measures

### Description

This function calculates community evenness indices. These include the ‘Camargo’, ‘Pielou’, ‘Simpson’, ‘Evar’ and ‘Bulla’ evenness measures. See details for more information and references.

### Usage

    estimateEvenness(
      x,
      abund_values = "counts",
      index = c("pielou", "camargo", "simpson_evenness", "evar", "bulla"),
      name = index,
      ...
    )

    ## S4 method for signature 'SummarizedExperiment'
    estimateEvenness(
      x,
      abund_values = "counts",
      index = c("camargo", "pielou", "simpson_evenness", "evar", "bulla"),
      name = index,
      ...,
      BPPARAM = SerialParam()
    )

### Arguments

`x` | a `SummarizedExperiment` object
`abund_values` | A single character value for selecting the `assay` used for calculation of the sample-wise estimates.
`index` | a `character` vector, specifying the eveness measures to be calculated.
`name` | a name for the column(s) of the colData the results should be stored in.
`...` | optional arguments: threshold a numeric threshold. assay values below or equal to this threshold will be set to zero.
`BPPARAM` | A `BiocParallelParam` object specifying whether calculation of estimates should be parallelized.

### Details

Evenness is a standard index in community ecology, and it quantifies how evenly the abundances of different species are distributed. The following evenness indices are provided:

By default, this function returns all indices.

The available evenness indices include the following (all in lowercase):

- 'camargo' Camargo's evenness (Camargo 1992)

- 'simpson_evenness' Simpson’s evenness is calculated as inverse Simpson diversity (1/lambda) divided by observed species richness S: (1/lambda)/S.

- 'pielou' Pielou's evenness (Pielou, 1966), also known as Shannon or Shannon-Weaver/Wiener/Weiner evenness; H/ln(S). The Shannon-Weaver is the preferred term; see Spellerberg and Fedor (2003).

- 'evar' Smith and Wilson’s Evar index (Smith & Wilson 1996).

- 'bulla' Bulla’s index (O) (Bulla 1994).

Desirable statistical evenness metrics avoid strong bias towards very large or very small abundances; are independent of richness; and range within the unit interval with increasing evenness (Smith & Wilson 1996). Evenness metrics that fulfill these criteria include at least camargo, simpson, smith-wilson, and bulla. Also see Magurran & McGill (2011) and Beisel et al. (2003) for further details.

### Value

`x` with additional `colData` named `*name*`

### References

Beisel J-N. et al. (2003) A Comparative Analysis of Evenness Index Sensitivity. Internal Rev. Hydrobiol. 88(1):3-15. URL: https://portais.ufg.br/up/202/o/2003-comparative_evennes_index.pdf

Bulla L. (1994) An index of evenness and its associated diversity measure. Oikos 70:167–171.

Camargo, JA. (1992) New diversity index for assessing structural alterations in aquatic communities. Bull. Environ. Contam. Toxicol. 48:428–434.

Locey KJ and Lennon JT. (2016) Scaling laws predict global microbial diversity. PNAS 113(21):5970-5975; doi:10.1073/pnas.1521291113.

Magurran AE, McGill BJ, eds (2011) Biological Diversity: Frontiers in Measurement and Assessment (Oxford Univ Press, Oxford), Vol 12.

Pielou, EC. (1966) The measurement of diversity in different types of biological collections. J Theoretical Biology 13:131–144.

Smith B and Wilson JB. (1996) A Consumer's Guide to Evenness Indices. Oikos 76(1):70-82.

Spellerberg and Fedor (2003). A tribute to Claude Shannon (1916 –2001) and a plea for more rigorous use of species richness, species diversity and the ‘Shannon–Wiener’ Index. Alpha Ecology & Biogeography 12, 177–197.

### See Also

`plotColData`

- `estimateRichness`

- `estimateDominance`

- `estimateDiversity`

### Examples

    data(esophagus)
    se <- esophagus

    # Specify index and their output names
    index <- c("pielou", "camargo", "simpson_evenness", "evar", "bulla")
    name  <- c("Pielou", "Camargo", "SimpsonEvenness",  "Evar", "Bulla")

    # Estimate evenness and give polished names to be used in the output
    se <- estimateEvenness(se, index = index, name = name)

    # Check the output
    head(colData(se))

[Package mia version 1.2.7 Index]