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Variation partitioning

Source: R/community-tests.R
ord_varpart.Rd

Partitions the variation in community composition among two to four groups of explanatory variables with adjusted \(R^2\) (Borcard et al. 1992; Peres-Neto et al. 2006), using vegan::varpart(). Fractions that are testable (the unique fraction of each group) are tested by permutation with partial RDA.

Usage

ord_varpart(
  data,
  ...,
  site = site,
  species = species,
  abundance = NULL,
  env = NULL,
  transform = "hellinger",
  permutations = 999
)

Arguments

data

A data frame in long format, with one row per record.

...

Two to four one-sided formulas of site variables, named by group, e.g. climate = ~ elevation, time = ~ season.

site, species

<tidy-select> The column holding site identifiers and the column holding species names.

abundance

<tidy-select> The column holding counts. If NULL (the default), a column called abundance is used when present, otherwise every row counts as one individual.

env

A data frame of site variables with a column named like the site column. By default, site variables are taken from data: every column that is constant within each site.

transform

Transformation before RDA; Hellinger by default.

permutations

Number of permutations for the tests of passive variables.

Value

A tibble of fractions with columns fraction, label (e.g. "[a] climate only"), adj_r2, testable and p.value.

References

Borcard, D., Legendre, P. and Drapeau, P. (1992). Partialling out the spatial component of ecological variation. Ecology, 73, 1045-1055. doi:10.2307/1940179

Peres-Neto, P. R. et al. (2006). Variation partitioning of species data matrices: estimation and comparison of fractions. Ecology, 87, 2614-2625. doi:10.1890/0012-9658(2006)87[2614:VPOSDM]2.0.CO;2

Examples

ants <- dplyr::mutate(png_ants, unit = paste(site, season, transect))
set.seed(1)
ord_varpart(ants, site = unit,
            elevation = ~elevation, season = ~season,
            permutations = 199)
#> # A tibble: 4 x 5
#>   fraction        label                       adj_r2 testable p.value
#>   <chr>           <chr>                        <dbl> <lgl>      <dbl>
#> 1 [a] = X1|X2     elevation only             0.107   TRUE       0.005
#> 2 [b] = X2|X1     season only                0.0127  TRUE       0.175
#> 3 [c]             shared elevation & season -0.00631 FALSE     NA    
#> 4 [d] = Residuals residual                   0.886   FALSE     NA