Create habitat data from measures of topography.

This function constructs habitat data based on elevation data. It calculates habitats in two steps:

1. It calculates mean elevation, convexity and slope for each quadrat.

2. It calculates habitats based on hierarchical clustering of the topographic metrics from step 1.

fgeo_habitat(elev, gridsize, n, ...)

Arguments

elev	One of these: A dataframe containing elevation data, with columns gx, gy, and elev, or x, y, and elev (e.g. fgeo.x::elevation$col). A ForestGEO-like elevation list with elements xdim and ydim giving plot dimensions, and element col containing a dataframe as described in the previous item (e.g. fgeo.x::elevation).
gridsize	Number giving the size of each quadrat for which a habitat is calculated. Commonly, gridsize = 20.
n	Integer. Number of cluster-groups to construct (passed to the argument k to stats::cutree()).
...	Arguments passed to fgeo_topography().

Value

A dataframe of subclass fgeo_habitat, with columns gx and gy, rounded with accuracy determined by gridsize, and column habitats, with as many distinct integer values as determined by the argument n.

See also

fgeo.plot::autoplot.fgeo_habitat(), fgeo_topography().

Other habitat functions: fgeo_topography(), tt_test()

Other functions to construct fgeo classes: fgeo_topography()

Author

Richard Condit.

Examples

assert_is_installed("fgeo.x")

# Input a ForestGEO-like elevation list or dataframe
elevation_ls <- fgeo.x::elevation
habitats <- fgeo_habitat(
  elevation_ls,
  gridsize = 20, n = 4
)

str(habitats)
#> tibble [400 × 3] (S3: fgeo_habitat/fgeo_topography/tbl_df/tbl/data.frame)
#>  $ gx      : num [1:400] 0 0 0 0 0 0 0 0 0 0 ...
#>  $ gy      : num [1:400] 0 20 40 60 80 100 120 140 160 180 ...
#>  $ habitats: int [1:400] 1 1 1 1 1 1 1 1 1 1 ...

# Habitat data is useful for calculating species-habitat associations
census <- fgeo.x::tree6_3species
as_tibble(
  tt_test(census, habitats)
)
#> Using `plotdim = c(320, 500)`. To change this value see `?tt_test()`.
#> Using `gridsize = 20`. To change this value see `?tt_test()`.
#> # A tibble: 12 x 8
#>    habitat sp     N.Hab Gr.Hab Ls.Hab Eq.Hab Rep.Agg.Neut Obs.Quantile
#>  * <chr>   <chr>  <dbl>  <dbl>  <dbl>  <dbl>        <dbl>        <dbl>
#>  1 1       CASARB    29   1242    356      2            0        0.776
#>  2 2       CASARB    20    390   1206      4            0        0.244
#>  3 3       CASARB    12    778    817      5            0        0.486
#>  4 4       CASARB     5    932    658     10            0        0.582
#>  5 1       PREMON    91   1093    504      3            0        0.683
#>  6 2       PREMON    89   1254    344      2            0        0.784
#>  7 3       PREMON    40    305   1292      3            0        0.191
#>  8 4       PREMON    14    270   1322      8            0        0.169
#>  9 1       SLOBER    18    273   1324      3            0        0.171
#> 10 2       SLOBER    24    810    788      2            0        0.506
#> 11 3       SLOBER    17   1155    440      5            0        0.722
#> 12 4       SLOBER     7   1292    303      5            0        0.808