taxondive {vegan} | R Documentation |

Function finds indices of taxonomic diversity and distinctness, which are averaged taxonomic distances among species or individuals in the community (Clarke & Warwick 1998, 2001)

taxondive(comm, dis, match.force = FALSE) taxa2dist(x, varstep = FALSE, check = TRUE, labels)

`comm` |
Community data. |

`dis` |
Taxonomic distances among taxa in `comm` . This should
be a `dist` object or a symmetric square matrix. |

`match.force` |
Force matching of column names in `comm` and
labels in `dis` . If `FALSE` , matching only happens when
dimensions differ, and in that case the species must be in identical
order in both. |

`x` |
Classification table with a row for each species or other basic taxon, and columns for identifiers of its classification at higher levels. |

`varstep` |
Vary step lengths between successive levels relative to proportional loss of the number of distinct classes. |

`check` |
If `TRUE` , remove all redundant levels which are
different for all rows or constant for all rows and regard each row
as a different basal taxon (species). If `FALSE` all
levels are retained and basal taxa (species) also must be coded as
variables (columns). You will get a warning if species are not
coded, but you can ignore this if that was your intention. |

`labels` |
The `labels` attribute of taxonomic distances. Row
names will be used if this is not given. Species will be matched by
these labels in `comm` and `dis` in `taxondive` if
these have different dimensions. |

Clarke & Warwick (1998, 2001) suggested several alternative indices of
taxonomic diversity or distinctness. Two basic indices are called
taxonomic diversity (*Delta*) and distinctness (*Delta^**):

Delta = (sum sum_{i<j} omega_{ij} x_i x_j)/(n (n-1) / 2) |

Delta^* = (sum sum_{i<j} omega_{ij} x_i x_j)/(sum sum_{i<j} x_i x_j) |

The equations give the index value for a single site, and summation
goes over species *i* and *j*. Here *omega* are taxonomic
distances among taxa, and *x* are species abundances, and *n*
is the total abundance for a site.
With presence/absence data both indices reduce to the same index
*Delta^+*, and for this index Clarke & Warwick (1998) also have
an estimate of its standard deviation. Clarke & Warwick (2001)
presented two new indices: *sDelta^+* is the product of species
richness and *Delta^+*, and index of variation in
taxonomic distinctness (*Lambda^+*) defined as

Lambda^+ = (sum sum_{i<j} omega_{ij}^2)/(n (n-1) / 2) - (Delta^+)^2 |

The `dis`

argument must be species dissimilarities. These must be
similar to dissimilarities produced by `dist`

. It is
customary to have integer steps of taxonomic hierarchies, but other
kind of dissimilarities can be used, such as those from phylogenetic
trees or genetic differences. Further, the `dis`

need not be
taxonomic, but other species classifications can be used.

Function `taxa2dist`

can produce a suitable `dist`

object
from a classification table. Each species (or basic taxon) corresponds
to a row of the classification table, and columns give the
classification at different levels. With `varstep = FALSE`

the
successive levels will be separated by equal steps, and with
`varstep = TRUE`

the step length is relative to the proportional
decrease in the number of classes (Clarke & Warwick 1999).
With `check = TRUE`

, the function removes classes which are distinct for all
species or which combine all species into one class, and assumes that
each row presents a distinct basic taxon. The function scales
the distances so that longest path length between
taxa is 100 (not necessarily when `check = FALSE`

).

Function `plot.taxondive`

plots *Delta^+* against Number of
species, together with expectation and its approximate 2*sd
limits. Function `summary.taxondive`

finds the *z* values and
their significances from Normal distribution for *Delta^+*.

Function returns an object of class `taxondive`

with following items:

`Species ` |
Number of species for each site. |

`D, Dstar, Dplus, SDplus, Lambda` |
Delta, Delta^*,
Delta^+, sDelta^+ and Lambda^+
for each site. |

`sd.Dplus` |
Standard deviation of Delta^+. |

`ED, EDstar, EDplus` |
Expected values of corresponding statistics. |

Function `taxa2dist`

returns an object of class `"dist"`

, with
an attribute `"steps"`

for the step lengths between successive levels.

The function is still preliminary and may change. The scaling of
taxonomic dissimilarities influences the results. If you multiply
taxonomic distances (or step lengths) by a constant, the values of all
Deltas will be multiplied with the same constant, and the value of
*Lambda^+* by the square of the constant.

Jari Oksanen

Clarke, K.R & Warwick, R.M. (1998) A taxonomic distinctness index and
its statistical properties. *Journal of Applied Ecology* 35,
523–531.

Clarke, K.R. & Warwick, R.M. (1999) The taxonomic distinctness measure
of biodiversity: weighting of step lengths between hierarchical
levels. *Marine Ecology Progress Series* 184: 21–29.

Clarke, K.R. & Warwick, R.M. (2001) A further biodiversity index
applicable to species lists: variation in taxonomic
distinctness. *Marine Ecology Progress Series* 216, 265–278.

## Preliminary: needs better data and some support functions data(dune) data(dune.taxon) # Taxonomic distances from a classification table with variable step lengths. taxdis <- taxa2dist(dune.taxon, varstep=TRUE) plot(hclust(taxdis), hang = -1) # Indices mod <- taxondive(dune, taxdis) mod summary(mod) plot(mod)

[Package *vegan* version 1.16-32 Index]