taxondive: Indices of Taxonomic Diversity and Distinctness

In vegan: Community Ecology Package

Description

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

Usage

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

Arguments

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.

Details

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

Δ = (∑ ∑_{i<j} ω_{ij} x_i x_j)/(n (n-1) / 2)

Δ^* = (∑ ∑_{i<j} ω_{ij} x_i x_j)/(∑ ∑_{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 ω 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 Δ^+, and for this index Clarke & Warwick (1998) also have an estimate of its standard deviation. Clarke & Warwick (2001) presented two new indices: sΔ^+ is the product of species richness and Δ^+, and index of variation in taxonomic distinctness (Λ^+) defined as

Λ^+ = (∑ ∑_{i<j} ω_{ij}^2)/(n (n-1) / 2) - (Δ^+)^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 Δ^+ 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 Δ^+.

Value

Function returns an object of class taxondive with following items:

Species	Number of species for each site.
D, Dstar, Dplus, SDplus, Lambda	Δ, Δ^*, Δ^+, sΔ^+ and Λ^+ for each site.
sd.Dplus	Standard deviation of Δ^+.
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.

Note

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 Λ^+ by the square of the constant.

Author(s)

Jari Oksanen

References

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.

See Also

diversity.

Examples

## 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)

Example output

Loading required package: permute
Loading required package: lattice
This is vegan 2.4-3
          Species    Delta   Delta*  Lambda+   Delta+ S Delta+
1           5.000   22.736   29.232  900.298   43.364   216.82
2          10.000   51.046   55.988  822.191   56.232   562.32
3          10.000   41.633   46.194 1025.471   62.869   628.69
4          13.000   50.795   55.140  888.244   64.837   842.88
5          14.000   63.498   67.856  715.393   69.211   968.95
6          11.000   70.201   76.361  628.743   73.281   806.09
7          13.000   61.605   66.187  679.337   69.918   908.94
8          12.000   52.544   56.374  756.375   66.729   800.74
9          13.000   50.526   54.108  849.448   63.205   821.67
10         12.000   60.068   64.960  730.736   69.291   831.49
11          9.000   69.589   77.740  404.609   77.803   700.23
12          9.000   62.405   69.795  552.129   74.470   670.23
13         10.000   47.316   53.842  536.429   66.657   666.57
14          7.000   71.383   82.091  239.543   82.013   574.09
15          8.000   68.564   77.097  334.889   79.010   632.08
16          8.000   55.984   64.400  978.014   69.708   557.66
17          7.000   53.913   60.222  632.990   59.286   415.00
18          9.000   73.235   81.865  438.355   76.288   686.59
19          9.000   68.727   76.091  336.364   78.636   707.73
20          8.000   72.343   80.670  444.915   82.078   656.62
Expected            65.330   62.560            71.031         
           Delta  Delta*  Delta+ sd(Delta+) z(Delta+) Pr(>|z|)   
1        22.7362 29.2322 43.3636    10.0499   -2.7530 0.005905 **
2        51.0458 55.9878 56.2323     5.7727   -2.5636 0.010359 * 
3        41.6334 46.1936 62.8687     5.7727   -1.4140 0.157360   
4        50.7952 55.1396 64.8368     4.5677   -1.3562 0.175047   
5        63.4979 67.8564 69.2108     4.2482   -0.4285 0.668251   
6        70.2011 76.3614 73.2810     5.3189    0.4229 0.672332   
7        61.6049 66.1871 69.9184     4.5677   -0.2437 0.807499   
8        52.5437 56.3743 66.7287     4.9215   -0.8743 0.381975   
9        50.5258 54.1079 63.2051     4.5677   -1.7134 0.086640 . 
10       60.0680 64.9597 69.2906     4.9215   -0.3537 0.723567   
11       69.5894 77.7396 77.8030     6.3011    1.0747 0.282517   
12       62.4049 69.7949 74.4697     6.3011    0.5457 0.585290   
13       47.3158 53.8421 66.6566     5.7727   -0.7578 0.448548   
14       71.3834 82.0909 82.0130     7.7069    1.4249 0.154186   
15       68.5645 77.0970 79.0097     6.9314    1.1510 0.249714   
16       55.9840 64.3999 69.7078     6.9314   -0.1909 0.848565   
17       53.9134 60.2224 59.2857     7.7069   -1.5240 0.127501   
18       73.2349 81.8645 76.2879     6.3011    0.8342 0.404155   
19       68.7273 76.0909 78.6364     6.3011    1.2069 0.227457   
20       72.3431 80.6704 82.0779     6.9314    1.5937 0.111005   
Expected 65.3302 62.5603 71.0313                                 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

vegan documentation built on May 2, 2019, 5:51 p.m.