# Structural and compositional dissimilarity

### Description

Function to calculate the dissimilarity between ecological communities taking into account both their composition and the size of organisms.

### Usage

1 2 |

### Arguments

`x` |
A stratified vegetation data set (see function |

`y` |
A second stratified vegetation data set (see function |

`paired` |
Only relevant when |

`type` |
Whether dissimilarities between pairs of sites should be calculated from differences in cummulative abundance ( |

`method` |
The dissimilarity coefficient to calculate (see details). |

`transform` |
A function or the name of a function to be applied to each cumulative abundance value. |

`classWeights` |
A numerical vector or a matrix containing the weight of each size class or combination of size classes (see functions |

### Details

The six different coefficients available are described in De Caceres et al. (2013): (1) `method="bray"`

for percentage difference (alias Bray-Curtis dissimilarity); (2) `method="ruzicka"`

for Ruzicka index (a generalization of Jaccard); (3) `method="kulczynski"`

for the Kulczynski dissimilarity index; (4) `method="ochiai"`

for the complement of a quantitative generalization of Ochiai index of similarity; (5) `method="canberra"`

for the Canberra index (Adkins form); (6) `method="relman"`

for the relativized Manhattan coefficient (Whittaker's index of association). Currently, the function also supports (7) `method="manhattan"`

for the city block metric.

### Value

Returns an object of class '`dist`

'.

### Author(s)

Miquel De Cáceres, Forest Science Center of Catalonia.

### References

De Cáceres, M., Legendre, P. & He, F. (2013) Dissimilarity measurements and the size structure of ecological communities. Methods in Ecology and Evolution 4: 1167-1177.

### See Also

`stratifyvegdata`

, `vegdist`

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
## Load stratified data
data(medreg)
## Check that 'medreg' has correct class
class(medreg)
## Create cumulative abundance profile (CAP) for each plot
medreg.CAP = CAP(medreg)
## Create dissimilarity (percentage difference) matrix using profiles
medreg.D = vegdiststruct(medreg, method="bray")
## Create dissimilarity (percentage difference) matrix using abundances
medreg.D2 = vegdiststruct(medreg, method="bray", type="total")
## Calculate correlation
cor(as.vector(medreg.D), as.vector(medreg.D2))
``` |