bgdispersal {vegan} | R Documentation |

This function computes coefficients of dispersal direction between geographically connected areas, as defined by Legendre and Legendre (1984), and also described in Legendre and Legendre (1998, section 13.3.4).

bgdispersal(mat, PAonly = FALSE, abc = FALSE)

`mat` |
Data frame or matrix containing a community composition data table (species presence-absence or abundance data). |

`PAonly` |
`FALSE` if the four types of coefficients, DD1 to
DD4, are requested; `TRUE` if `DD1` and `DD2` only are
sought (see Details). |

`abc` |
If `TRUE` , return tables `a` , `b` and `c`
used in `DD1` and `DD2` . |

The signs of the DD coefficients indicate the direction of dispersal, provided that the asymmetry is significant. A positive sign indicates dispersal from the first (row in DD tables) to the second region (column); a negative sign indicates the opposite. A McNemar test of asymmetry is computed from the presence-absence data to test the hypothesis of a significant asymmetry between the two areas under comparison.

In the input data table, the rows are sites or
areas, the columns are taxa. Most often, the taxa
are species, but the coefficients can be computed
from genera or families as well. DD1 and DD2 only
are computed for presence-absence data. The four
types of coefficients are computed for
quantitative data, which are converted to
presence-absence for the computation of DD1 and
DD2. `PAonly = FALSE`

indicates that the four types
of coefficients are requested. `PAonly = TRUE`

if DD1
and DD2 only are sought.

Function `bgdispersal`

returns a list containing the following matrices:

` DD1 ` |
DD1[j,k] = (a * (b - c))/((a + b + c)^2) |

` DD2 ` |
DD2[j,k] = (2*a * (b - c))/((2*a + b + c) * (a + b +
c))
where a, b, and c have the
same meaning as in the computation of binary
similarity coefficients. |

` DD3 ` |
DD3[j,k] = W*(A-B) / ((A+B-W)^2) |

` DD4 ` |
DD4[j,k] = 2*W*(A-B) / ((A+B)*(A+B-W))
where `W = sum(pmin(vector1, vector2))` , `A = sum(vector1)` ,
`B = sum(vector2)` |

` McNemar ` |
McNemar chi-square statistic of asymmetry (Sokal and
Rohlf 1995): 2*(b*log(b) + c*log(c) - (b+c)*log((b+c)/2)) / q
where q = 1 + 1/(2*(b+c)) (Williams correction for continuity) |

` prob.McNemar ` |
probabilities associated
with McNemar statistics, chi-square test. H0: no
asymmetry in (b-c). |

The function uses a more powerful alternative for the McNemar test
than the classical formula. The classical formula was constructed in
the spirit of Pearson's Chi-square, but the formula in this function
was constructed in the spirit of Wilks Chi-square or the *G*
statistic. Function `mcnemar.test`

uses the classical
formula. The new formula was introduced in vegan version
1.10-11, and the older implementations of `bgdispersal`

used the
classical formula.

Pierre Legendre, Departement de Sciences Biologiques, Universite de Montreal

Legendre, P. and V. Legendre. 1984. Postglacial dispersal of
freshwater fishes in the Québec
peninsula. *Can. J. Fish. Aquat. Sci.* **41**: 1781-1802.

Legendre, P. and L. Legendre. 1998. *Numerical ecology*, 2nd
English edition. Elsevier Science BV, Amsterdam.

Sokal, R. R. and F. J. Rohlf. 1995. *Biometry. The principles and
practice of statistics in biological research.* 3rd
edn. W. H. Freeman, New York.

mat <- matrix(c(32,15,14,10,70,30,100,4,10,30,25,0,18,0,40, 0,0,20,0,0,0,0,4,0,30,20,0,0,0,0,25,74,42,1,45,89,5,16,16,20), 4, 10, byrow=TRUE) bgdispersal(mat)

[Package *vegan* version 1.16-32 Index]