Description Usage Arguments Details Value Examples

Wraper function to perform ecological gradient analysis

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`data` |
A dataframe containing species as columns and sites as rows. May also contain environmental parameters, as long as the parameters are as columns and the site as rows. |

`dist` |
A vector or column containing the gradient along which the analysis will be done. Must be of the same lenght as data. |

`method` |
One of c("dca", "fanny", "vegclust", "diversity", "cmeans", "all"). Tell the function which analysis to perform. See details. |

`groups` |
Interger. The desired number of clusters if any of the clustering method is selected. |

`m.exp` |
Integer. The membership exponent for any of the clustering method. |

`standardize` |
Standardize method to apply to the data before further analysis (for fanny and cmeans). Must be one of decostand methods (see decostand). |

`seed` |
Integer or NULL. Set a seed for initial membership matrix for cmeans and vegclust algorithms. Recomended for time series, to keep a more consistent labelling of fuzzy clusters along the gradient. See Details. |

`diversity` |
diversity indice to be calculated. See details. |

`na.rm` |
Logical. Should NAs be removed. |

EcotoneFinder is a wraper function to perform multiple ecological
gradient analysis at once. The implemented methods are Detrended
Correspondance Analysis (DCA) - see Brownstein et al. 2013 - Fuzzy C-Means
(FCM) - see DeCaceres et al., 2010 - and the calculation of diversity
indices - see Jost, 2007. The DCA is intenally performed by the decorana
function of the vegan package. The FCM analyses can be performed by the
fanny function (cluster package), the vegclust function (vegclust package)
and the cmeans function (e1071 package) - for comparison purposes as the
outcome of the analyses might differ.
The vegclust and cmeans algorithms use random number generators to create
a matrix of initial centers. Setting a seed with the *seed* argument
guaranty the reproducibility of the outputs. This argument can also be set
to NULL, to preserve the randomness of initial centres.

It is recommended to stadardize data before applying fanny or cmeans analysis. See decostand documentation (vegan package) for information on standardisation methods. Must be one of: "total","max","freq","normalize","range","pa","chi.square","hellinger","log". If "log" is chosen, the user will be asked to provide the base to be used upon launching the function.

Several diversity incides have been implemented, as they are supposed to react to ecological gradients. It includes the Shannon index, the Pielou eveness and species richness - computed with the diversity function of the vegan package. expShannon corresponds to the shannon index in terms of effective number of species (see Jost, 2007). If "all" is selected, all the implemented indices will be calculated.

If "all" is selected in the method argument, all the implemented methods will be applied.

Ecofinder returns a list containing the original data, the value of the main arguments used in the function and the outcome of the selected analyses.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
#### Artificial dataset:
SyntheticTrial <- SyntheticData(SpeciesNum = 21, CommunityNum = 3,
SpCo = NULL, Length = 500,
Parameters = list(a=rep(60, 3),
b=c(0,250,500),
c=rep(0.015,3)),
pal = c("#008585", "#FBF2C4", "#C7522B"))
## Analyses:
SyntheticEcoFinder <- EcotoneFinder(data = SyntheticTrial[,-1],
dist = SyntheticTrial$Distance,
method = "all",
groups = 3, standardize = "hellinger",
diversity = "all")
``` |

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