Description Usage Arguments Value Author(s) References Examples

View source: R/allfunctions_cati.R

CVNND : Coefficient of variation of the nearest neigbourhood distance

MNND : Mean of the nearest neigbourhood distance

MinNND : Minimum of the nearest neigbourhood distance

SDNND : Standard deviation of the nearest neigbourhood distance

SDND : Standard deviation of the neigbourhood distance

MND : Mean of the neigbourhood distance

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
CVNND(traits, div_range = FALSE, na.rm = FALSE, scale.tr = TRUE,
method.dist = "euclidian")
MNND(traits, div_range = FALSE, na.rm = FALSE, scale.tr = TRUE,
method.dist = "euclidian")
MinNND(traits, div_range = FALSE, na.rm = FALSE, scale.tr = TRUE,
method.dist = "euclidian")
SDNND(traits, div_range = FALSE, na.rm = FALSE, scale.tr = TRUE,
method.dist = "euclidian")
SDND(trait, div_range = FALSE, na.rm = FALSE)
MND(trait, div_range = FALSE, na.rm = FALSE)
``` |

`traits` |
Trait vector (uni-trait metric) or traits matrix (Multi-traits metric), traits in column. |

`trait` |
Trait vector |

`div_range` |
Does metric need to be divided by the range? Default is no. |

`na.rm` |
If div_range=TRUE, a logical value indicating whether NA values should be stripped before the computation proceeds. |

`scale.tr` |
Does traits need to be scale before multi-traits metric calculation? Default is yes. |

`method.dist` |
Method to calculate the distance in case of multi-traits metric (function dist). Default is euclidian. |

One value corresponding to the metric value.

Adrien Taudiere

Aiba, M., Katabuchi, M., Takafumi, H., Matsuzaki, S.S., Sasaki, T. & Hiura, T. 2013. Robustness of trait distribution metrics for community assembly studies under the uncertainties of assembly processes. Ecology, 94, 2873-2885. Jung, Vincent, Cyrille Violle, Cedric Mondy, Lucien Hoffmann, et Serge Muller. 2010. Intraspecific variability and trait-based community assembly: Intraspecific variability and community assembly. Journal of Ecology 98 (5): 1134-1140.

1 2 3 4 5 6 7 | ```
data(finch.ind)
CVNND(traits.finch[,1], na.rm = TRUE)
CVNND(traits.finch[,1], div_range = TRUE, na.rm = TRUE)
CVNND(traits.finch, na.rm = TRUE)
CVNND(traits.finch, scale.tr = FALSE, na.rm = TRUE)
SDND(traits.finch[,1], na.rm = TRUE)
``` |

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