Coefficient of variation, mean, minimum and standard deviation of the nearest neigbourhood distance.

Description

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

Usage

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	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)

Arguments

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.

Value

One value corresponding to the metric value.

Author(s)

Adrien Taudiere

References

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.

Examples

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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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