filter_na_empty

internal

This analytical framework is based on an analysis of the shape of the trait abundance distributions to better understand community assembly processes, and predict community dynamics under environmental changes. This framework mobilized a study of the relationship between the moments describing the shape of the distributions: the skewness and the kurtosis (SKR). The SKR allows the identification of commonalities in the shape of trait distributions across contrasting communities. Derived from the SKR, we developed mathematical parameters that summarise the complex pattern of distributions by assessing (i) the R², (ii) the Y-intercept, (iii) the slope, (iv) the functional stability of community (TADstab), and, (v) the distance from specific distribution families (i.e., the distance from the skew-uniform family a limit to the highest degree of evenness: TADeve).

Lain Pavot

Realize the Trait Abundance Distribution

Nathan Rondeau

Yoann Le Bagousse-Pinguet

Raphael Martin

Pierre Liancourt

Nicolas Gross

INRAe/UREP 

filter_na_empty function

<dl><dt>weights</dt>
<dd>the dataframe of weights, one row correspond to a
series of observation</dd>
<dt>weights_factor</dt>
<dd>the dataframe which contains the different
factor linked to the weights</dd>
<dt>trait_data</dt>
<dd>a vector of the data linked to the different factor</dd></dl>

Arguments

input filter — filter_na_empty

<dl>

<dt>weights</dt>
<dd>the dataframe of weights, one row correspond to a
series of observation</dd>


<dt>weights_factor</dt>
<dd>the dataframe which contains the different
factor linked to the weights</dd>


<dt>trait_data</dt>
<dd>a vector of the data linked to the different factor</dd>

</dl>

input filter

filter_na_empty: input filter

Description

Usage

Arguments