save_obs_df

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 

save_obs_df function

<dl><dt>weights_factor</dt>
<dd>the dataframe which contains the different
factor linked to the weights</dd>
<dt>stat_per_obs_file</dt>
<dd>the path and name of the RDS file to
load/save the dataframe which
contains the statistics for each observed row regarding the random ones</dd>
<dt>regenerate_stat_per_obs_df</dt>
<dd>boolean to specify if
the statistics per observation dataframe is computed again</dd>
<dt>randomization_number</dt>
<dd>the number of random abundance matrix to
generate</dd>
<dt>significativity_threshold</dt>
<dd>the significance threshold to
consider that the observed value is in the randomized value</dd></dl>

Arguments

observations genration/save/load — save_obs_df

<dl>

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


<dt>stat_per_obs_file</dt>
<dd>the path and name of the RDS file to
load/save the dataframe which
contains the statistics for each observed row regarding the random ones</dd>


<dt>regenerate_stat_per_obs_df</dt>
<dd>boolean to specify if
the statistics per observation dataframe is computed again</dd>


<dt>randomization_number</dt>
<dd>the number of random abundance matrix to
generate</dd>


<dt>significativity_threshold</dt>
<dd>the significance threshold to
consider that the observed value is in the randomized value</dd>

</dl>

observations genration/save/load

save_obs_df: observations genration/save/load

Description

Usage

Arguments