Realize the Trait Abundance Distribution
skr ses genration/save/load
check_parameter_type
check_parameter_value
parameters checkings
The CONSTANTS constant
input filter
Generate random matrix
stats per random generation
abundance generation
stats per random genration/save/load
weighted moments generation
Launch the analysis
load_abundance_dataframe
load_depending_on_format
load_package
load_stat_skr_param
load_statistics_per_obs
load_statistics_per_random
load_tad_table
load_weighted_moments
moments_graph
Compare a value to random values
save_abundance_dataframe
save_depending_on_format
observations genration/save/load
save_stat_skr_param
save_statistics_per_obs
save_statistics_per_random
save_weighted_moments
skr_custom_uniform_names
skr_graph
skr_param_graph
skr_standard_uniform_names
Compute the weighted mean, variance, skewness and kurtosis
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).
Useful links