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TAD (version 1.0.1)

Realize the Trait Abundance Distribution

Description

The “TAD” package compiled an analytical framework 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).

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Version

Install

install.packages('TAD')

Monthly Downloads

113

Version

1.0.1

License

BSD_3_clause + file LICENSE

Maintainer

Raphael Martin

Last Published

February 19th, 2026

Functions in TAD (1.0.1)

get_abundance_df

abundance generation
null_model_distribution_stats

Compare a value to random values
generate_stat_per_rand

stats per random generation
load_weighted_moments

load_weighted_moments
weighted_mvsk

Compute the weighted mean, variance, skewness and kurtosis
weighted_moments_dataframe

Example dataset of weighted_moments_dataframe
moments_graph

moments_graph
skr_graph

skr_graph
skr_custom_uniform_names

skr_custom_uniform_names
stat_per_rand_dataframe

Example dataset of stat_per_rand_dataframe
trait

Example dataset containing some traits
load_package

load_package
load_depending_on_format

load_depending_on_format
save_abundance_dataframe

save_abundance_dataframe
save_stat_skr_param

save_stat_skr_param
save_depending_on_format

save_depending_on_format
save_weighted_moments

save_weighted_moments
save_statistics_per_random

save_statistics_per_random
save_statistics_per_obs

save_statistics_per_obs
save_obs_df

observations genration/save/load
get_stat_per_rand

stats per random genration/save/load
skr_param_graph

skr_param_graph
get_weighted_mnts

weighted moments generation
skr_ses_dataframe

Example dataset of skr_ses
skr_standard_uniform_names

skr_standard_uniform_names
stat_per_obs_dataframe

Example dataset of stat_per_obs_dataframe
filter_na_empty

input filter
generate_random_matrix

Generate random matrix
load_statistics_per_obs

load_statistics_per_obs
load_stat_skr_param

load_stat_skr_param
load_abundance_dataframe

load_abundance_dataframe
launch_analysis_tad

Launch the analysis
load_statistics_per_random

load_statistics_per_random
check_parameter_value

check_parameter_value
filtered_abundances

Example dataset of filtred results just after abundances generation
build_skr_ses

skr ses genration/save/load
AB

Example dataset containing some traits
check_parameters

parameters checkings
CONSTANTS

The CONSTANTS constant
check_parameter_type

check_parameter_type
abundance_dataframe

Example dataset of abundance_dataframe
load_tad_table

load_tad_table