This function determines whether the selected traits exhibit or not a clustering/overdispersion
signal on the tested samples. For each trait, compares the observed Mean Pairwise Distance (MPD)
of each sample against a distribution of synthetic commmunities MPDs obtained by a randomization
test. Each synthetic community is build maintaining the original sample richness and randomly
selecting organisms form the global pool.
A data frame containing organisms names on the first column and its trait values on the
consecutive ones. It also has to contain two columns with the maximum and the minimum values of the tested
environmental variable where the organisms have been observed.
table2
A presence-absence observations table with the organisms names on the first column and the
sample names as consecutive colnames.
table3
A dataframe containing sample names on the first column and environmental parameters on the
consecutive ones.
traits_columns
Table 1 column numbers where different trait values appear.
repetitions
Number of simulated synthetic communities distributions.
Value
The function returns a dataframe with trait names as colnames and the p-value distribution of the different
traits.
# NOT RUN {# }# NOT RUN {data(group_information)
data(table_presence_absence)
data(metadata)
rtcc1(group_information, table_presence_absence, metadata, 2:11, 100)
# }# NOT RUN {# }