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Concordance was measured using the Adjusted Rand Index [31], which quantifies the agreement between two data partitions.
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Two data partitions were created by concatenating MIR168a with MIR168b and ITS with EIF3E [ 37].
In the MrBayes analysis, substitution model parameters were unlinked across the four data partitions.
ILD test probability values for the four data partitions generated using 1000 replicates.
Notably, the position of P. krempfii was significantly different between the four largest data partitions (Table 4), even though this species does not appear to be associated with a rapid radiation (Table 5).
To assess congruence between data partitions three methods were used.
These both provide a measure of agreement between two clustering outcomes or data partitions, while the adjusted Rand index provides more sensitivity with its increased range and also accounts for randomness in class assignment [ 22].
Incongruence between data partitions indicates that the two partitions compared have had different histories or that one of them violate the assumptions of the phylogenetic method [ 29].
Primarily, there are two contradictory strategies utilized to handle data sets with significant phylogenetic incongruence between independent data partitions.
We detected significant conflict between data partitions, especially between morphology and molecules.
First, the two fungal sequences were tested for combinability using the Partition Homogeneity Test [ 39] implemented in PAUP*4.0b10 [ 40], which showed that there was no significant incongruence between the two data sets (1000 artificial data sets, p = 0.14).
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