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We used two null models to test drivers of species turnover (measured by zeta diversity of different orders).
We used two null models to simulate the data.
We used two null models: in model I, each cell in the matrix has the same probability of being occupied [44], whereas in model II that probability depends on the total number of links of the column and the row defining the cell position [5].
In the case study, the textual explanation of the command box says that the program uses three null models, but as far as I can see it calls only two: FF and CC.
The significance of nestedness was assessed using two null models.
We tested for significance of both modularity and the nestedness found in our phage-bacteria infection network using two null models based on properties of our network.
Additionally, using four different null models (Appendix 1), we rejected the hypothesis of random nestedness.
These enrichments were not found when using two distinct null models.
We tested the ME significance (as described in the MEMo approach and in the previous sections) for all the possible 3003 gene pairs by using two different null models, simulated by generating 10 000 randomized version of the BEM through N and N′ switching steps, respectively.
Two null models were used to generate ensembles of networks (of size N) to evaluate the strength of the modularity and nestedness observed in the classified Escherichia coli O157 H7 phage-bacteria infection network.
The third line runs FALCON, using two binary nestedness measures (NODF and SR) and two null models (CC and FF, i.e. nulls 2 and 3) using the adaptive solver and displaying histogram plots.
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