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• W1544885324 abstract "The cladistic literature does not always specify the kind of multistate character treatment that is applied for an analysis. Characters can be treated either as unordered transformation series or as rooted [three-item analysis (3ia)] or unrooted state trees (ordered characters). We aimed to measure the impact of these character treatments on phylogenetic inference. Discrete characters can be represented either as rows or columns in matrices (e.g. for parsimony) or as hierarchies for 3ia. In the present study, we use simulated and empirical examples to assess the relative merits of each method considering both the character treatment and representation. We measure two parameters (resolving power and artefactual resolution) using a new tree comparison metric, ITRI (inter-tree retention index). Our results suggest that the hierarchical character representation not only results (with our simulation settings) in the greatest resolving power, but also in the highest artefactual resolution. Our empirical examples provide equivocal results. Parsimony unordered states yield less resolving power and more artefactual resolutions than parsimony ordered states, both with our simulated and empirical data. Relationships between three operational taxonomic units (OTUs), irrespective of their relationships with other OTUs, are called three-item statements (3is). We compare the intersection tree (which reconstructs a single tree from all of the common 3is of source trees) with the traditional strict consensus and show that the intersection tree retains more of the information contained in the source trees." @default.
• W1544885324 created "2016-06-24" @default.
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• W1544885324 date "2013-10-16" @default.
• W1544885324 modified "2023-10-05" @default.
• W1544885324 title "Phylogenetic inference using discrete characters: performance of ordered and unordered parsimony and of three-item statements" @default.
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• W1544885324 doi "https://doi.org/10.1111/bij.12159" @default.
• W1544885324 hasPublicationYear "2013" @default.
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