The 'requirement of total evidence' and its role in phylogenetic systematics

Abstract

The question of whether or not to partition data for the purposes of inferring phylogenetic hypotheses remains controversial. Opinions have been especially divided since Kluge's (1989, Systematic Zoology 38, 7-25) claim that data partitioning violates the requirement of total evidence (RTE). Unfortunately, advocacy for or against the RTE has not been based on accurate portrayals of the requirement. The RTE is a basic maxim for non-deductive inference, stipulating that evidence must be considered if it has relevance to an inference. Evidence is relevant if it has a positive or negative effect on a given conclusion. In the case of 'partitioned' phylogenetic inferences, the RTE is violated, and the basis for rational belief in any conclusion is compromised, unless it is shown that the partitions are evidentially irrelevant to one another. The goal of phylogenetic systematics is to hypothesize past causal conditions to account for observed shared similarities among two or more species. Such inferences are non-deductive, necessitating consideration of the RTE. Some phylogeneticists claim the parsimony criterion as justification for the RTE. There is no relation between the two - parsimony is a relation between a hypothesis and causal question(s). Parsimony does not dictate the content of premises prior to an inference. 'Taxonomic congruence,' 'supertrees,' and 'conditional combination' methods violate the RTE. Taxonomic congruence and supertree methods also fail to achieve the intended goal of phylogenetic inference, such that 'consensus trees' and 'supertrees' lack an empirical basis. 'Conditional combination' is problematic because hypotheses derived from partitioned data cannot be compared - a causal hypothesis inferred to account for a set of effects only has relevance to those effects, not any comparative relevance to other causal hypotheses. A similar problem arises in the comparisons of hypotheses derived from different causal theories. © Springer 2006.