Abstract
As eloquently stated by Nelson and Ladiges (2001) in the passage above, the way that systematic data is analyzed almost certainly will affect how it becomes interpreted. Often the way in which data are analyzed will depend on the type of data being considered. Regardless of the methods employed or data under consideration, there are several levels to analysis and systematic studies - whether based on morphology or molecules. For Grande and Bemis (1998:647), this followed an empirical exploratory-analytical-explanatory progression, so that “no conscious assumptions about processes of speciation, completeness of the fossil record, geographical dispersal, specific ancestors, specific areas of endemism, or ‘true’ phylogenies” will bias the results of the analysis. We agree with this as a starting point, but rephrase and add to it here. In our view, systematic studies encompass four phases: 1, Data generation, which is equivalent to Grande and Bemis’ “empirical exploratory” phase, and for morphologically based studies this involves specimen examination and comparisons, whereas in molecular studies, this involves amplification and sequencing of specific genes; 2, Data analysis, which is similar to Grande and Bemis’ analytical phase, and involves “sorting” of data, already with hypotheses of homology in place (similarly scored characters, sequence alignment, etc.), by some method (parsimony, likelihood, or Bayesian), to search for patterns in the data. We see Grande and Bemis’ “explanatory” phase as encompassing two distinct yet interrelated activities: 3, data examination—an iterative process of checking and re-checking character definitions or character coding, often spurred on by primary homology statements being interpreted as homoplasies in light of other characters; and 4, data explanation, or interpretation of evolutionary scenarios (e.g., life history evolution, biogeography, etc.) based on the pattern of phylogeny resulting from the analysis of character data.
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