KIRCHOFF, BRUCE. Department of Biology, P.O. Box 26174, The University of North Carolina at Greensboro, Greensboro, NC 27402-6174. - Do rich data allow greater inter-investigator agreement in character states?
Groups of plant systematists at the Royal Botanic Gardens, Sydney,
were given 87 pictures of plant parts in one of two classes, and asked
to divide them into character states in two separate experiments. In
the first experiment (Trial 1) the pictures were of cotyledons only.
In the second experiment (Trial 2), the pictures constituted of
triplets: a cotyledon, seedling leaf, and inflorescence bract. These
triplets were intended to simulate complex data such a might be
garnered by looking at a plant. The pictures were drawn from a
published treatment of the plant genus Banksia. Each picture or
triplet represented one taxon. In each trial the systematists were
given about ¾ hour to create character states (groups of similar
pictures). Hierarchical groupings were not permitted. Each experiment
resulted in four characters, one for each group of systematists. For
analysis, these characters were represented as trees, and consensus
trees computed. Visual inspection of the data trees showed that the
systematists were able to produce smaller, more precisely defined
clusters (character states) in Trial 2. The Strict and Majority Rule
consensus trees for Trial 1 were completely unresolved, while those
for Trial 2 contained a single cluster of two triplets, and three
clusters of two triplets, respectively. The Semi-strict tree for Trial
1 contains four clusters, two of which are nested in a third. The
average cluster size is 6.3. The Trial 2 tree contains seven clusters,
two of which are nested in a much larger third. Average cluster size
is 4.4. The main differences between the two Adams trees are the
number and sizes of the clusters. The Trial 2 tree has a greater
number of smaller clusters than the Trial 1 tree. Conclusion: Rich
data does allow greater inter-investigator agreement in character
states.
Key words: Banksia, character states, characters, complexity, morphological characters, phylogenetic analysis