Abstract
The utility of fossils in evolutionary contexts is dependent on their accurate placement in phylogenetic frameworks, yet intrinsic and widespread missing data make this problematic. The complex taphonomic processes occurring during fossilization can make it difficult to distinguish absence from non-preservation, especially in the case of exceptionally preserved soft-tissue fossils: is a particular morphological character (e.g., appendage, tentacle, or nerve) missing from a fossil because it was never there (phylogenetic absence), or just happened to not be preserved (taphonomic loss)? Missing data have not been tested in the context of interpretation of non-present anatomy nor in the context of directional shifts and biases in affinity. Here, complete taxa, both simulated and empirical, are subjected to data loss through the replacement of present entries (1s) with either missing (?s) or absent (0s) entries. Both cause taxa to drift down trees, from their original position, toward the root. Absolute thresholds at which downshift is significant are extremely low for introduced absences (two entries replaced, 6% of present characters). The opposite threshold in empirical fossil taxa is also found to be low; two absent entries replaced with presences causes fossil taxa to drift up trees. As such, only a few instances of non-preserved characters interpreted as absences will cause fossil organisms to be erroneously interpreted as more primitive than they were in life. This observed sensitivity to coding non-present morphology presents a problem for all evolutionary studies that attempt to use fossils to reconstruct rates of evolution or unlock sequences of morphological change. Stem-ward slippage, whereby fossilization processes cause organisms to appear artificially primitive, appears to be a ubiquitous and problematic phenomenon inherent to missing data, even when no decay biases exist. Absent characters therefore require explicit justification and taphonomic frameworks to support their interpretation.
Highlights
Introduction of Random Missing Data andAbsencesAs a benchmark for the original position of a taxon in the starting tree, the distance of a taxon from the root, in terms of the number of intervening nodes, is averaged for all most parsimonious trees
As more missing data are introduced to a taxon, more noise is introduced and the magnitude of drift from the original position is greater, but these shifts are symmetrical on a gross level (Fig. 2)
When the problem is approached from the opposite direction, the converse trend is observed: empirical soft-bodied fossil taxa drift up trees as absent entries are replaced with presences; 95% reach thresholds for significant shift up with a median of two replacements (11% of absences) for 56 taxa from small- and medium-sized data sets
Summary
As a benchmark for the original position of a taxon in the starting tree, the distance of a taxon from the root, in terms of the number of intervening nodes, is averaged for all most parsimonious trees. Trees are found using traditional searches in TNT (mult) with 100 random. % Reaching No of thresholds entries Percent (%)
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