A PHYLOGENETIC FRAMEWORK FOR THE FAMILY PHACOPIDAE (TRILOBITA) BASED ON BAYESIAN INFERENCE METHODS

Arguments over the degree of taxonomic splitting, genera plagued by wastebasket taxa, and a relatively conserved morphology have left the systematics of the trilobite family Phacopidae in a state of disarray. Few published phylogenetic frameworks encompass the diversity of the group. Complex patterns of morphologic similarity between taxa complicate the distinction of synapomorphy from symplesiomorphy and/or homoplasy. Several species behave as ‘rogue taxa,’ being volatile in hypothesized phylogenetic placement—especially among analyses employing different methods or emphasizing different character sets—so that polytomies are common and phylogenetic resolution is low. These factors have resulted in unstable higher-level taxa.

Over the last decade, advances in Bayesian inference methods have revolutionized phylogenetic analysis of morphological data. Analyses of simulated datasets have shown that Bayesian inference methods may outperform parsimony-based methods in recovering phylogenetic trees. Though Bayesian methods are becoming more commonplace in paleontology, they usually combine extant and extinct species within a single framework and few studies have investigated fossil-only datasets using these methods.

Here, I apply Bayesian inference methods, using the Fossilized Birth-Death process as a model framework, to construct a phylogenetic tree of Phacopidae. This study encompasses 65 species representing four of the five major tribes and 68 characters representing all regions of the trilobite exoskeleton. I propose an MCC tree that shows strong crownward posterior support for recovered clades. Even after degradation of the dataset, these crownward relationships remain stable, suggesting a greater degree of phylogenetic signal compared to previous studies. The proposed tree offers a framework upon which future phylogenetic studies may build and macroevolutionary studies may be conducted.