DEEP TIME HISTORICAL BIOGEOGRAPHY OF MYTILID BIVALVES

Present-day patterns of biodiversity are heavily influenced by processes operating on million-year timescales, including evolution, extinction, and tectonics. A fundamental unit of biogeography is geographic range, or the physical representation of the spatial area a species inhabits. By reconstructing historic geographic ranges of taxa through deep time, we can understand how various processes have influenced the modern abundance and distribution of species. Here, I use Mytilid (Family Mytilidae) bivalves – a clade with high preservation potential and an excellent fossil record – as a case study for reconstructing the historical biogeography of a clade in a phylogenetic context. I digitize the known native geographic ranges of 30 extant bivalve species to create authentic geodesic data, and analyze these using ancestral state reconstruction. I leverage this approach to address the following questions: where did the clade originate, and what are the characteristics of its ancestral range? As the clade diversified, were there predictable biogeographic correlates for taxa prone to speciation or extinction? Lastly, are specific lifestyles (e.g., epifaunal, semi-infaunal or boring) geographically constrained, and is this pattern consistent through evolutionary time? Preliminary results suggest that the ancestral mytilid was epifaunal, confined to the tropics, and possessed a large ancestral geographic range. Extant bivalve species disregard Rapoport’s rule as their biology effectively tethers them towards warmer temperatures – something that remains consistent when analyzing the ancestral state. With an expanded dataset incorporating both extant and fossil taxa, this work will help address longstanding questions in macroecology and macroevolution; specifically the role of biogeography in determining speciation and extinction risk, and to what extent different environmental perturbations (e.g., warming vs. cooling) produce differing effects on biogeographic patterns. Lastly, these data may help form the basis for a predictive ‘roadmap’ for how we expect species to respond to a variety of future global change scenarios.