Search for: All records

Abstract The stem lineage of Archosauria is populated by a diverse fossil record that remains notably understudied relative to the crown clade. Prominent among these specimens is a beautifully preserved skull of the early mid-Triassic rhynchosaur Mesosuchus browni [Iziko South African Museum (SAM) 6536], whose phylogenetic position has considerable influence on patterns of pan-archosaurian cranial evolution. We used high-resolution, micro-computed tomography to re-examine the anatomy of this specimen, building on previous studies that were either limited to external observations or restricted to the braincase. A digital segmentation of the cranial elements and primary neurovascular canals of SAM-PK-6536 allows for expanded character scoring and constitutes a foundation for future comparative insights. Our data support the phylogenetically oldest instance of a pneumatized maxilla in a pan-archosaur, bringing the record of antorbital pneumatization into closer alignment with that of the neurocranium. The nasal cavity and primary palate of Mesosuchus includes a complex septomaxilla, a novel element anterior to the vomer, and is likely to have supported a well-developed vomeronasal system. The evolution of this system is discussed in terms of both phylogenetic pattern and how the skeletal architecture of Mesosuchus and other fossils could inform the signalling dynamics that pattern the vomeronasal system during development. 

Abstract Metagenomics provides insights into the potential of microorganisms to mediate key biogeochemical processes encoded in ecosystem models. Efforts have been made to model gene abundance changes, but it is unclear how much gene abundance variation can be explained by modeled biogeochemical rates alone. We compare the relative abundance of 32 genes having the potential for photosynthesis, nitrification, denitrification, and sulfur cycling with rates predicted by a model in the Chesapeake Bay. Modeled rates explained a significant amount of gene abundance variation for half of the genes examined and at least one gene involved in four of five processes examined. An average of 21.3% of gene abundance variability is explained by the modeled rates, which increases to 31.8% when considering the 16 genes with significant relationships. For photosynthesis and denitrification, rates represent the behavior of some taxonomic groups (cyanobacteria and gammaproteobacteria) better than others (eukaryotic algae and Bacteroidetes). Significant correlations between sulfur cycling rates and genes appear for oxidative but not reductive forms of the relevant genes. The marker genesamoABwere not significantly correlated with nitrification rates. However, another gene involved in nitrification but not considered a marker gene (hao) was significantly correlated. This work demonstrates modeled rates often but not always and capture a significant amount variation of genes encoding enzymes involved in the modeled processes. Other factors, like temperature‐dependent rates or cell transport, may need to be incorporated into models to explain more variation in gene abundance. Doing so could be a useful quality control for microbial processes encoded in ecosystem‐level biogeochemical models.