Colin J. Carlson

This study uses phylogeographic and phylodynamic methods to analyze DENV genome data, revealing asymmetric global spread patterns and the role of travel over climate in DENV transmission.

The paper uses machine learning to attribute an unusual ecological event, early Joshua tree flowering, to natural weather variability rather than climate change.

Legally traded wild mammals have higher odds (OR 2.72) of sharing pathogens with humans, and each 9 years in global trade adds roughly one human-shared pathogen.

This study shows that specialist symbionts drive biodiversity scaling in host-symbiont networks and may account for most threatened species.

This study uses whole-genome sequencing and phylodynamic methods to analyze the evolutionary history and ecological dynamics of Jamestown Canyon virus, revealing its slow evolution and transmission patterns.

The paper identifies bat subclades with high viral epidemic potential and links them to regions with high zoonotic risk.

The paper uses machine learning to screen museum tissues for novel coronaviruses and paramyxoviruses, recovering sequences from archived samples and identifying new host species.

The paper analyzes viral coinfection patterns in wildlife using the PREDICT dataset, finding rare but significant coinfections linked to host age, species, and sampling biases.

The paper introduces a spatially-explicit method to estimate extinction dates and identify potential rediscovery zones using georeferenced sighting data.

The paper simulates anthrax transmission using movement data to assess how contact rate estimates vary with analysis scale and method.

The paper introduces PEARL, an open-source database for parasite conservation assessments, focusing on macroparasitic invertebrates and their extinction risks.