Biology subjects

Carlson, C. J.

Publications and source records attributed to Carlson, C. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Phylodynamic analysis reveals asymmetric and accelerating global spread of dengue virus

Dengue virus (DENV) continues to expand globally, with increasing incidence in both endemic and non-endemic countries. Leveraging a large global dataset of DENV genomes starting from the 1940s, we reconstructed global and regional patterns of DENV spread using phylogeographic and phylodynamic methods. Our analyses reveal that the current global diversity of urban DENV originated in Asia in the first half of the 20th century. During the more than 100 years since, we find that the highest density of between-country spread occurs within Asia and the region continues to be a global source, seeding transmission in Africa and the Americas. Global spread is, however, not balanced. Even though there is more travel to South America, we show that DENV lineages primarily enter North America (mostly from South Asia) through a link defined by seasonal synchrony across the Northern Hemisphere. Along with a substantial increase in global travel starting ~2010, the rate of spread to the Americas is increasing, establishing new lineages associated with large recent outbreaks. DENV lineages do not frequently spread back to Asia from the Americas or Africa, and we posit this is due to higher genetic diversity in Asia, leading to stiffer competition for invading lineages. Within the Americas, the network of DENV dispersal initiates in North America, primarily the Caribbean, and then is maintained by major hubs in South America. Overall, we find that travel volume, rather than climate factors, is mostly responsible for long-term patterns of DENV spread globally and within the Americas. Our results highlight key nodes in the global dynamics of DENV lineages, and suggest spread will continue to accelerate in a more connected world.

genomics↗

bioRxiv2026

Limited role of climate change in out-of-season Joshua tree flowering

Climate change is expected to touch every ecological community on the planet, but connecting climate change to specific ecological events remains challenging. The emerging practice of climate change attribution can identify how anthropogenic climate change contributes to extreme weather events--but has not yet been applied to unusual ecological events. Here, we demonstrate attribution of a recent, striking ecological anomaly: Joshua trees (Yucca brevifolia and Y. jaegeriana) flowering in October 2025, fully four months earlier than normal. We used crowdsourced records of Joshua tree flowering to train a machine learning model that recovers weather triggers of flowering, and successfully predicts regular-seasonal and out-of-season flowering events. We then simulated weather without human-caused climate change using the output of 10 global climate models, and projected Joshua tree flowering under those counterfactual conditions with our trained model. Surprisingly, we found out-of-season blooms were driven by high winter rainfall, not rising temperatures--and therefore, are probably the result of natural weather variability. Our results place out-of-season flowering in context with climate change threats facing Joshua trees, while providing a prototype attribution analysis of an extreme ecological event and identifying priorities for future climate modeling.

ecology↗

bioRxiv2026

Specialists drive biodiversity scaling in symbiotic relationships

The stunning diversity of symbiotic life forms, and their unique vulnerability to extinction, emerge from the close relationship between host and symbiont species richness. The general form of this relationship should be linear, but simulation studies have shown that it becomes sub-linear (and even power law-like) when sampling within a host-symbiont network. Here, we resolve this paradox with a new mathematical model of scaling in bipartite graphs, based on the independent behavior of specialist (single-host) and generalist (multi-host) symbionts. Using this model, we show that specialists constrain the architecture of ecological networks, and at global scales, drive the accumulation of symbiont biodiversity. By definition, specialists also face the highest risk of coextinction with their hosts and -- despite substantial uncertainty about their true richness -- we show that they could easily account for the majority of threatened species on Earth. Our study reveals that symbiosis remains one of the most poorly-understood building blocks of ecosystem function and evolutionary diversification, and serves as a reminder that foundational macroecological principles are still waiting to be discovered from first principles.

ecology↗

bioRxiv2026

Evolutionary history of Jamestown Canyon virus disentangles complex multi-vector ecology

Jamestown Canyon virus (JCV) is a re-emerging mosquito-borne virus of increasing concern in North America. It has been historically understudied, leading to significant gaps in our understanding of its evolutionary history, ecological maintenance, and transmission dynamics. Here, we generated 658 whole-genome JCV sequences from the Northeast United States, including 84% (500/597) of all JCV-positive mosquitoes detected in Connecticut from 1997-2022. Then we applied phylodynamic methods to demonstrate how mosquito phenology and host interaction structure the persistence and spread of JCV. Our phylogenetic analyses estimate that JCV was introduced in the Northeast by at least the early 1700s and the primary introductions of lineages A and B into Connecticut occurred during the mid-1800s to mid-1900s. Further, we estimate that JCV evolves at a rate of [~]3 x 10-5 s/s/y, making it one of the slowest evolving known RNA viruses, because the virus spends [~]10 months per year in evolutionary stasis while over-wintering in mosquito eggs. To investigate ecological drivers of JCV spread in Connecticut, we paired discrete trait and continuous phylogeographic reconstructions with mosquito surveillance data. We estimate that JCV has a low diffusion rate of [~]30-60 km2/year, which is more similar to slow-moving tick-borne viruses than other mosquito-borne viruses. We found that univoltine Aedes mosquitoes were likely to maintain the virus across years through overwintering in eggs, accounting for its slow evolution and dispersal, while multivoltine mosquitoes contribute to periodic bursts of spatial diffusion and amplification within seasons. By characterizing seasonal dynamics of JCV, we demonstrate the utility of dense sequencing and phylodynamics to disentangle complex transmission cycles, offering a framework to rapidly advance our evolutionary and ecological knowledge of understudied viruses.

ecology↗

bioRxiv2025

Museum collections and machine learning guide discovery of novel coronaviruses and paramyxoviruses

Natural history museum collections are valuable but underutilized resources for viral discovery, offering opportunities to test hypotheses about viral occurrence across space, time, and taxonomic groups. We developed machine learning models of bat host suitability to guide coronavirus and paramyxovirus screening of 1330 and 491 tissues, respectively, in a museum collection. For the first time, we recovered coronavirus (n = 16) and paramyxovirus (n = 3) sequences from archived museum tissues, confirming three novel coronavirus host species and three novel paramyxovirus host species (3% and 33% prediction success rate, respectively). These sequences included a SARS-like coronavirus and an orthoparamyxovirus from Angolan Rhinolophus fumigatus specimens collected in June 2019, suggesting that viruses with epidemic potential may be more widespread in sub-Saharan Africa than previously believed. Our study demonstrates the value of combining predictive modeling and collections-based viral discovery, particularly for filling outstanding sampling gaps and investigating changes in host-virus associations over time.

ecology↗

bioRxiv2025

The macroecology of viral coinfection

Coinfection is common in wild animals, and can profoundly influence disease outcomes and transmission. However, most coinfection research is based on laboratory experiments or a few well-studied wildlife systems. Here, we use data from the PREDICT project - the largest standardized wildlife disease surveillance project ever conducted - to describe patterns of viral coinfection and evaluate their association with host and virus factors. Within the viruses prioritized for testing, we find that coinfection is rare (detected in just 223 of 65,662 animals), but still more common than expected by chance - especially coinfections of coronaviruses, paramyxoviruses, and influenza A virus. We further find that coinfection is associated with host age, but bats and rodents exhibit opposing relationships. We find that captive wild animals (specifically rats and mallards) exhibit higher coinfection than free-ranging wild animals, highlighting potential risks to wildlife and human health from the wildlife trade. Finally, we find that biases in sampling and testing can shape observed patterns of coinfection. Our results characterize associations among viruses in the largest relevant dataset currently available. Factors associated with coinfection in this dataset such as host-level variation, virus-virus interactions, and human interference should be further tested via surveillance and laboratory approaches to better resolve the role of coinfection as an important and likely overlooked driver of viral dynamics in nature.

ecology↗

bioRxiv2025

Community and functional stability in a working bioreactor degrading 1,4-dioxane at the Lowry Landfill Superfund Site

1,4-dioxane (dioxane) is an emerging contaminant that poses risks to human and environmental health. Bacterial dioxane degradation is increasingly being studied as a method to remove dioxane from contaminated water. However, there is a lack of studies on microbial community structures and functions within efficient, large scale, biodegradation-based remediation technologies. The Lowry Landfill Superfund Site (Colorado, USA) uses an on-site, pump-and-treat facility to remove dioxane from contaminated groundwater by biodegradation. Here, 16S rRNA and shotgun metagenomic sequencing were used to describe microbial community composition, soluble di-iron monooxygenase (SDIMO) alpha hydroxylases, and potential for dioxane degradation and horizontal gene transfer in bioreactor support media from the facility. Support media showed diverse microbial communities dominated by Nitrospiraceae, Nitrososphaeraceae, and Nitrosomonadaceae. Pseudonocardia were also detected, suggesting a potential presence of known dioxane-degraders. Candidate SDIMOs belonged mostly to Group V, followed by Groups IV, II, and I (based on read depth). The most abundant Group V clade contained 38 proteins that were phylogenetically related to DxmA-like proteins, including that of Pseudonocardia dioxanivorans CB1190 (a known dioxane degrader). Seventeen Lowry contigs containing DxmA-like proteins contained protein-coding genes potentially involved in chemical degradation, transcriptional regulation, and chemical transport. Interestingly, these contigs also contained evidence of potential horizontal gene transfer, including toxin-antitoxin proteins, phage integrase proteins, putative transposases, and putative miniature inverted-repeat transposable elements. These findings improve our understanding of potential dioxane biodegradation mechanisms in a functioning remediation system. Further studies are needed to definitively confirm microbial activity and enzymatic activity towards dioxane removal in this site. IMPORTANCEAs an environmental contaminant, 1,4-dioxane poses risks for water quality and human health. Used as a solvent and chemical stabilizer in a variety of manufacturing and industrial applications, microbiological methods of detoxification and mitigation are of interest. The degradation of 1,4-dioxane by the bacterium Pseudonocardia spp. is the best understood example; however, these studies are largely based on single isolate, bench-scale, or in silico experiments. Consequently, a knowledge gap exists on bacterial degradation of 1,4-dioxane at environmentally relevant concentrations using functioning remediation technologies at scale. This study addresses this gap directly by describing microbial taxa, enzymes, and potential horizontal gene transfer mechanisms associated with an active treatment plant located on a 1,4-dioxane-impacted U.S. Environmental Protection Agency (EPA) superfund site. As 1,4-dioxane contamination gains more attention, these findings may prove useful for future facilities aiming to promote and optimize removal by biodegradation.

microbiology↗

bioRxiv2025

Wildlife trade drives animal-to-human pathogen transmission over 40 years

Wildlife trade affects a quarter of terrestrial vertebrates(1) and creates novel opportunities for cross-species pathogen transmission(2-4). Yet, its precise role in shaping human-wildlife pathogen exchanges remains unclear. Analysing 40 years of global wildlife trade data, we show that traded mammals are twice as likely to share pathogens with humans than non-traded species. Moreover, time spent in trade strongly predicts the number of zoonotic pathogens that wildlife species host: on average, a species shares an additional pathogen with humans for every 9 years of presence in trade. This work highlights the importance of the wildlife trade in driving animal-to-human pathogen transmission, offering key insights into pathogen biogeography in the Anthropocene and the prevention of future pandemics.

ecology↗

bioRxiv2024

Viral epidemic potential is not uniformly distributed across the bat phylogeny

Characterizing host-virus associations is critical due to the rising frequency of emerging infectious diseases originating from wildlife. Past analyses have evaluated zoonotic risk as binary, but virulence and transmissibility can vary dramatically. Recent work suggests bats harbor more viruses with high virulence in humans than other taxa. However, it remains unknown whether all bats harbor viruses of equal zoonotic potential. We used phylogenetic factorization to flexibly identify clades of mammals (at any taxonomic level) associated with low or high viral epidemic potential, and found virulence and transmissibility only cluster within bat subclades, often among cosmopolitan families. Mapping the geographic distributions of these bat clades with spatial data on anthropogenic footprint suggests high zoonotic risk in coastal South America, Southeast Asia, and equatorial Africa. Our results deepen understanding of the host- virus network and identify clades to prioritize for viral surveillance, risk mitigation, and future studies characterizing mechanisms of viral tolerance.

evolutionary biology↗

bioRxiv2023

Viral genomic features predict orthopoxvirus reservoir hosts

Orthopoxviruses (OPVs), including the causative agents of smallpox and mpox have led to devastating outbreaks in human populations worldwide. However, the discontinuation of smallpox vaccination, which also provides cross-protection against related OPVs, has diminished global immunity to OPVs more broadly. We apply machine learning models incorporating both host ecological and viral genomic features to predict likely reservoirs of OPVs. We demonstrate that incorporating viral genomic features in addition to host ecological traits enhanced the accuracy of potential OPV host predictions, highlighting the importance of host-virus molecular interactions in predicting potential host species. We identify hotspots for geographic regions rich with potential OPV hosts in parts of southeast Asia, equatorial Africa, and the Amazon, revealing high overlap between regions predicted to have a high number of potential OPV host species and those with the lowest smallpox vaccination coverage, indicating a heightened risk for the emergence or establishment of zoonotic OPVs. Our findings can be used to target wildlife surveillance, particularly related to concerns about mpox establishment beyond its historical range.

microbiology↗

bioRxiv2023

Trends in mosquito species distribution modeling: insights for vector surveillance and disease control

Species distribution modeling (SDM) has become an increasingly common approach to explore questions about ecology, geography, outbreak risk, and global change as they relate to infectious disease vectors. Here, we conducted a systematic review of the scientific literature, screening 563 abstracts and identifying 204 studies that used SDMs to produce distribution estimates for mosquito species. While the number of studies employing SDM methods has increased markedly over the past decade, the overwhelming majority used a single method (MaxEnt) and focused on human infectious disease vectors or their close relatives. The majority of regional models were developed for areas in Africa and Asia, while more localized modeling efforts were most common for North America and Europe. Findings from this study highlight gaps in taxonomic, geographic, and methodological foci of current SDM literature for mosquitoes that can guide future efforts to study the geography of mosquito-borne disease risk.

ecology↗

bioRxiv2022

Ecological drivers of sustained enzootic yellow fever virus transmission in Brazil, 2017-2021

Beginning December 2016, sylvatic yellow fever (YF) outbreaks spread into southeastern Brazil, and Minas Gerais state experienced two sylvatic YF waves (2017 and 2018). Following these massive YF waves, we screened 187 free-living non-human primate (NHPs) carcasses collected throughout the state between January 2019 and June 2021 for YF virus (YFV) using qPCR. One sample belonging to a Callithrix, collected in June 2020, was positive for YFV. The viral strain belonged to the same lineage associated with 2017-2018 outbreaks, showing the continued enzootic circulation of YFV in the state. Next, using data from 781 NHPs carcasses collected in 2017-18, we used generalized additive mixed models (GAMMs) to identify the spatiotemporal and host-level drivers of YFV infection and intensity (an estimation of genomic viral load in the liver of infected NHP). Our GAMMs explained 65% and 68% of variation in virus infection and intensity, respectively, and uncovered strong temporal and spatial patterns for YFV infection and intensity. NHP infection was higher in the eastern part of Minas Gerais state, where 2017-2018 outbreaks affecting humans and NHPs were concentrated. The odds of YFV infection were significantly lower in NHPs from urban areas than from urban-rural or rural areas, while infection intensity was significantly lower in NHPs from urban areas or the urban-rural interface relative to rural areas. Both YFV infection and intensity were higher during the warm/rainy season compared to the cold/dry season. The higher YFV intensity in NHPs in warm/rainy periods could be a result of higher exposure to vectors and/or higher virus titers in vectors during this time resulting in the delivery of a higher virus dose and higher viral replication levels within NHPs. Further studies are needed to better test this hypothesis and further compare the dynamics of YFV enzootic cycles between different seasons. Author SummaryIn 2017 and 2018 massive sylvatic yellow fever (YF) outbreaks took place in Minas Gerais Brazil. To investigate yellow fever virus (YFV) circulation following these massive outbreaks, we investigated samples from 187 free-living non-human primate (NHPs) collected between January 2019 and June 2021. One sample belonging to a Callithrix, collected in June 2020 was positive for YFV. This virus was closely related to YFV from previous outbreaks (2017-2018) showing the continued enzootic circulation of YFV in the state. Next, we investigated the drivers of YFV infection and intensity (an estimation of viral load in each infected NHP) during the 2017-18 outbreaks. The odds of YFV infection in NHPs were lower in urban areas compared to rural ones as expected in sylvatic cycles. There were strong temporal and spatial patterns were observed for YFV infection and intensity, especially in the eastern part of Minas Gerais state. The higher YFV infection and intensity observed during the warm/rainy season (as opposed to the cold/dry one) could be related to higher exposure to vectors and/or higher virus titers in vectors during this time. The possible delivery of a higher virus dose in NHPs could lead to higher viral replication levels within NHPs explaining the higher intensity of infection during warm/rainy season. Further studies are needed to better test this hypothesis and further compare the dynamics of YFV enzootic cycles between different seasons.

microbiology↗

bioRxiv2022

Viral diversity and zoonotic risk in endangered species

A growing body of evidence links zoonotic disease risk, including pandemic threats, to biodiversity loss and other upstream anthropogenic impacts on ecosystem health. However, there is little current research assessing viral diversity in endangered species. Here, combining IUCN Red List data on 5,876 mammal species with data on host-virus associations for a subset of 1,273 extant species, we examine the relationship between endangered species status and viral diversity, including the subset of viruses that can infect humans (zoonotic viruses). We show that fewer total viruses and fewer zoonotic viruses are known to infect more threatened species. After correcting for sampling effort, zoonotic virus diversity is mostly independent of threat status, but endangered species--despite a higher apparent research effort--have a significantly lower diversity of viruses, a property that is not explained by collinearity with host phylogeography or life history variation. Although this pattern could be generated by real biological processes, we suspect instead that endangered species may be subject to additional sampling biases not captured by the total volume of scientific literature (e.g., lower rates of invasive sampling may decrease viral discovery). Overall, our findings suggest that endangered species are no more or less likely to host viruses that pose a threat to humans, but future zoonotic threats might remain undiscovered in these species. This may be concerning, given that drivers of endangered species vulnerability such as habitat disturbance, wildlife trade, or climate vulnerability may increase virus prevalence in reservoirs and risk of spillover into humans.

ecology↗

bioRxiv2022

Sampling strategies and pre-pandemic surveillance gaps for bat coronaviruses

The emergence of SARS-CoV-2, and the challenge of pinpointing its ecological and evolutionary context, has highlighted the importance of evidence-based strategies for monitoring viral dynamics in bat reservoir hosts. Here, we compiled the results of 93,877 samples collected from bats across 111 studies between 1996 and 2018, and used these to develop an unprecedented open database, with over 2,400 estimates of coronavirus infection prevalence or seroprevalence at the finest methodological, spatiotemporal, and phylogenetic level of detail possible from public records. These data revealed a high degree of heterogeneity in viral prevalence, reflecting both real spatiotemporal variation in viral dynamics and the effect of variation in sampling design. Phylogenetically controlled meta-analysis revealed that the most significant determinant of successful viral detection was repeat sampling (i.e., returning to the same site multiple times); however, fewer than one in five studies longitudinally collected and reported data. Viral detection was also more successful in some seasons and from certain tissues, but was not improved by the use of euthanasia, indicating that viral detection may not be improved by terminal sampling. Finally, we found that prior to the pandemic, sampling effort was highly concentrated in ways that reflected concerns about zoonotic risk, leaving several broad geographic regions (e.g., South Asia, Latin America and the Caribbean, and most of Sub-Saharan Africa) and bat subfamilies (e.g., Stenodermatinae and Pteropodinae) measurably undersampled. These gaps constitute a notable vulnerability for global health security and will likely be a future barrier to contextualizing the origin of novel zoonotic coronaviruses.

ecology↗

bioRxiv2022

Exploring the mosquito-arbovirus network: a survey of vector competence experiments

Arboviruses receive heightened research attention during major outbreaks, or when they cause unusual or severe clinical disease, but are otherwise under-characterized. Global change is also accelerating the emergence and spread of arboviral diseases, leading to time sensitive questions about potential interactions between viruses and novel vectors. Vector competence experiments help determine the susceptibility of certain arthropods to a given arbovirus, but these experiments are often conducted in real-time during outbreaks, rather than with preparedness in mind. We conducted a systematic review of reported mosquito-arbovirus competence experiments, screening 570 abstracts to arrive at 265 studies testing in vivo arboviral competence. We found that over 90% of potential mosquito-virus combinations are untested in experimental settings, and that entire regions and their corresponding vectors and viruses are undersampled. These knowledge gaps stymie outbreak response, and limit attempts to both build and validate predictive models of the vector-virus network.

ecology↗

bioRxiv2021

Mammal virus diversity estimates are unstable due to accelerating discovery effort

Host-virus association data form the backbone of research into eco-evolutionary drivers of viral diversity and host-level zoonotic risk. However, knowledge of the wildlife virome is inherently constrained by historical discovery effort, and there are concerns that the reliability of ecological inference from host-virus data may be undermined by taxonomic and geographical sampling biases. Here, we evaluate whether current estimates of host-level viral diversity in wild mammals are stable enough to be considered biologically meaningful, by analysing a comprehensive dataset of discovery dates of 6,571 unique mammal host-virus associations between 1930 and 2018. We show that virus discovery rates in mammal hosts are still either constant or accelerating, with little evidence of declines towards viral richness asymptotes in even highly-sampled hosts. Consequently, inference of relative viral richness across host species has been unstable over time, particularly in bats, where intensified surveillance since the early 2000s caused a rapid rearrangement of species ranked viral richness. Our results show that comparative inference of host-level virus diversity across mammals is highly sensitive to even short-term changes in sampling effort. We advise caution to avoid overinterpreting patterns in current data, since our findings suggest that an analysis conducted today could feasibly draw quite different conclusions than one conducted only a decade ago.

ecology↗

bioRxiv2021

The Global Virome in One Network (VIRION): an atlas of vertebrate-virus associations

Data cataloguing viral diversity on Earth have been fragmented across sources, disciplines, formats, and various degrees of open collation, posing challenges for research on macroecology, evolution, and public health. Here, we solve this problem by establishing a dynamically-maintained database of vertebrate-virus associations, called The Global Virome in One Network (VIRION). The VIRION database has been assembled through both reconciliation of static datasets and integration of dynamically-updated databases. These data sources are all harmonized against one taxonomic backbone, including metadata on host and virus taxonomic validity and higher classification; additional metadata on sampling methodology and evidence strength are also available in a harmonized format. In total, the VIRION database is the largest open-source, open-access database of its kind, with roughly half a million unique records that include 9,521 resolved virus "species" (of which 1,661 are ICTV ratified), 3,692 resolved vertebrate host species, and 23,147 unique interactions between taxonomically-valid organisms. Together, these data cover roughly a quarter of mammal diversity, a tenth of bird diversity, and ~6% of the estimated total diversity of vertebrates, and a much larger proportion of their virome than any previous database. We show how these data can be used to test hypotheses about microbiology, ecology, and evolution, and make suggestions for best practices that address the unique mix of evidence that coexists in these data.

microbiology↗

bioRxiv2021

Plague risk in the western United States over seven decades of environmental change

After several pandemics over the last two millennia, the wildlife reservoirs of plague (Yersinia pestis) now persist around the world, including in the western United States. Routine surveillance in this region has generated comprehensive records of human cases and animal seroprevalence, creating a unique opportunity to test how plague reservoirs are responding to environmental change. Here, we develop a new method to detect the signal of climate change in infectious disease distributions, and test whether plague reservoirs and spillover risk have shifted since 1950. We find that plague foci are associated with high-elevation rodent communities, and soil biochemistry may play a key role in the geography of long-term persistence. In addition, we find that human cases are concentrated only in a small subset of endemic areas, and that spillover events are driven by higher rodent species richness (the amplification hypothesis) and climatic anomalies (the trophic cascade hypothesis). Using our detection model, we find that due to the changing climate, rodent communities at high elevations have become more conducive to the establishment of plague reservoirs--with suitability increasing up to 40% in some places--and that spillover risk to humans at mid-elevations has increased as well, although more gradually. These results highlight opportunities for deeper investigation of plague ecology, the value of integrative surveillance for infectious disease geography, and the need for further research into ongoing climate change impacts.

ecology↗