skip to main content

Search for: All records

Creators/Authors contains: "Albery, Gregory F."

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Free, publicly-accessible full text available January 1, 2024
  2. Free, publicly-accessible full text available July 21, 2023
  3. Free, publicly-accessible full text available June 1, 2023
  4. Ostfeld, Richard (Ed.)
    Free, publicly-accessible full text available June 1, 2023
  5. Free, publicly-accessible full text available August 1, 2023
  6. Host-virus association data underpin research into the distribution and eco-evolutionary correlates of viral diversity and zoonotic risk across host species. However, current 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 6571 unique mammal host-virus associations between 1930 and 2018. We show that virus discovery rates in mammal hosts are either constant or accelerating, with little evidence of declines towards viral richness asymptotes, even in 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 illustrate 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 it is feasible that an analysis conducted today could draw quitemore »different conclusions than one conducted only a decade ago.« less
  7. Pickett, Brett E. ; Jurado, Kellie (Ed.)
    ABSTRACT Data that catalogue viral diversity on Earth have been fragmented across sources, disciplines, formats, and various degrees of open sharing, 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 data sets 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 10th 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 testmore »hypotheses about microbiology, ecology, and evolution and make suggestions for best practices that address the unique mix of evidence that coexists in these data. IMPORTANCE Animals and their viruses are connected by a sprawling, tangled network of species interactions. Data on the host-virus network are available from several sources, which use different naming conventions and often report metadata in different levels of detail. VIRION is a new database that combines several of these existing data sources, reconciles taxonomy to a single consistent backbone, and reports metadata in a format designed by and for virologists. Researchers can use VIRION to easily answer questions like “Can any fish viruses infect humans?” or “Which bats host coronaviruses?” or to build more advanced predictive models, making it an unprecedented step toward a full inventory of the global virome.« less
  8. Abstract Background

    Fire strongly affects animals’ behavior, population dynamics, and environmental surroundings, which in turn are likely to affect their immune systems and exposure to pathogens. However, little work has yet been conducted on the effects of wildfires on wildlife disease. This research gap is rapidly growing in importance because wildfires are becoming globally more common and more severe, with unknown impacts on wildlife disease and unclear implications for livestock and human health in the future.


    Here, we discussed how wildfires could influence susceptibility and exposure to infection in wild animals, and the potential consequences for ecology and public health. In our framework, we outlined how habitat loss and degradation caused by fire affect animals’ immune defenses, and how behavioral and demographic responses to fire affect pathogen exposure, spread, and maintenance. We identified relative unknowns that might influence disease dynamics in unpredictable ways (e.g., through altered community composition and effects on free-living parasites). Finally, we discussed avenues for future investigations of fire-disease links.


    We hope that this review will stimulate much-needed research on the role of wildfire in influencing wildlife disease, providing an important source of information on disease dynamics in the wake of future wildfires and other natural disasters, andmore »encouraging further integration of the fields of fire and disease ecology.

    « less