Body condition metrics are widely used to infer animal health and to assess costs of parasite infection. Since parasites harm their hosts, ecologists might expect negative relationships between infection and condition in wildlife, but this assumption is challenged by studies showing positive or null condition–infection relationships. Here, we outline common condition metrics used by ecologists in studies of parasitism, and consider mechanisms that cause negative, positive, and null condition–infection relationships in wildlife systems. We then perform a meta‐analysis of 553 condition–infection relationships from 187 peer‐reviewed studies of animal hosts, analysing observational and experimental records separately, and noting whether authors measured binary infection status or intensity. Our analysis finds substantial heterogeneity in the strength and direction of condition–infection relationships, a small, negative average effect size that is stronger in experimental studies, and evidence for publication bias towards negative relationships. The strongest predictors of variation in study outcomes are host thermoregulation and the methods used to evaluate body condition. We recommend that studies aiming to assess parasite impacts on body condition should consider host–parasite biology, choose condition measures that can change during the course of infection, and employ longitudinal surveys or manipulate infection status when feasible.
Old World fruit bats (Chiroptera: Pteropodidae) provide critical pollination and seed dispersal services to forest ecosystems across Africa, Asia, and Australia. In each of these regions, pteropodids have been identified as natural reservoir hosts for henipaviruses. The genus Henipavirus includes Hendra virus and Nipah virus, which regularly spill over from bats to domestic animals and humans in Australia and Asia, and a suite of largely uncharacterized African henipaviruses. Rapid change in fruit bat habitat and associated shifts in their ecology and behavior are well documented, with evidence suggesting that altered diet, roosting habitat, and movement behaviors are increasing spillover risk of bat-borne viruses. We review the ways that changing resource landscapes affect the processes that culminate in cross-species transmission of henipaviruses, from reservoir host density and distribution to within-host immunity and recipient host exposure. We evaluate existing evidence and highlight gaps in knowledge that are limiting our understanding of the ecological drivers of henipavirus spillover. When considering spillover in the context of land-use change, we emphasize that it is especially important to disentangle the effects of habitat loss and resource provisioning on these processes, and to jointly consider changes in resource abundance, quality, and composition.
Urban development can alter resource availability, land use, and community composition, which, in turn, influences wildlife health. Generalizable relationships between wildlife health and urbanization have yet to be quantified and could vary across different measures of health and among species. We present a phylogenetic meta‐analysis of 516 comparisons of the toxicant loads, parasitism, body condition, or stress of urban and non‐urban wildlife populations reported in 106 studies spanning 81 species in 30 countries. We found a small but significant negative relationship between urbanization and wildlife health, driven by considerably higher toxicant loads and greater parasite abundance, greater parasite diversity, and/or greater likelihood of infection by parasites transmitted through close contact. Invertebrates and amphibians were particularly affected, with urban populations having higher toxicant loads and greater physiological stress than their non‐urban counterparts. We also found strong geographic and taxonomic bias in research effort, highlighting future research needs. Our results suggest that some types of health risks are more pronounced for wildlife in urban areas, which could have important implications for conservation.
Bats are reservoirs of emerging viruses that are highly pathogenic to other mammals, including humans. Despite the diversity and abundance of bat viruses, to date they have not been shown to harbor exogenous retroviruses. Here we report the discovery and characterization of a group of koala retrovirus-related (KoRV-related) gammaretroviruses in Australian and Asian bats. These include the Hervey pteropid gammaretrovirus (HPG), identified in the scat of the Australian black flying fox (Pteropus alecto), which is the first reproduction-competent retrovirus found in bats. HPG is a close relative of KoRV and the gibbon ape leukemia virus (GALV), with virion morphology and Mn2+-dependent virion-associated reverse transcriptase activity typical of a gammaretrovirus. In vitro, HPG is capable of infecting bat and human cells, but not mouse cells, and displays a similar pattern of cell tropism as KoRV-A and GALV. Population studies reveal the presence of HPG and KoRV-related sequences in several locations across northeast Australia, as well as serologic evidence for HPG in multiple pteropid bat species, while phylogenetic analysis places these bat viruses as the basal group within the KoRV-related retroviruses. Taken together, these results reveal bats to be important reservoirs of exogenous KoRV-related gammaretroviruses.
Emerging diseases caused by coronaviruses of likely bat origin (e.g. SARS, MERS, SADS and COVID-19) have disrupted global health and economies for two decades. Evidence suggests that some bat SARS-related coronaviruses (SARSr-CoVs) could infect people directly, and that their spillover is more frequent than previously recognized. Each zoonotic spillover of a novel virus represents an opportunity for evolutionary adaptation and further spread; therefore, quantifying the extent of this "hidden" spillover may help target prevention programs. We derive biologically realistic range distributions for known bat SARSr-CoV hosts and quantify their overlap with human populations. We then use probabilistic risk assessment and data on human-bat contact, human SARSr-CoV seroprevalence, and antibody duration to estimate that ~400,000 people (median: ~50,000) are infected with SARSr-CoVs annually in South and Southeast Asia. These data on the geography and scale of spillover can be used to target surveillance and prevention programs for potential future bat-CoV emergence.
Emerging diseases caused by coronaviruses of likely bat origin (e.g., SARS, MERS, SADS, COVID-19) have disrupted global health and economies for two decades. Evidence suggests that some bat SARS-related coronaviruses (SARSr-CoVs) could infect people directly, and that their spillover is more frequent than previously recognized. Each zoonotic spillover of a novel virus represents an opportunity for evolutionary adaptation and further spread; therefore, quantifying the extent of this spillover may help target prevention programs. We derive current range distributions for known bat SARSr-CoV hosts and quantify their overlap with human populations. We then use probabilistic risk assessment and data on human-bat contact, human viral seroprevalence, and antibody duration to estimate that a median of 66,280 people (95% CI: 65,351–67,131) are infected with SARSr-CoVs annually in Southeast Asia. These data on the geography and scale of spillover can be used to target surveillance and prevention programs for potential future bat-CoV emergence.
Zoonotic spillover and subsequent disease emergence cause significant, long-lasting impacts on our social, economic, environmental and political systems. Identifying and averting spillover transmission is crucial for preventing outbreaks and mitigating infectious disease burdens. Investigating the processes that lead to spillover fundamentally involves interactions between animals, humans, pathogens and the environments they inhabit. Accordingly, it is recognized that transdisciplinary approaches provide a more holistic understanding of spillover phenomena. To characterize the discourse about spillover within and between disciplines, we conducted a review of review papers about spillover from multiple disciplines. We systematically searched and screened literature from several databases to identify a corpus of review papers from ten academic disciplines. We performed qualitative content analysis on text where authors described either a spillover pathway, or a conceptual gap in spillover theory. Cluster analysis of pathway data identified nine major spillover processes discussed in the review literature. We summarized the main features of each process, how different disciplines contributed to them, and identified specialist and generalist disciplines based on the breadth of processes they studied. Network analyses showed strong similarities between concepts reviewed by 'One Health' disciplines (e.g.
Anthropogenic landscape modification such as urbanization can expose wildlife to toxicants, with profound behavioural and health effects. Toxicant exposure can alter the local transmission of wildlife diseases by reducing survival or altering immune defence. However, predicting the impacts of pathogens on wildlife across their ranges is complicated by heterogeneity in toxicant exposure across the landscape, especially if toxicants alter wildlife movement from toxicant-contaminated to uncontaminated habitats. We developed a mechanistic model to explore how toxicant effects on host health and movement propensity influence range-wide pathogen transmission, and zoonotic exposure risk, as an increasing fraction of the landscape is toxicant-contaminated. When toxicant-contaminated habitat is scarce on the landscape, costs to movement and survival from toxicant exposure can trap infected animals in contaminated habitat and reduce landscape-level transmission. Increasing the proportion of contaminated habitat causes host population declines from combined effects of toxicants and infection. The onset of host declines precedes an increase in the density of infected hosts in contaminated habitat and thus may serve as an early warning of increasing potential for zoonotic spillover in urbanizing landscapes. These results highlight how sublethal effects of toxicants can determine pathogen impacts on wildlife populations that may not manifest until landscape contamination is widespread.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.