Biology subjects

Burthe, S. J.

Publications and source records attributed to Burthe, S. J..

4 recordsLinked to original sources

bioRxiv2024

Asymptomatic infection and antibody prevalence to co-occurring avian influenza viruses vary substantially between sympatric seabird species following H5N1 outbreaks

Emerging infectious diseases are of major concern to animal and human health. Recent emergence of high pathogenicity avian influenza virus (HPAIV) (H5N1 clade 2.3.4.4b) led to substantial global mortality across a range of host species. Co-occurring species showed marked differences in mortality, generating an urgent need for better epidemiological understanding within affected populations. We therefore tested for antibodies, indicative of previous exposure and recovery, and for active viral infection in apparently healthy individuals (n=350) across five co-occurring seabird species on the Isle of May, Scotland, during 2023, following H5N1 HPAIV associated mortality in the preceding summer. Antibody prevalence to AIV subtypes varied substantially between species, ranging from 1.1% in European shags (Gulosus aristotelis) (to H5) to 78.7% in black-legged kittiwakes (Rissa tridactyla) (to H16 or both H13 and H16), and between 31-41% for three auk species (H5, H16 or both). At least 20.4% of auks had antibodies to an as yet unidentified subtype, suggesting further subtypes circulating in the population. We found low levels of active, but asymptomatic, AIV infection in individuals (1.6-4.5%), but excluded this as H5N1. Our results emphasise the importance of testing healthy individuals to understand the prevalence of co-circulating AIV subtypes in wild populations, and the potential for future reassortment events which could alter virus behaviour and impact.

ecology↗

bioRxiv2024

Density-dependent network structuring within and across wild animal systems

High population density should drive individuals to more frequently share space and interact, producing better-connected spatial and social networks [1-4]. Although this theory is fundamental to our understanding of disease dynamics [2,5-8], it remains unconfirmed how local density generally drives individuals positions within their networks, which reduces our ability to understand and predict density-dependent processes [4,9,10]. Here we provide the first general evidence that density drives greater network connectedness at fine spatiotemporal scales, at the scale of individuals within wild animal populations. We analysed 36 datasets of simultaneous spatial and social behaviour in >58,000 individual animals, spanning 30 species of fish, reptiles, birds, mammals, and insects. 80% of systems exhibited strong positive relationships between local density and network centrality. However, >80% of relationships were nonlinear and 75% became shallower at higher values, signifying that demographic and behavioural processes counteract densitys effects, thereby producing saturating trends [11-15]. Densitys effect was much stronger and less saturating for spatial than social networks, such that individuals become disproportionately spatially connected rather than socially at higher densities. Consequently, ecological processes that depend on spatial connections (e.g. indirect pathogen transmission, resource competition, and territory formation) are likely more density-dependent than those involving social interactions (e.g. direct pathogen transmission, aggression, and social learning). These findings reveal fundamental ecological rules governing societal structuring, with widespread implications. Identifying scaling rules based on processes that generalise across systems, such as these patterns of density dependence, might provide the ability to predict network structures in novel systems.

ecology↗

bioRxiv2022

Components of micro-evolutionary and phenotypic change in seasonal migration versus residence in a wild population

Dissecting joint micro-evolutionary and plastic responses to environmental perturbations fundamentally requires quantifying interacting components of genetic and environmental variation underlying expression of key traits. This ambition is particularly challenging for phenotypically discrete traits where multiscale decompositions are required to handle non-linear transformations of underlying genetic and environmental variation into phenotypic variation, especially when effects have to be estimated from incomplete field observations. We devised a novel joint multistate capture-recapture and quantitative genetic animal model, and fitted this model to full-annual-cycle resighting data from partially migratory European shags (Gulosus aristotelis) to estimate key components of genetic, environmental and phenotypic variance in the ecologically critical discrete trait of seasonal migration versus residence. We demonstrate non-trivial additive genetic variance in latent liability for migration, resulting in estimated micro-evolutionary responses following two episodes of strong survival selection. Yet, underlying additive genetic effects interacted with substantial permanent individual and temporary environmental effects to generate complex non-additive effects, causing large intrinsic gene-by-environment interaction variance in phenotypic expression. Our findings reveal how temporal dynamics of seasonal migration result from combinations of instantaneous micro-evolution and within-individual phenotypic inertia, and highlight how plastic phenotypic variation could expose cryptic genetic variation underlying discrete traits to complex forms of selection.

evolutionary biology↗

bioRxiv2022

Using mechanistic models to highlight research priorities for tick-borne zoonotic diseases: Improving our understanding of the ecology and maintenance of Kyasanur Forest Disease in India

The risk of spillover of zoonotic diseases to humans is changing in response to multiple environmental and societal drivers, particularly in tropical regions where the burden of neglected zoonotic diseases is highest and land use change and forest conversion is occurring most rapidly. In these regions, neglected zoonotic diseases can have significant impacts on poor and marginalised populations in low-resource settings but ultimately receive less attention and funding for research and interventions. As such, effective control measures and interventions are often hindered by a limited ecological evidence base, which results in a limited understanding of epidemiologically relevant hosts or vectors and the processes that contribute to the maintenance of pathogens and spillover to humans. Here, we develop a generalisable next generation matrix modelling framework to better understand the transmission processes and hosts that have the greatest contribution to the maintenance of tick-borne diseases with the aim of improving the ecological evidence base and framing future research priorities for tick-borne diseases. Using this model we explore the relative contribution of different host groups and transmission routes to the maintenance of a neglected zoonotic tick-borne disease, Kyasanur Forest Disease Virus (KFD). The results highlight the potential importance of transovarial transmission and small mammals and birds in maintaining this disease. This contradicts previous hypotheses that primates play an important role influencing the distribution of infected ticks. There is also a suggestion that risk could vary across different habitat types. In light of these results we outline the key knowledge gaps for this system and future research priorities that would aid in informing effective interventions and control measures.

ecology↗