Author Correction: Ecology, evolution and spillover of coronaviruses from bats.

In the past two decades, three coronaviruses with ancestral origins in bats have emerged and caused widespread outbreaks in humans, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the first SARS epidemic in 2002–2003, the appreciation of bats as key hosts of zoonotic coronaviruses has advanced rapidly. More than 4,000 coronavirus sequences from 14 bat families have been identified, yet the true diversity of bat coronaviruses is probably much greater. Given that bats are the likely evolutionary source for several human coronaviruses, including strains that cause mild upper respiratory tract disease, their role in historic and future pandemics requires ongoing investigation. We review and integrate information on bat–coronavirus interactions at the molecular, tissue, host and population levels. We identify critical gaps in knowledge of bat coronaviruses, which relate to spillover and pandemic risk, including the pathways to zoonotic spillover, the infection dynamics within bat reservoir hosts, the role of prior adaptation in intermediate hosts for zoonotic transmission and the viral genotypes or traits that predict zoonotic capacity and pandemic potential. Filling these knowledge gaps may help prevent the next pandemic

Advances in understanding bat infection dynamics across biological scales

Over the past two decades, research on bat-associated microbes such as viruses, bacteria and fungi has dramatically increased. Here, we synthesize themes from a conference symposium focused on advances in the research of bats and their microbes, including physiological, immunological, ecological and epidemiological research that has improved our understanding of bat infection dynamics at multiple biological scales. We first present metrics for measuring individual bat responses to infection and challenges associated with using these metrics. We next discuss infection dynamics within bat populations of the same species, before introducing complexities that arise in multi-species communities of bats, humans and/or livestock. Finally, we outline critical gaps and opportunities for future interdisciplinary work on topics involving bats and their microbes

Spatial dynamics of pathogen transmission in communally roosting species: Impacts of changing habitats on bat-virus dynamics.

The spatial organization of populations determines their pathogen dynamics. This is particularly important for communally roosting species, whose aggregations are often driven by the spatial structure of their environment. We develop a spatially explicit model for virus transmission within roosts of Australian tree-dwelling bats (Pteropus spp.), parameterized to reflect Hendra virus. The spatial structure of roosts mirrors three study sites, and viral transmission between groups of bats in trees was modelled as a function of distance between roost trees. Using three levels of tree density to reflect anthropogenic changes in bat habitats, we investigate the potential effects of recent ecological shifts in Australia on the dynamics of zoonotic viruses in reservoir hosts. We show that simulated infection dynamics in spatially structured roosts differ from that of mean-field models for equivalently sized populations, highlighting the importance of spatial structure in disease models of gregarious taxa. Under contrasting scenarios of flying-fox roosting structures, sparse stand structures (with fewer trees but more bats per tree) generate higher probabilities of successful outbreaks, larger and faster epidemics, and shorter virus extinction times, compared to intermediate and dense stand structures with more trees but fewer bats per tree. These observations are consistent with the greater force of infection generated by structured populations with less numerous but larger infected groups, and may flag an increased risk of pathogen spillover from these increasingly abundant roost types. Outputs from our models contribute insights into the spread of viruses in structured animal populations, like communally roosting species, as well as specific insights into Hendra virus infection dynamics and spillover risk in a situation of changing host ecology. These insights will be relevant for modelling other zoonotic viruses in wildlife reservoir hosts in response to habitat modification and changing populations, including coronaviruses like SARS-CoV-2

Impact of intense disturbance on the structure and composition of wet-eucalypt forests: A case study from the Tasmanian 2016 wildfires

<div><p>Fire is a key process in eucalypt communities, exerting a strong influence on the composition, structure and functioning of forests. Much of the research on the fire response of temperate, wet-sclerophyll trees in Australia comes from Victoria, where the dominant eucalypt is <i>Eucalyptus regnans</i>. In contrast, central and northern Tasmanian forests, dominated by <i>Eucalyptus delegatensis</i>, are relatively understudied. There is a need to determine whether Tasmanian wet-sclerophyll forests, though the same forest type in name, are functionally different in floristics and response to fire. Here we document the forest community response to a natural wildfire event in Tasmania—using opportunistic before/after control/impact (BACI) data from pre-existing monitoring plots. Uniting pre- and post-fire floristic data, we quantified mortality and regeneration of eucalypt, acacia and other dominant tree species, and tree ferns, <i>Dicksonia antarctica</i>, in response to wildfire. We also evaluated the density of eucalypt and acacia seedling establishment between burnt and unburnt forests, and quantified faunal responses to fire. Despite moderate-to-high intensity burning in patches across the plot, mortality of eucalypts, acacias and tree ferns due to fire were low. By contrast, fire-sensitive rainforest species showed low survival, though were able to persist in unburnt refugia. Eucalypt and acacia seedling regeneration was high in the burnt plot, suggesting that <i>E</i>. <i>delegatensis</i> forests regenerate without stand-replacing fire events. This contrasts to Victorian <i>E</i>. <i>regnans</i> forests, whose persistence is dependent on high-severity stand-replacing events. We also found some group-specific avifaunal and invertebrate responses to the fire event, which are broadly reflective of responses documented in other Victorian-based studies. Our results have implications for Tasmanian wet-forest silvicultural practices, which are based on the principle of stand-replacement after fire. The broader relevance of this work to forest ecology is in demonstrating the serendipitous opportunities that can arise with baseline monitoring plots.</p></div

Results from the invertebrate analysis.

<p>Results from the invertebrate analysis.</p

Live- and dead-tree distribution across the burnt plot.

<p>A) Distribution of live trees before the fire event. B) topographic map of the plot, with colours representing height gradient. C) Fire-severity rating per subplot, where High = Scorching >5 m height and/or crown damage, Moderate = Lack of understory and scorching up to 2 m, Low = Minor scorching on logs and lower trunk. D) Post fire distribution of dead trees. E) Enlarged fire severity map with number of eucalypt (E) and acacia (A) seedlings per subplot. The average number of eucalypt and acacia seedlings for each severity class were as follows- High: 111 and 7, Moderate: 71 and 6, Low: 75 and 3.</p

Frequency of bird detections by site.

<p>Frequency of bird detections by site.</p

Spatial maps of <i>Dicksonia antarctica</i> and unburnt trees within the burnt site.

<p>A) Map of burnt and unburnt <i>D</i>. <i>antarctica</i> clustering at the burnt site, B) Cluster map of unburnt <i>D</i>. <i>antarctica</i> and unburnt trees. Axes represent increments of 20 m, with the total plot size equal to 100 x 100 m (1 hectare). Clusters of unburnt <i>D</i>. <i>antarctica</i> are highlighted with circles.</p

Dose-response and transmission: the nexus between reservoir hosts, environment and recipient hosts.

Dose is the nexus between exposure and all upstream processes that determine pathogen pressure, and is thereby an important element underlying disease dynamics. Understanding the relationship between dose and disease is particularly important in the context of spillover, where nonlinearities in the dose-response could determine the likelihood of transmission. There is a need to explore dose-response models for directly transmitted and zoonotic pathogens, and how these interactions integrate within-host factors to consider, for example, heterogeneity in host susceptibility and dose-dependent antagonism. Here, we review the dose-response literature and discuss the unique role dose-response models have to play in understanding and predicting spillover events. We present a re-analysis of dose-response experiments for two important zoonotic pathogens (Middle East respiratory syndrome coronavirus and Nipah virus), to exemplify potential difficulties in differentiating between appropriate models with small exposure experiment datasets. We also discuss the data requirements needed for robust selection between dose-response models. We then suggest how these processes could be modelled to gain more realistic predictions of zoonotic transmission outcomes and highlight the exciting opportunities that could arise with increased collaboration between the virology and epidemiology disciplines. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.The ALBORADA Trust DARP

Methods used by people to remove bats from buildings.

Attempts to remove bats were common and frequently led to direct contact with bats that could facilitate pathogen exposure. This question allowed for multiple responses from respondents.</p