Lek-associated movement of a putative Ebolavirus reservoir, the hammer-headed fruit bat (Hypsignathus monstrosus), in northern Republic of Congo

Spaceborne and UAV-LiDAR reveal hammer-headed bat preference for intermediate canopy height and diverse structure in a Central African rainforest

BACKGROUND

Animals with key ecological roles, such as seed-dispersing fruit bats, rely to varying degrees on habitat structure to indicate the locations of resources and risks.

METHODS

To understand how variation in vegetation structure influences fruit bat habitat selection, we related movement steps of hammer-headed bats (Hypsignathus monstrosus) to attributes of canopy height, vertical and horizontal vegetation structure, and habitat type in a mature rainforest of southern Cameroon. Vegetation structural metrics were measured with UAV-LiDAR at 10 m resolution for a 25 km2 study area. Because bats frequently moved outside the study area, we also characterized vegetation height and horizontal complexity over the full extent of bat movement trajectories by upscaling UAV-LiDAR measurements using primarily GEDI LiDAR data.

RESULTS

At the site level, hammer-headed bats preferred areas of intermediate canopy height (13.9-32.0 m) close to large canopy gaps (≥ 500 m2). Individual bats varied in selection for vertical vegetation complexity, distance to smaller canopy gaps (≥ 50 m2) and plant volume density of intermediate vegetation strata (10-20 m). Over the full extent of movement trajectories, hammer-headed bats consistently preferred intermediate canopy height, and areas closer to canopy gaps. At both spatial extents, bats moved the shortest distances in swamp habitats dominated by Raphia palms. These behaviors indicate the use of forest types that vary structurally, with a preference for open airspace during foraging or moving among resources, and for dense swamp vegetation during roosting and resting periods. In addition, most bats regularly made long flights of up to 17.7 km shortly after sunset and before sunrise and limited their movements to three or fewer destinations throughout the tracking period.

CONCLUSIONS

These results highlight the importance of structurally diverse landscapes for the nightly movements of hammer-headed bats. Our results show how remote sensing methods and animal tracking data can be integrated to understand habitat selection and movement behavior in tropical ecosystems.

Using serosurveys to optimize surveillance for zoonotic pathogens

Zoonotic pathogens pose a significant risk to human health, with spillover into human populations contributing to chronic disease, sporadic epidemics, and occasional pandemics. Despite the widely recognized burden of zoonotic spillover, our ability to identify which animal populations serve as primary reservoirs for these pathogens remains incomplete. This challenge is compounded when prevalence reaches detectable levels only at specific times of year. In these cases, statistical models designed to predict the timing of peak prevalence could guide field sampling for active infections. Thus, we develop a general model that leverages routinely collected serosurveillance data to optimize sampling for elusive pathogens by predicting time windows of peak prevalence. Using simulated data sets, we show that our methodology reliably identifies times when pathogen prevalence is expected to peak. Then, we demonstrate an implementation of our method using publicly available data from two putative Ebolavirus reservoirs, straw-colored fruit bats (Eidolon helvum) and hammer-headed bats (Hypsignathus monstrosus). We envision our method being used to guide the planning of field sampling to maximize the probability of detecting active infections, and in cases when longitudinal data is available, our method can also yield predictions for the times of year that are most likely to produce future spillover events. The generality and simplicity of our methodology make it broadly applicable to a wide range of putative reservoir species where seasonal patterns of birth lead to predictable, but potentially short-lived, pulses of pathogen prevalence.

Foraging and mating behaviors of Hypsignathus monstrosus at the bat-human interface in a central African rainforest

Studying wildlife space use in human-modified environments contributes to characterize wildlife-human interactions to assess potential risks of zoonotic-pathogens transmission, and to pinpoint conservation issues. In central African rainforests with human dwelling and activities, we conducted a telemetry study on a group of males of Hypsignathus monstrosus, a lek-mating fruit bat identified as a potential maintenance host for Ebola virus. During a lekking season in 2020, we investigated the foraging-habitat selection and the individual nighttime space use during both mating and foraging activities close to villages and their surrounding agricultural landscape. At night, marked individuals strongly selected agricultural lands and more generally areas near watercourses to forage, where they spent more time compared to forest ones. Furthermore, the probability and duration of the presence of bats in the lek during nighttime decreased with the distance to their roost site but remained relatively high within a 10 km radius. Individuals adjusted foraging behaviors according to mating activity by reducing both the overall time spent in foraging areas and the number of forest areas used to forage when they spent more time in the lek. Finally, the probability of a bat revisiting a foraging area in the following 48 hours increased with the previous time spent in that foraging area. These behaviors occurring close to or in human-modified habitats can trigger direct and indirect bat-human contacts, which could thus facilitate pathogen transmission such as Ebola virus.

Mapping of Ebola virus spillover: Suitability and seasonal variability at the landscape scale

The unexpected Ebola virus outbreak in West Africa in 2014 involving the Zaire ebolavirus made clear that other regions outside Central Africa, its previously documented niche, were at risk of future epidemics. The complex transmission cycle and a lack of epidemiological data make mapping areas at risk of the disease challenging. We used a Geographic Information System-based multicriteria evaluation (GIS-MCE), a knowledge-based approach, to identify areas suitable for Ebola virus spillover to humans in regions of Guinea, Congo and Gabon where Ebola viruses already emerged. We identified environmental, climatic and anthropogenic risk factors and potential hosts from a literature review. Geographical data layers, representing risk factors, were combined to produce suitability maps of Ebola virus spillover at the landscape scale. Our maps show high spatial and temporal variability in the suitability for Ebola virus spillover at a fine regional scale. Reported spillover events fell in areas of intermediate to high suitability in our maps, and a sensitivity analysis showed that the maps produced were robust. There are still important gaps in our knowledge about what factors are associated with the risk of Ebola virus spillover. As more information becomes available, maps produced using the GIS-MCE approach can be easily updated to improve surveillance and the prevention of future outbreaks.

Ebola virus disease is a highly pathogenic disease transmitted from wildlife to humans. It was first described in 1976 and its distribution remained restricted to Central Africa until 2014, when an outbreak in West Africa, causing more than 28,000 cases and more than 11,000 deaths, took place. Anthropogenic factors, such as bushmeat hunting, trade and consumption, and environmental and climatic factors, may promote the contact between humans and infected animals, such as bats, primates and duikers, increasing the risk of virus transmission to the human population. In this study, we used the spatial multicriteria evaluation framework to gather all available information on risk factors and animal species susceptible to infection, and produce maps of areas suitable for Ebola virus spillover in regions in Guinea, Congo and Gabon. The resulting maps highlighted high spatial and temporal variability in the suitability for Ebola virus spillover. Data from reported cases of Ebola virus transmission from wild animals to humans were used to validate the maps. The approach developed is capable of integrating a wide diversity of risk factors, and provides a flexible and simple tool for surveillance, which can be updated as more data and knowledge on risk factors become available.

Bat-borne viruses in Africa: a critical review

In Africa, bat-borne zoonoses emerged in the past few decades resulting in large outbreaks or just sporadic spillovers. In addition, hundreds of more viruses are described without any information on zoonotic potential. We discuss important characteristics of bats including bat biology, evolution, distribution and ecology that not only make them unique among most mammals but also contribute to their potential as viral reservoirs. The detection of a virus in bats does not imply that spillover will occur and several biological, ecological and anthropogenic factors play a role in such an event. We summarize and critically analyse the current knowledge on African bats as reservoirs for corona-, filo-, paramyxo- and lyssaviruses. We highlight that important information on epidemiology, bat biology and ecology is often not available to make informed decisions on zoonotic spillover potential. Even if knowledge gaps exist, it is still important to recognize the role of bats in zoonotic disease outbreaks and implement mitigation strategies to prevent exposure to infectious agents including working safely with bats. Equally important is the crucial role of bats in various ecosystem services. This necessitates a multidisciplinary One Health approach to close knowledge gaps and ensure the development of responsible mitigation strategies to not only minimize risk of infection but also ensure conservation of the species.