Ebola spillover correlates with bat diversity

Some of the world’s deadliest diseases and greatest public health challenges are zoonoses from wildlife, such as Ebola (Ebolavirus). Due to the increasing number of cases in recent years, it has been widely hypothesized that increasing human population densities and anthropogenic disturbance largely explain outbreaks of Ebola virus disease in humans. While studies indicate that ebolaviruses are likely hosted by bats (Chiroptera), their role in outbreaks of the disease remains unclear. We tested whether bat species richness (total and within families), human population density, and anthropogenic disturbance explained the occurrence of Ebola virus disease spillovers within Africa using both generalized linear models and Maxent models. We demonstrate that spillover occurred in areas with high species richness of nycterid bats and low levels of both anthropogenic disturbance and human population density. Outbreaks of Ebola virus disease have devastating effects on people and communities and our results provide an important step toward understanding how and where Ebola virus disease may spill over to human populations.The National Science Foundation Graduate Research Fellowship under Grant No. DGE-1315138 (JTS).http://link.springer.com/journal/103442020-12-01hj2020Mammal Research InstituteZoology and Entomolog

Predictive modeling of cave entrance locations: relationships between surface and subsurface morphology

Cave entrances directly connect the surface and subsurface geomorphology in karst landscapes. Understanding the spatial distribution of these features can help identify areas on the landscape that are critical to flow in the karst groundwater system. Sinkholes and springs are major locations of inflow and outflow from the groundwater system, respectively, however not all sinkholes and springs are equally connected to the main conduit system. Predicting where on the landscape zones of high connectivity exist is a challenge because cave entrances are difficult to detect and imperfectly documented. Wildlife research has a similar issue of understanding the complexities of where a given species is likely to exist on a landscape given incomplete information and presence-only data. Species distribution models can address some of these issues to create accurate predictions of species or event occurrence across the landscape. Here we apply a species distribution model, MaxEnt, to predict cave entrance locations in three geomorphic regions of Kentucky. We built the models with cave locations from the Kentucky Speleological Survey database and landscape predictor variables, including distance from sinkholes, distance from springs, distance from faults, elevation, lithology, slope, and aspect. All three regional models predict cave locations well with the most important variables for predicting cave entrance locations consistent between models. Throughout all three models, sinkholes and springs had the largest influence on the likelihood of cave entrance presence. This unique use of species distribution modeling techniques shows that they are potentially valuable tools to understand spatial patterns of other landscape features that are either ephemeral or difficult to identify using standard techniques

Urbanization may limit impacts of an invasive predator on native mammal diversity

Our understanding of the effects of invasive species on faunal diversity is limited in part because invasions often occur in modified landscapes where other drivers of community diversity can exacerbate or reduce the net impacts of an invader. Furthermore, rigorous assessments of the effects of invasive species on native communities that account for variation in sampling, species-specific detection and occurrence of rare species are lacking. Invasive Burmese pythons (Python molurus bivittatus) may be causing declines in medium- to large-sized mammals throughout the Greater Everglades Ecosystem (GEE); however, other factors such as urbanization, habitat changes and drastic alteration in water flow may also be influential in structuring mammal communities. The aim of this study was to gain an understanding of how mammal communities simultaneously facing invasive predators and intensively human-altered landscapes are influenced by these drivers and their interactions

Rewilding in Southeast Asia: Singapore as a case study

Re-establishing extirpated wildlife—or “rewilding”—is touted as a way to restore biodiversity and ecosystem processes, but we lack real-world examples of this process, particularly in Southeast Asia. Here, we use a decade of aggregated camera trap data, N-mixture occupancy models, and input from local wildlife experts to describe the unassisted recolonization of two native large herbivores in Singapore. Sambar deer (Rusa unicolor) escaped from captivity (in private or public zoos) in the 1970s and contemporary camera trap data show they have only colonized nearby forest fragments and their abundance remains low. Wild pigs (Sus scrofa), in contrast, naturally recolonized by swimming from Malaysia in the 1990s and have rapidly expanded their range and abundance across Singapore. While wild pigs have not recolonized all viable green spaces yet, their trajectory indicates they soon will. We also note that a third ungulate, the muntjac deer (Muntiacus muntjak), was captured in camera trapping in 2014 and 2015 but was never recorded afterward despite increased sampling effort, and thus we do not focus on their presumably unsuccessful recolonization. The divergent rewilding trajectories between sambar deer and wild pigs suggest different conservation outcomes and management requirements. Sambar deer may restore lost plant–animal interactions such as herbivory and seed dispersal without requiring significant management. Wild pigs, in contrast, have reached high numbers rapidly and may require active management to avoid hyperabundance and negative ecological impacts in regions, such as Singapore that lack both hunting and large predators.Nanyang Technological UniversityNational Parks BoardPublished versionThe research was funded by the National Parks Board of Singapore, the Smithsonian Institution's ForestGEO program, Nanyang Technological University, and the University of Queensland (UQ)