Models of Eucalypt phenology predict bat population flux

Abstract

Fruit bats (Pteropodidae) have received increased attention after the recent emergence of notable viral pathogens of bat origin. Their vagility hinders data collection on abundance and distribution, which constrains modeling efforts and our understanding of bat ecology, viral dynamics, and spillover. We addressed this knowledge gap with models and data on the occurrence and abundance of nectarivorous fruit bat populations at 3 day roosts in southeast Queensland. We used environmental drivers of nectar production as predictors and explored relationships between bat abundance and virus spillover. Specifically, we developed several novel modeling tools motivated by complexities of fruit bat foraging ecology, including: (1) a dataset of spatial variables comprising Eucalypt‐focused vegetation indices, cumulative precipitation, and temperature anomaly; (2) an algorithm that associated bat population response with spatial covariates in a spatially and temporally relevant way given our current understanding of bat foraging behavior; and (3) a thorough statistical learning approach to finding optimal covariate combinations. We identified covariates that classify fruit bat occupancy at each of our three study roosts with 86–93% accuracy. Negative binomial models explained 43–53% of the variation in observed abundance across roosts. Our models suggest that spatiotemporal heterogeneity in Eucalypt‐based food resources could drive at least 50% of bat population behavior at the landscape scale. We found that 13 spillover events were observed within the foraging range of our study roosts, and they occurred during times when models predicted low population abundance. Our results suggest that, in southeast Queensland, spillover may not be driven by large aggregations of fruit bats attracted by nectar‐based resources, but rather by behavior of smaller resident subpopulations. Our models and data integrated remote sensing and statistical learning to make inferences on bat ecology and disease dynamics. This work provides a foundation for further studies on landscape‐scale population movement and spatiotemporal disease dynamics.

Changing resource landscapes and spillover of henipaviruses

“…As such, the results indicate that the density of flying fox roosts, rather than the population density of flying foxes, is associated with HeV spillover. This agrees with the findings of Giles et al ., who found that the presence of more smaller camps was associated with spillover. Similarly, a study on the roost characteristics of P. medius in Bangladesh noted more roosts, but not more bats, in villages reporting NiV cases, and that increased numbers of smaller roosts and human disease were associated with forest fragmentation .…”

“…However, theoretical models provide a range of predictions for the consequences of urban habituation on the distribution of pathogen across bat populations. Resource shifts from habitat loss or resource provisioning that changes flying fox site fidelity and migratory behavior or stopover patterns could also influence HNV prevalence in bat populations and spillover risks . For pathogens with long infectious periods relative to bat movement rates, urban colonization could spread pathogens across new areas near humans and domestic animals.…”

“…In an ecological context, resource provisioning changes patch occupancy times and potentially colony size, which theory predicts would facilitate landscape‐level spread of viruses . In Australia, conflicting associations between flying fox density and spillover have been reported . Smith et al .…”

Climate Change Could Increase the Geographic Extent of Hendra Virus Spillover Risk

“…Empirical evidence suggests that HeV spillover is related to climate by several different mechanisms acting at different temporal and spatial scales. From broad to fine: the spatial and temporal abundance patterns of HeV reservoir hosts, flying foxes, are related to climatic suitability (Martin et al 2016); the spatial dynamics of bats are largely governed by food resources that are dependent on climate (Hudson et al 2010; Giles et al 2016); the levels of HeV shedding may be linked to low food productivity and availability after severe weather events (Plowright et al 2008; McFarlane et al 2011; Páez et al 2017; Peel et al 2017); and lastly HeV survival in microclimates which might facilitate indirect transmission, is also dependent on climate (Martin et al 2015, 2017). …”

Microclimates Might Limit Indirect Spillover of the Bat Borne Zoonotic Hendra Virus

“…Consequently, temperature dependent survival, as estimated here, is more likely to be the best case survival scenario and an overestimate. This means that the poor contribution of HeV survival towards predicting its spillover [11] ■ could be caused by its susceptibility to the conditions that occur in microclimates, and the stronger effect that temperature has on other processes that influence HeV spillover risk like bat densities and Eucalyptus phenology [28, 29] ■ .…”