Abstract:
Synanthropic bats live in close proximity to humans and domestic animals, creating
opportunities for potential pathogen spillover. We explored environmental correlates
of occurrence for a widely distributed synanthropic African bat, Mops pumilus—a species associated with potential zoonotic viruses—and estimated current and future environmental suitability in the Taita Hills region and surrounding plains in Taita–Taveta
County in southeast Kenya. To project future environmental suitability, we used four
Coupled Model Intercomparison Project Phase 6 general circulation models that
capture temperature and precipitation changes for East Africa. The models were parameterized with empirical capture data of M. pumilus collected from 2016 to 2023,
combined with satellite-based vegetation, topographic, and climatic data to identify
responses to environmental factors. The strongest drivers for current environmental
suitability for M. pumilus were short distance to rivers, higher precipitation during the
driest months, sparse vegetation—often related to urban areas—and low yearly temperature variation. To predict current and future areas suitable for M. pumilus, we created ensemble niche models, which yielded excellent predictive accuracies. Current
suitable environments were located southward from the central and southern Taita
Hills and surrounding plains, overlapping with urban centers with the highest human
population densities in the area. Future projections for 2050 indicated a moderate increase in suitability range in the southern portion of the region and surrounding plains
in human-dominated areas; however, projections for 2090 showed a slight contraction
of environmental suitability for M. pumilus, potentially due to the negative impact of
increased temperatures. These results show how environmental changes are likely to
impact the human exposure risk of bat-borne pathogens and could help public health
officials develop strategies to prevent these risks in Taita–Taveta County, Kenya, and
other parts of Africa.
KEYWORDS
climate change, East Africa, ecological modeling, ensemble prediction, Mops pumilus
