Nycteribiid bat flies (Arthropoda, Insecta, Diptera, Nycteribiidae) of Kenya

Bat flies (Diptera: Nycteribiidae and Streblidae) are hematophagous ectoparasites of bats characterized by viviparous pupiparity and generally high host specificity. Nycteribiid bat flies are wingless, morphologically constrained, and are most diverse in the Eastern Hemisphere. Africa hosts approximately 22% of global bat biodiversity and nearly one-third of all African bat species occur in Kenya, one of Africa’s most bat-rich countries. However, records of nycteribiid bat fly diversity in Kenya remain sparse and unconsolidated. This paper combines all past species records of nycteribiid bat flies with records from a survey of 4,255 Kenyan bats across 157 localities between 2006 and 2015. A total of seven nycteribiid genera and 17 species are recorded, with seven species from the recent ‘Bats of Kenya’ surveys representing previously undocumented country records. Host associations and geographic distributions based on all available records are also described. This comprehensive species catalog addresses and further emphasizes the need for similar investigations of nycteribiid biodiversity across Africa

Guild Vertical Stratification and Drivers of Bat Foraging in a Semi-Arid Tropical Region, Kenya

Africa faces significant challenges in reconciling economic and social development while preserving its natural resources. Little is known about the diverse bat community on the continent, particularly in drier ecosystems. A better understanding of the bat community will help improve and inform the management of these ecosystems. Our study aimed to provide detailed information on the main drivers of bat richness and activity at three different heights above the ground in a semi-arid region of Kenya. We assessed how bat activity varied with space and height using acoustic sampling and complementary methods. We sampled 48 sites at ground level and two sites on meteorological masts at 20 m and 35 m above the ground. We recorded more than 20 bat species, including one species of concern for conservation. Our models showed that the use of space varies with bat guild, creating trade-offs in the variables that affect their activity. Low-flying bat species are mostly associated with habitat variables, whereas high-flying species are more dependent on weather conditions. Our study highlights the richness of bat assemblages in semi-arid environments and emphasizes the need for management measures to protect bat diversity in the face of habitat degradation caused by climate change, land management, and development projects.info:eu-repo/semantics/publishedVersio

A revision of pipistrelle-like bats (Mammalia: Chiroptera: Vespertilionidae) in East Africa with the description of new genera and species

Vespertilionidae (class Mammalia) constitutes the largest family of bats, with ~500 described species. Nonetheless, the systematic relationships within this family are poorly known, especially among the pipistrelle-like bats of the tribes Vespertilionini and Pipistrellini. Perhaps as a result of their drab pelage and lack of obvious morphological characters, the genus and species limits of pipistrelle-like bats remain poorly resolved, particularly in Africa, where more than one-fifth of all vesper bat species occur. Further exacerbating the problem is the accelerating description of new species within these groups. In this study, we attempt to resolve the systematic relationships among the pipistrelle-like bats of sub-Saharan Africa and Madagascar and provide a more stable framework for future systematic efforts. Our systematic inferences are based on extensive genetic and morphological sampling of > 400 individuals covering all named genera and the majority of described African pipistrelle-like bat species, focusing on previously unstudied samples of East African bats. Our study corroborates previous work by identifying three African genera in Pipistrellini (Pipistrellus, Scotoecus and Vansonia), none of which is endemic to Africa. However, the situation is more complex in Vespertilionini. With broad taxonomic sampling, we confirm that the genus Neoromicia is paraphyletic, a situation that we resolve by assigning the species of Neoromicia to four genera. Neoromicia is here restricted to Neoromicia zuluensis and allied taxa. Some erstwhile Neoromicia species are transferred into an expanded Laephotis, which now includes both long-eared and short-eared forms. We also erect two new genera, one comprising a group of mostly forest-associated species (many of which have white wings) and the other for the genetically and morphologically unique banana bat. All four of these genera, as recognized here, are genetically distinct, have distinctive bacular morphologies and can be grouped by cranial morphometrics. We also demonstrate that the genus Nycticeinops, until now considered monospecific, includes both Afropipistrellus and the recently named Parahypsugo, thus representing the fifth African genus in Vespertilionini. A sixth genus, Hypsugo, is mostly extra-limital to sub-Saharan Africa. Finally, we describe three new species of pipistrelle-like bats from Kenya and Uganda, uncovered during the course of systematic bat surveys in the region. Such surveys are greatly needed across tropical Africa to uncover further bat diversity.https://academic.oup.com/zoolinneanhj2022Mammal Research InstituteZoology and Entomolog

Bombali Virus in Mops condylurus Bat, Kenya

Bombali virus (genus Ebolavirus) was identified in organs and excreta of an Angolan free-tailed bat (Mops condylurus) in Kenya. Complete genome analysis revealed 98% nucleotide sequence similarity to the prototype virus from Sierra Leone. No Ebola virus-specific RNA or antibodies were detected from febrile humans in the area who reported contact with bats.Peer reviewe

Towards a coordinated strategy for intercepting human disease emergence in Africa

Non peer reviewe

The future of zoonotic risk prediction

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges? This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.Peer reviewe

DarkCideS 1.0, a global database for bats in karsts and caves

Tanalgo, Krizler C., Tabora, John Aries G., de Oliveira, Hernani Fernandes Magalhães, Haelewaters, Danny, Beranek, Chad T., Otálora-Ardila, Aída, Bernard, Enrico, Gonçalves, Fernando, Eriksson, Alan, Donnelly, Melissa, González, Joel Monzón, Ramos, Humberto Fernández, Rivas, Alberto Clark, Webala, Paul W., Deleva, Stanimira, Dalhoumi, Ridha, Maula, Jaycelle, Lizarro, Dennis, Aguirre, Luis F., Bouillard, Nils, Quibod, Ma. Niña Regina M., Barros, Jennifer, Turcios-Casco, Manfredo Alejandro, Martínez, Marcio, Ordoñez-Mazier, Diego Iván, Orellana, José Alejandro Soler, Ordoñez-Trejo, Eduardo J., Ordoñez, Danny, Chornelia, Ada, Lu, Jian Mei, Xing, Chen, Baniya, Sanjeev, Muylaert, Renata L., Dias-Silva, Leonardo Henrique, Ruadreo, Nittaya, Hughes, Alice Catherine (2022): DarkCideS 1.0, a global database for bats in karsts and caves. Scientific Data 9 (1): 155, DOI: 10.1038/s41597-022-01234-4, URL: http://dx.doi.org/10.1038/s41597-022-01234-

The future of zoonotic risk prediction

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges? This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’.NSF BII 2021909; the University of Toronto EEB Fellowship; the Wellcome Trust; the National Institute of Allergy and Infectious Diseases of the National Institutes of Health and the Defense Threat Reduction Agency.http://rstb.royalsocietypublishing.orgam2022Medical Virolog

The bii4africa dataset of faunal and floral population intactness estimates across Africa’s major land uses

Sub-Saharan Africa is under-represented in global biodiversity datasets, particularly regarding the impact of land use on species’ population abundances. Drawing on recent advances in expert elicitation to ensure data consistency, 200 experts were convened using a modified-Delphi process to estimate ‘intactness scores’: the remaining proportion of an ‘intact’ reference population of a species group in a particular land use, on a scale from 0 (no remaining individuals) to 1 (same abundance as the reference) and, in rare cases, to 2 (populations that thrive in human-modified landscapes). The resulting bii4africa dataset contains intactness scores representing terrestrial vertebrates (tetrapods: ±5,400 amphibians, reptiles, birds, mammals) and vascular plants (±45,000 forbs, graminoids, trees, shrubs) in sub-Saharan Africa across the region’s major land uses (urban, cropland, rangeland, plantation, protected, etc.) and intensities (e.g., large-scale vs smallholder cropland). This dataset was co-produced as part of the Biodiversity Intactness Index for Africa Project. Additional uses include assessing ecosystem condition; rectifying geographic/ taxonomic biases in global biodiversity indicators and maps; and informing the Red List of Ecosystems