A new species of the Miniopterus australis species complex (Chiroptera: Miniopteridae) from the Western Ghats, India

The genus Miniopterus is highly diverse in cryptic species. Based on integrated approaches of morphometrics, echolocation call analysis, and molecular phylogenetics, we present evidence of a hitherto undescribed species, Srini's Bent-winged bat Miniopterus srinii sp. nov.. The new species, found in the Western Ghats of southern Karnataka, India, closely resembles the Small Bent-winged bat Miniopterus pusillus, found elsewhere in Karnataka, Kerala, and Tamil Nadu, India. Although it shows external similarity with Miniopterus pusillus sensu stricto from the Nicobar Islands, the new species is relatively larger and distinct in craniodental measurements and echolocation call parameters, despite slight overlaps. Importantly, Miniopterus srinii exhibits morphological convergence with Miniopterus pusillus as despite similarities in morphologies, there is a significant genetic distance of 10.84 ± 0.22%. The new cryptic species shares distribution with Miniopterus phillipsi and Miniopterus pusillus in the Western Ghats, further highlighting the need to study both the genus' cryptic diversity, and the region's conservation importance.

Identifying priority areas for bat conservation in the Western Ghats mountain range, peninsular India

Understanding patterns of species distribution and diversity plays a vital role in biodiversity conservation. Such documentation is frequently lacking for bats, which are relatively little studied and often threatened. The Western Ghats biodiversity hotspot in peninsular India is a bat hotspot with 63 species. We conducted a comprehensive bat survey across the southern Western Ghats and used maximum entropy modeling (MaxEnt) to model the potential distribution of 37 bat species for which sufficient data were available. We generated binary maps of each species using species-specific thresholds to estimate suitable habitat areas and overlaid binary maps of species to produce bat hotspots (we use the term “bat hotspot” for regions that were suitable for more than 25 bat species). We also estimated species richness across protected area networks in the southern Western Ghats to assess the level of protection. The highest levels of species richness were found mainly along the southmost Periyar–Agastyamalai landscape. The study also identified a 1,683 km2 area of potential bat hotspot and 726 km2 (43%) of the total bat hotspots are currently within the protected area network. However, more than 50% of suitable habitats for each of the 37 species remain unprotected. Therefore, conservation decisions are needed to take into account both bat hotspots and species with restricted distributions.

Taxonomic and ecological notes on some poorly known bats (Mammalia: Chiroptera) from Meghalaya, India

The chiropteran diversity of Meghalaya State is very high with 65 reported species.  Taxonomic and ecological information on many of these bat species, however, are scant or largely outdated.  We reinforce the records on five poorly known bat species in Meghalaya, viz., Megaerops niphanae, Myotis pilosus, Kerivoula kachinensis, Miniopterus magnater, & Miniopterus pusillus, critically evaluate their taxonomic assignment, and provide detailed morphometric data for further comparisons.  For three of these species, we also provide echolocation call data that are reported for the first time in India.  Together, these new data highlight the need for a more robust and critical examination of the rich bat fauna existing in the foothills of the Himalaya.

Echolocation calls of some bats of Gujarat, India

Bats play an important role by providing ecosystem services including pollination, seed dispersal, forest regeneration and insect pest control and also serve as bio-indicators. In the present study, we present an acoustic guide to the calls of nine species of bats from Gujarat belonging to families Rhinopomatidae (Rhinopoma hardwickii, Rhinopoma microphyllum), Emballonuridae (Taphozous melanopogon, Taphozous longimanus and Taphozous nudiventris), Rhinolophidaea (Rhinolophus lepidus), Hipposideridae (Hipposideros galeritus) and Vespertilionidae (Scotophilus heathii, Pipistrellus ceylonicus). Discriminant function analysis was used to classify the bat calls to the species level using leave-one-out cross validation. Analysis was carried out separately for constant frequency (CF) calls and frequency-modulated (FM) calls. Bats echolocating with CF calls were classified with 100% success, while in the case of FM calls, the calls were classified with 66.7% accuracy. In species-rich communities, care should be taken while using echolocation calls to identify bats producing FM calls. More such call libraries of bats from other parts of India are needed for non-invasive documentation of chiropteran fauna in different biogeographic zones.

Prioritizing surveillance of Nipah virus in India

The 2018 outbreak of Nipah virus in Kerala, India, highlights the need for global surveillance of henipaviruses in bats, which are the reservoir hosts for this and other viruses. Nipah virus, an emerging paramyxovirus in the genus Henipavirus, causes severe disease and stuttering chains of transmission in humans and is considered a potential pandemic threat. In May 2018, an outbreak of Nipah virus began in Kerala, > 1800 km from the sites of previous outbreaks in eastern India in 2001 and 2007. Twenty-three people were infected and 21 people died (16 deaths and 18 cases were laboratory confirmed). Initial surveillance focused on insectivorous bats (Megaderma spasma), whereas follow-up surveys within Kerala found evidence of Nipah virus in fruit bats (Pteropus medius). P. medius is the confirmed host in Bangladesh and is now a confirmed host in India. However, other bat species may also serve as reservoir hosts of henipaviruses. To inform surveillance of Nipah virus in bats, we reviewed and analyzed the published records of Nipah virus surveillance globally. We applied a trait-based machine learning approach to a subset of species that occur in Asia, Australia, and Oceana. In addition to seven species in Kerala that were previously identified as Nipah virus seropositive, we identified at least four bat species that, on the basis of trait similarity with known Nipah virus-seropositive species, have a relatively high likelihood of exposure to Nipah or Nipah-like viruses in India. These machine-learning approaches provide the first step in the sequence of studies required to assess the risk of Nipah virus spillover in India. Nipah virus surveillance not only within Kerala but also elsewhere in India would benefit from a research pipeline that included surveys of known and predicted reservoirs for serological evidence of past infection with Nipah virus (or cross reacting henipaviruses). Serosurveys should then be followed by longitudinal spatial and temporal studies to detect shedding and isolate virus from species with evidence of infection. Ecological studies will then be required to understand the dynamics governing prevalence and shedding in bats and the contacts that could pose a risk to public health.