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Time-expanded echolocation calls were recorded from 29 species of Neotropical bats in lowland moist tropical forest in Trinidad, West Indies with three aims: (1) to describe the echolocation calls of the members of a diverse Neotropical bat community, especially members of the family Phyllostomidae, whose calls are not well documented (2) to investigate whether multivariate analysis of calls allows species and foraging guilds to be identified and (3) to evaluate the use of bat detectors in surveying the phyllostomids of Neotropical forests. The calls of 12 species of the family Phyllostomidae are described here for the first time and a total of 29 species, belonging to five families (Emballonuridae, Mormoopidae, Phyllostomidae, Molossidae and Vespertilionidae) were recorded. Quadratic discriminant function analysis (DFA) was used to obtain classification rates for each one of 11 individual species and for six guilds (based on diet, foraging mode and habitat) comprising 26 species. Overall classification rates were low compared to similar studies conducted in the Palaeotropics. We suggest that this may be due to a combination of ecological plasticity for certain species and a loose relationship between echolocation call shape, fine-grained resource partitioning and resource acquisition in phyllostomids.
The bat fauna of Mozambique is poorly documented. We conducted a series of inventories across the country between 2005 and 2009, resulting in the identification of 50 species from 41 sites. Of these, seven species represent new national records that increase the country total to 67 species. These data include results from the first detailed surveys across northern Mozambique, over an area representing almost 50% of the country. We detail information on new distribution records and measurements of these specimens. Special attention is paid to the Rhinolophidae, because these include several taxa that are currently in a state of taxonomic confusion. Furthermore, we also present some notes on taxonomy, ecology and echolocation calls. Finally, we combine modelled distributions to present predicted species richness across the country. Species richness was lowest across the coastal plain, to the east and far north, and is predicted to increase in association with rising altitude and higher topographic unevenness of the landscape.
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