A continental-scale tool for acoustic identification of European bats

Summary 1. Acoustic methods are used increasingly to survey and monitor bat populations. However, the use of acoustic methods at continental scales can be hampered by the lack of standardized and objective methods to identify all species recorded. This makes comparable continent-wide monitoring difficult, impeding progress towards developing biodiversity indicators, transboundary conservation programmes and monitoring species distribution changes. 2. Here we developed a continental-scale classifier for acoustic identification of bats, which can be used throughout Europe to ensure objective, consistent and comparable species identifications. We selected 1350 full-spectrum reference calls from a set of 15 858 calls of 34 European species, from EchoBank, a global echolocation call library. We assessed 24 call parameters to evaluate how well they distinguish between species and used the 12 most useful to train a hierarchy of ensembles of artificial neural networks to distinguish the echolocation calls of these bat species. 3. Calls are first classified to one of five call-type groups, with a median accuracy of 97·6%. The median species-level classification accuracy is 83·7%, providing robust classification for most European species, and an estimate of classification error for each species. 4. These classifiers were packaged into an online tool, iBatsID, which is freely available, enabling anyone to classify European calls in an objective and consistent way, allowing standardized acoustic identification across the continent. 5. Synthesis and applications. iBatsID is the first freely available and easily accessible continental- scale bat call classifier, providing the basis for standardized, continental acoustic bat monitoring in Europe. This method can provide key information to managers and conservation planners on distribution changes and changes in bat species activity through time.

Recent surveys of bats (Mammalia: Chiroptera) from China. I. Rhinolophidae and Hipposideridae

We conducted surveys of bats in China between 1999 and 2007, resulting in the identification of at least 62 species. In this paper we present data on 19 species, comprising 12 species from the family Rhinolophidae and seven from the Hipposideridae. Rhinolophids captured were Rhinolophus affinis, R. ferrumequinum, R. lepidus, R. luctus, R. macrotis, R. siamensis, R. marshalli, R. rex, R. pearsonii, R. pusillus, R. sinicus and R. stheno. Because of extensive morphological similarities we question the species distinctiveness of R. osgoodi (may be conspecific with R. lepidus), R. paradoxolophus (which may best be treated as a subspecies of R. rex), R. huananus (probably synonymous with R. siamensis), and we are skeptical as to whether R. sinicus is distinct from R. thomasi. Hipposiderids captured were Hipposideros armiger, H. cineraceus, H. larvatus, H. pomona, H. pratti, Aselliscus stoliczkanus and Coelops frithii. Of these species, two rhinolophids (Rhinolophus marshalli and R. stheno) and one hipposiderid (Hipposideros cineraceus) represent new species records for China. We present data on species' ranges, morphology and echolocation call frequencies, as well as some notes on ecology and conservation status. China hosts a considerable diversity of rhinolophid and hipposiderid bats, yet threats to their habitats and populations are substantial.

Vocalizations of the North Island Brown Kiwi (Apteryx mantelli)

Few studies have investigated the vocal communication of ratites, and none has investigated the spectral and temporal structure of vocalizations of Apteryx, the only extant ratite genus in New Zealand. We describe the long-range vocalization (whistle call) and vocal behavior of male and female North Island Brown Kiwi (Apteryx mantelli). Spontaneous calling by seven pairs was recorded in the field over a one-year period. Call notes produced by males were tonal in nature; the fundamental frequency was ~1.5 kHz, with overtones reaching up to ~13.0 kHz. Call notes produced by females contained a series of tightly packed, poorly defined harmonics and consisted of a fundamental frequency of ~0.1 kHz, with overtones reaching ~7.0 kHz. The amplitude within notes of females was concentrated into two prominent formants. Some individuals of pairs exhibited duetting behavior that resulted in alteration of the inter-note interval after the onset of the call of their mate. Our findings draw attention to the uniqueness of the North Island Brown Kiwi's vocalizations, and we uncovered some unexpected structural features that call for further investigation.

Morphology, echolocation and foraging behaviour in two sympatric sibling species of bat (Tylonycteris pachypus and Tylonycteris robustula) (Chiroptera : Vespertilionidae)

We studied the wing morphology, echolocation calls, foraging behaviour and flight speed of Tylonycteris pachypus and Tylonycteris robustula in Longzhou County, South China during the summer (June–August) of 2005. The wingspan, wing loading and aspect ratio of the two species were relatively low, and those of T. pachypus were lower compared with T. robustula. The echolocation calls of T. pachypus and T. robustula consist of a broadband frequency modulated (FM) sweep followed by a short narrowband FM sweep. The dominant frequency of calls of T. pachypus was 65.1 kHz, whereas that of T. robustula was 57.7 kHz. The call frequencies (including highest frequency of the call, lowest frequency of the call and frequency of the call that contained most energy) of T. pachypus were higher than those of T. robustula, and the pulse duration of the former was longer than that of the latter. The inter-pulse interval and bandwidth of the calls were not significantly different between the two species. Tylonycteris pachypus foraged in more complex environments than T. robustula, although the two species were both netted in edge habitats (around trees or houses), along pathways and in the tops of trees. Tylonycteris pachypus flew slower (straight level flight speed, 4.3 m s−1) than T. robustula (straight level flight speed, 4.8 m s−1). We discuss the relationship between wing morphology, echolocation calls, foraging behaviour and flight speed, and demonstrate resource partitioning between these two species in terms of morphological and behavioural factors.

Echolocation calls, wing shape, diet and phylogenetic diagnosis of the endemic Chinese bat Myotis pequinius

We describe the echolocation calls, flight morphology and diet of the endemic Chinese bat Myotis pequinius Thomas, 1908. Orientation calls are broadband, and reach low terminal frequencies. Diet comprised 80% beetles by volume. Wing shape and call design suggest that the bats fly in cluttered habitats, and the possession of moderately long ears and the dietary composition imply they forage at least sometimes by gleaning. Myotis pequinius resembles a larger Oriental version of the western Palaearctic species M. nattereri. Phylogenetic analysis based on sequences of the cytochrome b gene of mitochondrial DNA (1,140 base pairs) from a range of Palaearctic Myotis species confirmed that M. pequinius is close to the nattereri group, and is a sister-species to the eastern Palaearctic M. bombinus. One bat sequenced from China could not be identified from available species descriptions. It was smaller than M. pequinius, and also differed from it in sequence divergence by 6.7%, suggesting the existence of additional, cryptic taxonomic diversity in this group. Our phylogenetic analysis also supports the recognition of M. schaubi as a species distinct from M. nattereri in Transcaucasia and south-western Asia. Myotis nattereri tschuliensis is more closely related to M. schaubi than to M. nattereri, and is best considered either as a subspecies of M. schaubi, or possibly as a distinct species.

Phylogenetics of small horseshoe bats from east Asia based on mitochondrial DNA sequence variation

We undertook analyses of mitochondrial DNA gene sequences and echolocation calls to resolve phylogenetic relationships among the related bat taxa Rhinolophus pusillus (sampled across China), R. monoceros (Taiwan), R. cornutus (main islands of Japan), and R. c. pumilus (Okinawa, Japan), Phylogenetic trees and genetic divergence analyses were constructed by combining new complete mitochondrial cytochrome-b gene sequences and partial mitochondrial control region sequences with published sequences. Our work showed that these 4 taxa formed monophyletic groups in the phylogenetic tree. However, low levels of sequence divergence among the taxa, together with similarities in body size and overlapping echolocation call frequencies, point to a lack of taxonomic distinctiveness. We therefore suggest that these taxa are better considered as geographical subspecies rather than distinct species, although this should not diminish the conservation importance of these island populations, which are important evolutionarily significant units. Based on our findings, we suggest that the similarities in body size and echolocation call frequency in these rhinolophids result from their recent common ancestry, whereas similarities in body size and call frequency with R. hipposideros of Europe are the result of convergent evolution.

Identification of New Zealand bats in flight from analysis of echolocation calls by artificial neural networks.

Time-expanded and heterodyned echolocation calls of the New Zealand long-tailed Chalinolobus tuberculatus and lesser short-tailed bat Mystacina tuberculata were recorded and digitally analysed. Temporal and spectral parameters were measured from time-expanded calls and power spectra generated for both time-expanded and heterodyned calls. Artificial neural networks were trained to classify the calls of both species using temporal and spectral parameters and power spectra as input data. Networks were then tested using data not previously seen. Calls could be unambiguously identified using parameters and power spectra from time-expanded calls. A neural network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 40 kHz (the frequency with the most energy of the fundamental of C. tuberculatus call), could identify 99% and 84% of calls of C. tuberculatus and M. tuberculata, respectively. A second network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 27 kHz (the frequency with the most energy of the fundamental of M. tuberculata call), could identify 34% and 100% of calls of C. tuberculatus and M. tuberculata, respectively. This study represents the first use of neural networks for the identification of bats from their echolocation calls. It is also the first study to use power spectra of time-expanded and heterodyned calls for identification of chiropteran species. The ability of neural networks to identify bats from their echolocation calls is discussed, as is the ecology of both species in relation to the design of their echolocation calls.

Acoustic identification of 12 species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.