The importance of exotic plantation forest for the New Zealand long-tailed bat (Chalinolobus tuberculatus)

Environmental certification schemes have stimulated increasing interest in biodiversity and its management within exotic plantation forests. These schemes expect management to be scientifically-based, even though little is known about how often, or which, native species use exotic plantation forests. Greater knowledge of the ecology of native species within exotic plantation forests is required to advise management and reduce risks to native species, particularly those that are rare, such as the New Zealand long-tailed bat (Chalinolobus tuberculatus). Long-tailed bats use exotic plantation forests throughout New Zealand but need protection from the impacts of forest management, and particularly clear-fell harvest, that is achievable only through a better understanding of their biology. The consequences of the current reduced re-planting, and the conversion of plantation forests into pasture resulting in smaller forested areas, should not be ignored because they may be associated with reductions in long-tailed bat populations. We review the current knowledge of long-tailed bats' use of exotic plantation forests, and report for the first time which exotic plantations long-tailed bats are known to use. We make recommendations for the design of monitoring programmes to detect long-tailed bats within plantation forests, and for research into the effects of forest management, especially logging, and comment on the likely impacts of reductions in forested areas on long-tailed bats.

Classification of echolocation calls from 14 species of bat by Support Vector Machines and Ensembles of Neural Networks

Calls from 14 species of bat were classified to genus and species using discriminant function analysis (DFA), support vector machines (SVM) and ensembles of neural networks (ENN). Both SVMs and ENNs outperformed DFA for every species while ENNs (mean identification rate – 97%) consistently outperformed SVMs (mean identification rate – 87%). Correct classification rates produced by the ENNs varied from 91% to 100%; calls from six species were correctly identified with 100% accuracy. Calls from the five species of Myotis, a genus whose species are considered difficult to distinguish acoustically, had correct identification rates that varied from 91 – 100%. Five parameters were most important for classifying calls correctly while seven others contributed little to classification performance.

Human vs. machine : identification of bat species from their echolocation calls by humans and by artificial neural networks

Automated remote ultrasound detectors allow large amounts of data on bat presence and activity to be collected. Processing of such data involves identifying bat species from their echolocation calls. Automated species identification has the potential to provide more consistent, predictable, and potentially higher levels of accuracy than identification by humans. In contrast, identification by humans permits flexibility and intelligence in identification, as well as the incorporation of features and patterns that may be difficult to quantify. We compared humans with artificial neural networks (ANNs) in their ability to classify short recordings of bat echolocation calls of variable signal to noise ratios; these sequences are typical of those obtained from remote automated recording systems that are often used in large-scale ecological studies. We presented 45 recordings (1–4 calls) produced by known species of bats to ANNs and to 26 human participants with 1 month to 23 years of experience in acoustic identification of bats. Humans correctly classified 86% of recordings to genus and 56% to species; ANNs correctly identified 92% and 62%, respectively. There was no significant difference between the performance of ANNs and that of humans, but ANNs performed better than about 75% of humans. There was little relationship between the experience of the human participants and their classification rate. However, humans with <1 year of experience performed worse than others. Currently, identification of bat echolocation calls by humans is suitable for ecological research, after careful consideration of biases. However, improvements to ANNs and the data that they are trained on may in future increase their performance to beyond those demonstrated by humans.

Fruit-feeding behaviour and use of olfactory cues by the fruit bat Rousettus leschenaulti: an experimental study

This paper describes the feeding behaviour ofRousettus leschenaulti Desmarest, 1820 on lychees, the preferred cultivated food of this bat in captive conditions. We found that feeding comprised 25–30% of the total activity of these animals in a flight cage and that feeding durations were not significantly different between two sexes. To evaluate the role of odor and vision in foraging behaviour, we provided animals with artificial lychees, real lychees and artificial lychees soaked in the juice of real lychees and we recorded the number of feeding approaches to the different “fruit” types. The results indicated that bats approached real fruit significantly more than artificial fruit, and that the number of approaches to the soaked artificial fruit was also significantly higher than to the unsoaked artificial fruit. There were no significant differences between sexes in approach rates to any “fruit” type. We discuss the role of different sensory cues in the foraging behaviour of these bats and emphasize that the olfactory cue is important in detecting food resources and discriminating between different kinds of food items.

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.

Echolocation call intensity in the aerial hawking bat Eptesicus bottae (Vespertilionidae) studied using stereo videogrammetry

Aerial hawking bats use intense echolocation calls to search for insect prey. Their calls have evolved into the most intense airborne animal vocalisations. Yet our knowledge about call intensities in the field is restricted to a small number of species. We describe a novel stereo videogrammetry method used to study flight and echolocation behaviour, and to measure call source levels of the aerial hawking bat Eptesicus bottae (Vespertilionidae). Bats flew close to their predicted minimum power speed. Source level increased with call duration; the loudest call of E. bottae was at 133 dB peSPL. The calculated maximum detection distance for large flying objects (e.g. large prey, conspecifics) was up to 21 m. The corresponding maximum echo delay is almost exactly the duration of one wing beat in E. bottae and this also is its preferred pulse interval. These results, obtained by using videogrammetry to track bats in the field, corroborate earlier findings from other species from acoustic tracking methods.

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.

The long and short of it: branch lengths and the problem of placing the New Zealand short-tailed bat.

The taxonomic position of the endemic New Zealand bat genus Mystacina has vexed systematists ever since its erection in 1843. Over the years the genus has been linked with many microchiropteran families and superfamilies. Most recent classifications place it in the Vespertilionoidea, although some immunological evidence links it with the Noctilionoidea (=Phyllostomoidea). We have sequenced 402 bp of the mitochondrial cytochrome b gene for M. tuberculata (Gray in Dieffenbach, 1843), and using both our own and published DNA sequences for taxa in both superfamilies, we applied different tree reconstruction methods to find the appropriate phylogeny and different methods of estimating confidence in the parts of the tree. All methods strongly support the classification of Mystacina in the Noctilionoidea. Spectral analysis suggests that parsimony analysis may be misleading for Mystacina's precise placement within the Noctilionoidea because of its long terminal branch. Analyses not susceptible to long-branch attraction suggest that the Mystacinidae is a sister family to the Phyllostomidae. Dating the divergence times between the different taxa suggests that the extant chiropteran families radiated around and shortly after the Cretaceous–Tertiary boundary. We discuss the biogeographical implications of classifying Mystacina within the Noctilionoidea and contrast our result with those classifications placing Mystacina in the Vespertilionoidea, concluding that evidence for the latter is weak.

The effect of recording situation on the echolocation calls of the New Zealand Lesser short-tailed bat (Mystacina tuberculata Gray).

Using a broad‐band recording system (150 Hz‐100 kHz) the echolocation calls of the lesser short‐tailed bat (Mystacina tuberculata) were recorded under three very different situations: free‐flying, flying within a flight cage, and on release from the hand. Calls of bats landing and feeding on a platform in Wellington Zoo were also recorded. Both the lowest frequency and frequency of peak amplitude of calls were significantly affected by the situation under which calls were recorded. Although the calls of free‐flying bats are different from those produced by bats foraging on the ground, it is unlikely that M. tuberculata uses echolocation to locate prey on the ground. No significant differences could be found between the calls emitted by male and female bats, and no consistent relationships were obvious between temporal and spectral call characteristics. There was some evidence to suggest that individual bats could be identified by their echolocation calls.

Echolocation calls of the long tailed bat: a quantitative analysis of types of calls

The echolocation calls of long-tailed bats (Chalinolobus tuberculatus) were recorded in the Eglinton Valley, Fjordland, New Zealand, and digitized for analysis with the signal-processing software. Univariate and multivariate analyses of measure features facilitated a quantitative classification of the calls. Cluster analysis was used to categorize calls into two groups equating to search and terminal buzz calls described qualitatively for other species. When moving from search to terminal phases, the calls decrease in bandwidth, maximum and minimum frequency of call, and duration. Search calls begin with a steep-downward FM sweep followed by a short, less-modulated component. Buzz calls are FM sweeps. Although not found quantitatively, a broad pre-buzz group of calls also was identified. Ambiguity analysis of calls from the three groups shows that search-phrase calls are well suited to resolving the velocity of targets, and hence, identifying moving targets in a stationary clutter. Pre-buzz and buzz calls are better suited to resolving range, a feature that may aid the bats in capture of evasive prey after it has been identified.

Search-phase echolocation calls of the New Zealand lesser short-tailed bat (Mystacina tuberculata) and long-tailed bat (Chalinolobus tuberculatus).

This paper describes the search-phase echolocation calls of lesser short-tailed bats (Mystacina tuberculata) and long-tailed bats (Chalinolobus tuberculatus). Calls were recorded from all three subspecies of short-tailed bat and seven populations of long-tailed bat, three in Northland, two in the central North Island, and two in the lower South Island. The calls were recorded in the field and digitised, then three spectral components and one temporal component of the calls were measured. Calls of the lesser short-tailed bat could be loosely classified into subspecies by means of multivariate discriminant function analysis. Similarly, long-tailed bat calls showed regional variation, and discriminant function analysis was able to fit calls to regional groups with a high rate of success. The significance of the results presented is discussed in terms of the conservation of New Zealand bats and the unique ecology of the lesser short-tailed bat.

A comparison of the performance of a brand of broad-band and several brands of narrow-band bat detectors in two different habitat types.

The use of bat detectors to monitor bat activity is common. Although several papers have compared the performance of different brands, none have dealt with the effect of different habitats nor have they compared narrow- and broad-band detectors. In this study the performance of four brands of ultrasonic bat detector, including three narrowband and one broad-band model, were compared for their ability to detect a 40 kHz continuous sound of variable amplitude along 100 metre transects. Transects were laid out in two contrasting bat habitat types: grassland and forest. Results showed that the different brands of detector differed in their ability to detect the source in terms of maximum and minimum detectable distance of the source. The rate of sound degradation with distance as measured by each brand was also different. Significant differences were also found in the performance of different brands in open grassland versus deep forest. No significant differences were found within any brand of detector. Though not as sensitive as narrow-band detectors, broad-band models hold an advantage in their ability to identify species where several species are found sympatrically.

The Long and Short of It: Branch Lengths and the Problem of Placing the New Zealand Short-Tailed Bat, Mystacina

The taxonomic position of the endemic New Zealand bat genus Mystacina has vexed systematists ever since its erection in 1843. Over the years the genus has been linked with many microchiropteran families and superfamilies. Most recent classifications place it in the Vespertilionoidea, although some immunological evidence links it with the Noctilionoidea (=Phyllostomoidea). We have sequenced 402 bp of the mitochondrial cytochrome b gene for M. tuberculata (Gray in Dieffenbach, 1843), and using both our own and published DNA sequences for taxa in both superfamilies, we applied different tree reconstruction methods to find the appropriate phylogeny and different methods of estimating confidence in the parts of the tree. All methods strongly support the classification of Mystacina in the Noctilionoidea. Spectral analysis suggests that parsimony analysis may be misleading for Mystacina's precise placement within the Noctilionoidea because of its long terminal branch. Analyses not susceptible to long-branch attraction suggest that the Mystacinidae is a sister family to the Phyllostomidae. Dating the divergence times between the different taxa suggests that the extant chiropteran families radiated around and shortly after the Cretaceous-Tertiary boundary. We discuss the biogeographical implications of classifying Mystacina within the Noctilionoidea and contrast our result with those classifications placing Mystacina in the Vespertilionoidea, concluding that evidence for the latter is weak.

Acoustic identification of twelve 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.