Effects of different surfaces on the perception of prey-generated noise by the Indian false vampire bat Megaderma lyra.

The low- and high-frequency components of a rustling sound, created when prey (freshly killed frog) was jerkily pulled on dry and wet sandy floors and asbestos, were recorded and played back to individual Indian false vampire bats (Megaderma lyra). Megaderma lyra responded with flight toward the speakers and captured dead frogs, that were kept as reward. The spectral peaks were at 8.6, 7.1 and 6.8 kHz for the low-frequency components of the sounds created at the dry, asbestos and wet floors, respectively. The spectral peaks for the high-frequency sounds created on the respective floors were at 36.8,27.2 and 23.3 kHz. The sound from the dry floor was more intense than that of from the other two substrata. Prey movements that generated sonic or ultrasonic sounds were both sufficient and necessary for the bats to detect and capture prey. The number of successful prey captures was significantly greater for the dry floor sound, especially to its high-frequency components. Bat-responses were low to the wet floor and moderate to the asbestos floor sounds. The bats did not respond to the sound of unrecorded parts of the tape. Even though the bats flew toward the speakers when the prey generated sounds were played back and captured the dead frogs we cannot rule out the possibility of M. lyra using echolocation to localize prey. However, the study indicates that prey that move on dry sandy floor are more vulnerable to predation by M. lyra.

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 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.

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.

Practical guidelines for planning and implementing fauna translocations

A successful translocation involves many complex factors, including a genetically appropriate source population that can sustain harvest, social and governmental support, assessment of disease transmission risk and a release site with appropriately secure habitat that can support population establishment and persistance. This information is typically discussed during staturory approval processes and can take considerable time. However, following approval, for translocations of most fauna, the initial critical step involves the inherently stressful process of capture, holding, transportation and release. This process is unpredictable and novel, and is especially challenging for wild animals when they are confined in close proximity to conspecifics and humans. In contrast, captive-reared animals have to cope with the unfamiliar challenges of finding food and shelter, along with coping with competition and predation. Little has been written in the scientific literature about the translocation process. This is unsurprising because this process has usually been the realm of skilled practioners, often with animal husbandry backgrounds, rather than research scientists. Highly skilled intuition, observation and the translocation practioner's equivalent of a 'green thumb' often guides the way. However, theory and experimentation, particularly on the effects of stress, is available and this work is invaluable for a successful translocation. Here, we provide a brief description of the translocation process, and discussion of what stress is and how it can be managed. We then provide practical guidelines for the successful translocation of invertebrates, lizards, turtles, passerine birds, marsupials and bats, using examples from Australia and New Zealand.

Adoption of alternative habitats by a threatened, "obligate" forest-dwelling bat in a fragmented landscape

While they are among the most ecologically important animals within forest ecosystems, little is known about how bats respond to habitat loss and fragmentation. The threatened lesser short-tailed bat (Mystacina tuberculata), considered to be an obligate deep-forest species, is one of only 2 extant land mammals endemic to New Zealand; it plays a number of important roles within native forests, including pollination and seed dispersal, and rarely occurs in modified forests. We used radiotelemetry to study the movements, roosting behavior, and habitat use of M. tuberculata within a fragmented landscape comprised of 3 main habitat types: open space (harvested forest and pastoral land), native forests, and exotic pine plantations. We found that the bats had smaller home-range areas and travelled shorter nightly distances than populations investigated previously from contiguous native forest. Furthermore, M. tuberculata occupied all 3 habitat types, with native forest being preferred overall. However, individual variation in habitat selection was high, with some bats preferring exotic plantation and open space over native forest. Roosting patterns were similar to those previously observed in contiguous forest; individual bats often switched between communal and solitary roosts. Our findings indicate that M. tuberculata exhibit some degree of behavioral plasticity that allows them to adapt to different landscape mosaics and exploit alternative habitats. To our knowledge, this is the first such documentation of plasticity in habitat use for a bat species believed to be an obligate forest-dweller.

Four mammal fossil calibrations: Balancing competing palaeontological and molecular considerations

With the introduction of relaxed-clock molecular dating methods, the role of fossil calibration has expanded from providing a timescale, to also informing the models for molecular rate variation across the phylogeny. Here I suggest fossil calibration bounds for four mammal clades, Monotremata (platypus and echidnas), Macropodoidea (kangaroos and potoroos), Caviomorpha-Phiomorpha (South American and African hystricognath rodents), and Chiroptera (bats). In each case I consider sources of uncertainty in the fossil record and provide a molecular dating analysis to examine how the suggested calibration priors are further informed by other mammal fossil calibrations and molecular data.

Bat species comparisons based on external morphology: A test of traditional versus geometric morphometric approaches

External morphology is commonly used to identify bats as well as to investigate flight and foraging behavior, typically relying on simple length and area measures or ratios. However, geometric morphometrics is increasingly used in the biological sciences to analyse variation in shape and discriminate among species and populations. Here we compare the ability of traditional versus geometric morphometric methods in discriminating between closely related bat species – in this case European horseshoe bats (Rhinolophidae, Chiroptera) – based on morphology of the wing, body and tail. In addition to comparing morphometric methods, we used geometric morphometrics to detect interspecies differences as shape changes. Geometric morphometrics yielded improved species discrimination relative to traditional methods. The predicted shape for the variation along the between group principal components revealed that the largest differences between species lay in the extent to which the wing reaches in the direction of the head. This strong trend in interspecific shape variation is associated with size, which we interpret as an evolutionary allometry pattern.

Temporal: The artwork

The interactive artwork Temporal arose from a series of art-science investigations with some of Australia’s leading flying fox ecologists. It was designed as a gently evolving meditation upon the complex, periodic processes that mark Australia’s often irregular seasonal changes. In turn these changes directly govern the migratory movements of Australia’s keystone pollinating mammals - the mega bats (Flying Foxes). Temporal further called attention to our increasing capacity to profoundly disturb these partners within Australia’s complex, life-supporting systems

The efficiency of bounding vampires

Vampire bats, Desmodus rotundus, must maximize their feeding cycle of one blood meal per day by being efficient in the stalking and acquisition of their food. Riskin and Hermanson documented the running gait of the common vampire bat and observed they were efficient at running speeds, using longer stride lengths and thus decreased stride frequency. We obtained preliminary data on gait maintained for up to 10 minutes on a moving treadmill belt at speeds ranging from 0.23 to 0.74 m/s, which spanned a range from walking to running gaits. Bats tended to transition between gaits at about 0.40 m/s. Fourteen bats were studied and included four that were able to walk or run for 10 minutes. There was no significant change in either stride duration or frequency associated with an increase in speed. We estimated O2 consumption and CO2 production both before and 5 minutes after exercise, and found that O2 consumption increased 1 minute and 5 minutes after exercise. CO2 levels increased significantly 1 minute after exercise, but tended back towards pre-exercise level 5 minutes after exercise. Two bats were tested for blood O2, CO2 and pH levels. Interestingly, pH levels fell from 7.3 to about 7.0, indicating lactate accumulation.