The last decades show development of various bat detection techniques. From the basic forms of transforming ultrasound to the audible frequency range of humans a couple of high speed digital storage solutions exist. The different techniques all have an - sometimes huge - impact on how reliable bats are detected and species identified. Only with time-expansion systems as well as with real time recording systems all necessary sound information is available for an objective analysis as well as independent control. Furthermore only these systems are suitable for automated monitoring, if reliable species identification is necessary.
Presence of bats can easily be detected by means of acoustical methods. This works very well due to the fact that bats echolocate between roughly 2 to 20 times a second and thus advertise their presence. Most of these are in the ultrasonic frequency range and can't be heard by humans. Thus, a technical device for call detection has to be utilized. Today many different types and models of these so-called bat detectors exist. They either transform ultrasound to human hearing range and/or store the sound waves for later analysis. Technical differences in these devices have an influence on the reliability of detecting and identifying different bat species. Not all device types are therefore equally well suited for different tasks. We're going to introduce you to the common types of detectors, how they can be used and compare them regarding automated monitoring as well as species identification. The following text is intended as a rough overview. The complexity of bat detection in the field for scientific or consulting work is more complex than shown here.
|Heterodyne-/ FD||Anabat SD2||Time-expansion||Real-time||batcorder|
|amplitude resolution||---||8 bit||16 bit||16 bit|
|sample rate||---||300-350 kHz||500 kHz||500 kHz|
|sound signal||reduced, changed||only zero crossings||slightly changed||original||original|
|storage||extern, analogue||intern||extern, analogue||intern, digital||intern, digital|
|robustness||+, not weatherproof||+, not weatherproof||-, not weatherproof||-/+, not weatherproof||++, weatherproof|
|typ. runtime||< 24 hours||< 12 hours||6 hrs. - 1 week||ca. 1 week|
|usability||simple||medium||medium - hard||simple|
|recording trigger||none / amplitude||amplitude + simple parameters||call analysis|
|accessories, price etc.|
|accessories||self-made||self-made, PDA, remote transfer, ...||self-made||self-made||Setup tools, wind turbine extension, box'ed versione (planned)|
|price (incl. german VAT)||< 400€||ca. 1700€||900-1500€||1700-5000€||2850€|
For a long time the only possibility for distinguishing bats in the field were - apart from capture - heterodyne or frequency division detectors. The acoustic footprint, mainly call frequency and rhythm, supported by optical information (flight style, size, ...) often allow an identification on genus and species level. For many species this is rather reliable if the user is experienced. Yet, in some situations even a id on genus level is impossible. Since the user experience is heavily influencing the results and calls are not archived for cross examination, this subjective method should be rejected if reliable data is needed. It nevertheless allows rapid assessment of bat activity in the field.
The output of a FD detector can be recorded with regular sound hardware. It allows computer based analysis. The reduction of sound data nevertheless has it drawbacks. Especially short calls of less than 10 ms are reduced to very short signals that are hard to examine in more detail. Only a tenth of the orignal sound waves are preserved. For many species, for example of genus Myotis, this is not optimal.
The Anabat SD1 system (and its predecessor) are primarily used in the english speaking countries. It was developed as a long term monitoring system. To reduce the amount of data that has to be stored it implements a zero crossing analysis of the frequency divided signal to only save the wavelengths. Only waves above a selectable threshold are analysed and stored. The recording quality is good enough for basic genus identification. Many species in Europe can not be determined from these signals reliably. It is inferior to time expansion or real-time systems.
In the early 90's these systems where invented in a cooperation of Ahlen and Pettersson. The recordings generally allow a good identification of calls. Yet, the low sample rate and low amplitude resolution in most devices decreases its suitability for species identification in qualitative sampling. It also has a low usability in the field since calls stored on ring memory have to be played back ten times slower than recorded (3s recording - 30 seconds playback) to record them with common audio hardware. You also have to handle the audio recorder simultaneously. While playback is active you can not record further bat passes.
A couple of years ago advances in technology allowed development of consumer devices that allow digital real-time recording of bat calls. Two of the available devices were designed specifically for automated monitoring (Pettersson D500x, ecoObs batcorder). Two other systems have heterodyne/FD detectors coupled for auditory feedback in the field (Pettersson D1000x, Avisoft UltraSoundGate, the second only works if coupled with a PC). These systems have a high recording quality. Thus, identification can be supported by statistical methods.
Even when using the last mentioned real-time recording systems species identification can be a tough process and not always grants unambiguous results. Variability of calls, unknown calls and other influences often don't allow extraction of a species based on calls.