Not yet, we are still working on it! But the other FAQs and Resources elsewhere on the site will answer many user questions. Also, there is contextual help built into SonoBat. To access this, simply locate your computer cursor on a feature in the SonoBat window and press CTRL-H (on a PC) or Command-SHIFT-H (on a Mac) and a pop-up window will appear with information about that feature. Moving your cursor to other features in the SonoBat window will dynamically change the information that displays in the pop-up window. For more information about all the features of SonoBat consider attending a Software Training Course or Field Workshop where students receive intensive training and hands-on use with SonoBat software and bat detector hardware for conducting acoustic surveys. For current information on available training see: http://www.batmanagement.com/Programs/programcentral.html

SonoBat is available for both Windows and Mac platforms, and runs identically on either, plus recordings may be swapped seamlessly between the two.Windows Requirements: At Least Windows 7 operating system, Pentium processor with at least 2 GB of RAM, about 120 MB of free disk space (more will be needed as you collect calls), and a display 1024×786 pixels (xga) or larger.Macintosh Requirements: OS X operating system, Intel processor with at least 2 GB of RAM, and about 120 MB of free disk space (more will be needed as you collect calls).

In addition to the computer, a bat detector capable of recording time expansion sequences or direct-recording, full-spectrum triggered sequences is required. As a basic unit, we recommend the Pettersson D240x time-expansion unit, which has an auto-triggering function that will automatically retain and deliver 10x, time-expanded call sequences directly to a laptop or to a digital recording device and can be used for either active (e.g., voucher calls) or passive (unattended) deployments. Recorded calls can then be downloaded into the SonoBat program for processing and analysis. Other Pettersson units that work well with SonoBat include the D500x, D980x, D1000x and the M500. Specifications about these units are on the Pettersson web site (http://www.batsound.com). In addition, all Binary Acoustic Technology, Elekon, and Wildlife Acoustics full-spectrum, direct-recording detectors are compatible with SonoBat. To compare models and prices or to order equipment, see: http://www.batmanagement.com/Ordering/acoustic/hardware.html

SonoBatLIVE Works with all ultrasound microphones that show up under ‘input’ on your sound prefrences or Binary Acoustic Technology microphones. At this time the important one to note is that the Petterson M500 does not work on the mac version of SonoBat LIVE

You can certainly detect most of the relatively loud tree-bats and free-tailed bats a couple of hundred feet away at least. Some lower intensity, whispering bats like the northern myotis, or Townsend\’s big eared bats, twenty feet (or less) is likely the maximum distance of detection. Moreover, lower frequency echolocation calls will travel farther in air before being attenuated, therefore bats with lower “characteristic frequencies” or Fc values will be more easily detected and will be detected at greater distances, than higher frequency bats. But in general, you need to be within about 100-feet to detect fully formed call pulses within a sequence.But, besides the intensity and frequency, another large part of the complicating factors involves the orientation of the bat toward the microphone. Bats emit their vocalizations with most of the energy directed forward. So the orientation of the bat relative to the microphone will profoundly affect the effective distance of perception. Just exactly where the bat is in the three-dimensional space in relation to the microphone will throw in additional stochasticity. So, if the bat is “off axis” to the best volume of detection of the microphone, calls will be increasingly difficult to record.Of course then there is a subjective assessment of “how good” of a bat pass do you need for confident chances of a species ID. Most biologists who determine occupancy based on acoustic recordings like to see about a dozen “fully formed” pulses in a sequence before rendering a confident decision. Fully-formed bat pulses including those that exhibit a harmonics in the recording and/or those with clear indications of low-intensity portions of the bat call present. Most of the passively recorded files you record will not meet these criteria.To increase the chances of recording high-quality bat passes, invest in a high-quality microphone. Independent testing amongst many biologists specializing in echolocation recording have identified the Pettersson D500x, particularly with the external microphone option, as one of the best detector/microphone combinations on the market today.

SEE UPDATE PAGE #fix

The Maximum Likelihood Estimates provide a probabilistic estimate and have no direct connection to certainty. The MLE calculation depends upon the absolute and relative counts of each species, and if there was a chance of their species count falling within the error rate of other classified species that sometimes get misclassified as those species. In other words, not a strong enough sample of a species\’ result for confident presence. (Of course that\’s the probabilistic result, but manual vetting could confirm or reject presence.) The standard MLE calculation is developed from a confusion matrix of classifier performance. However, such an approach uses idealized results from data used to generate a classifier. The SonoBat MLE calculation uses adjustments based on experience of classifier performance on real-world data sets. When you interpret the SonoBat outputs, you should manually vet any files that come up as an unusual, unexpected, or one of only a few species at a site, manually check to see if it is a confident type of call sequence.

No, the AnaBat uses zero-crossing, which employs a different high-frequency sound conversion principle than full spectrum detectors. Zero-crossing does not acquire sufficient signal information to render full spectrum, high-resolution sonograms.

A divide by ten frequency division essentially discards all but 1 in ten parts of the data and prevents the high resolution analysis that is the foundation of the SonoBat approach. You can use SonoBat to inspect frequency division audio signals, but you will get a very smeary-looking image because you only have 10% of the signal resolution of a full-spectrum signal. So the answer is yes, you can use SonoBat with frequency division, but how well you could use that information for bat identification will be limited, you will have a lack confidence for anything more than sorting of the most basic call characteristics, and you will not have access to the subtle discriminations that SonoBat can support with full-spectrum data.

Not necessarily. There is a greater variety of time expansion detectors available than zero-crossing detectors, some of which have special features and high prices. But a basic unit such as a Pettersson D240x will yield excellent results and has a comparable cost to an AnaBat detector together with the requisite ZCAIM unit needed to interface with a computer. No extra interface unit is needed to use a time expansion detector with SonoBat (see below). Most of the recordings displayed on these web pages and in the SonoBat demo were made using a similar Pettersson D140.

The D240x can accept 12V external gel cell battery, attached to a matching 9V connector (with appropriate polarity; positive-male / negative-female) connected to the D240x with an in-line 1Amp fuse on the positive line from the battery to protect the D240x. A recorder and solar panel charger can be integrated as well. A D240x draws about 20mA of current. For more information see: http://batterystuff.com/batteries/

Event though time-expansion D240x detectors only are in active recurring mode 10% of the time, because 90% of the time is spent expanding and saving the TE recording (i.e., a 1.7-second recording takes 17-seconds to process and save), operationally this doesn’t result in many missed bat passes unless bats are triggering recordings at intervals of less than 1.7 seconds (the standard setting for passive monitoring) they won’t be missed while the unit is processing data. Unfortunately, results are far more disappointing when using a D240x for a mobile survey. Mobile surveys tend to have a lot more noise that trigger recordings. That does not affect a real time recording device like a D500x as it can get right back to recording after a noise-triggered event, but with the D240x that spends ten times as long offloading the data just ends up missing too much.

Most detector microphones are “weather resistant” and will not be damaged by rain. It is especially important to orient microphones so they do not collect water on the sensitive membrane. Wet microphones will not faithfully record high-frequency sound until they dry out. Orienting microphones slightly below horizontal will prevent water from pooling on the membrane. (This includes moisture from condensation, dew, or fog.) Windscreens are effective, but at the expense of sensitivity. Other weatherproofing devices (tubes, reflectors, enclosures) negatively affect call quality, especially with full-spectrum detectors and therefore should not be used. Unfortunately, bat the detectors themselves are not as resistant to moisture. Using an external microphone on an extension cable and housing the detector in a weather

This error occurs when SonoBat attempts to write to its “preference” file, the * .ini configuration file but gets denied from doing so because you lack write permissions to files in that directory. You can try changing the write Attributes of the entire SonoBat Suite directory. Select the option that comes up for “Apply changes to this folder, subfolders and files” when you hit the Apply button after disabling the Read-only option for the directory. If that doesn’t work, Windows still has its security settings on high alert. You could delve into that, or use this work around: Move the SonoBat Suite folder to another location, perhaps where you keep your SonoBat files. Fortunately, Windows should keep track of the program links from your start menu and everything should run fine with SonoBat in a new home beyond the “helpful” purview of User Access Control.

SonoBat is optimized to display 8-second (or shorter) files. Longer duration recordings take more CPU time to process and render and especially to parameterize and classify, and depending on your computer hardware, files in excess of 10-seconds or more may cause the program to crash when displaying, scrubbing, attributing, or batch-processing. You can organize a folder of files by size, and take out the longer duration files to split into two or more shorter duration files using the “save zoomed section” tool. Then archive the longer duration recordings elsewhere, and only keep the “zoomed” sections in your folder.

Ideally, bat detectors should be able to recognize when a bat pass begins and ends and save an individual file that only includes a single pass. But bats are unpredictable and sometimes multiple bats will fly by a detector in sequence, generating longer than expected recordings with multiple bats or species. If your bat detector records files of a fixed length (like most Pettersson models), then select a “File Length” in the “User Profile” of no less than 3 and no more than 5 seconds. Other detectors are capable of making variable length recordings for as long a trigger persists in front of the microphone. Most of these detectors will use a user-defined period of silence after the last bat pulse to stop the recording. A 1 second period might be too short to capture complete sequences of bats with long inter-pulse intervals (e.g., western free-tailed bats or some hoary bat search-phase calls) so the period of silence (i.e., for Wildlife Acoustics models, a “Trigger Window”) should be set to 1.5 or 2 seconds. Wildlife Acoustics models and some other detectors also allow users to elect a “Maximum file Length” to stop a file regardless of the “Trigger Window” setting in the case of constant bat activity. This prevents recordings from being longer than a user-defined maximum, i.e., 5-seconds.

Standard view pulses can be selected several ways. With a call sequence displayed, simply select the turquoise “std view” button and a single call pulse from the sequence (usually near the mid point of the file) will be displayed. Or click one of the 10, 15, 20 or 30 buttons to the left of the “std view” button for a call pulse at one of those resolutions. To select a specific call pulse from a sequence to render in Standard View, use your cursor to draw a box on the pulse and press the “std view” button or one of the standard view resolution numbers. (The box does not have to completely enclose the call pulse when being selected from a sequence displayed in “compressed view.” When a sequence is displayed in “real-time view”

This typically happens on distorted, weak, or otherwise compromised signals that inhibit call-trending and are usually rejected from analysis anyway due to unacceptable call quality. And, although these distorted and noisy calls typically prevent a confident classification, SonoBat still attempts to distinguish bat calls from noise and tallies sequences with call regardless of quality during batch processing to facilitate counting total bat passes.

When learning qualitative bat call analysis, sometimes its preferable to display standard view calls without the automatic call trending and classification results. To change this, select the “set prefs” button in the lower right hand of the main SonoBat window and un-check “enable analysis mode when selecting a call in std view.” Then when a call pulse is rendered in Standard View, the parameterization and classification can be manually selected with the red “enable analysis” button below the main SonoBat window.

The notion behind the Standard View feature is to allow call pulses to be viewed at a fixed time scale so the user always views calls of certain durations at a similar scale. This aids in developing the “sight picture” or “gestalt” for the appearance of different call types from different species, supporting qualitative recognition. The “best resolution” e.g., 10ms, 15ms, 20ms, for a Standard View display will depend upon the duration of the call pulse. A call pulse with a duration that approaches the Standard View resolution may appear “clipped” (i.e., either the leading or trailing edge is truncated in the window when a 9ms call is rendered in a 10ms…

You would get that error if the files are not parsing and instead attempting to build one large file without a break to write shorter parsed files. You may not have the threshold set high enough to be above the signal level in between the bat recording events. Check the instructions on setting the AutoParser’s auto-triggering threshold (push the “?” button to get to that). To successfully parse files, the AutoParser must be able to recognize the signal level when the recorder was not receiving a downloaded recording from the detector, and when it was. The threshold level is how it accomplishes that. When that is working, the AutoParser will find the 17 or 34 second file sections (i.e., time expanded 1.7 sec or 3.4 sec bat passes) and save them to your disk as separate files. These files will be about 1.4 or 3 MB, respectively. If the threshold is set at too low a setting it will continuously read the file in preparation for writing a parsed file to disk, without a break, filling your RAM to capacity until your memory is full. You need to set the threshold so that the read process breaks in between the recorded events. Also, if you are using a Zoom recorder, there is no need to copy the entire file from the Zoom. Just read the file directly from the Zoom to parse, and that way you only save the bat content to your disk. Run the file to parse again with the lower left button set to monitor without saving to set the threshold as per the help instructions: Adjust the threshold setting so that it remains above the recording level between the call sequences that you desire to record, but low enough that it remains triggered during the entirety of the sequence that you want to capture. To find the best threshold setting, run the file that you wish to parse with the AutoParser set to monitor without saving (lower left button). Watch the sound input level bar and note the signal level between call sequences and during call sequences. The AutoParser saves your threshold setting when you close the utility, and will set that level the next time you launch the AutoParser. If the files fly by too quickly on your recording, you can also calibrate your AutoParser by setting up your detector and recorder up as to record, but have the D240x on manual, and just generate some files by manually clicking the start/stop button in the D240x on and off, giving maybe 10 sec between each click. That should give you a file with good separations between signals to make it easy to set your threshold. You want it as low as you can get it without getting triggered in between signals downloaded from the detector; but if too high, it might write multiple files for a single pass. Once you have set the threshold, upon quitting the AutoParser it will remember that setting and use it the next time you launch the AutoParser. If AutoParsing calls from a Zoom H2, consider this improved method.

The AutoParser depends upon a quiescent signal level between bat events, i.e., passes, to recognize and edit out the passes as separate files. The first thing to consider is the audio cord/connection arrangement. The Pettersson outputs the heterodyne signal on the left channel and the time expansion signal on the right channel. The heterodyne signal is continuous (for monitoring passes as clicks), but the TE channel is intermittent in the auto-recording mode. The TE channel is the only data you need for analysis (and for AutoParsing). The SonoBat cords we supply (and directions for making them are in the User’s Guide, also see instructions in this guide) eliminate the HET signal so that the recorded data has a quiescent level between triggered TE signals, and that enables the discrimination of those TE events by the AutoParser. If a standard stereo cable was used, and both HET and TE signals were combined*, then there can be some confounding baseline signal level that makes it difficult to discriminate and parse the TE signals. In such a case you can’t find a sufficiently low threshold setting on the AutoParser to recognize the triggered TE events, and if the discrimination level is set above the noise level it will likely be too high and will only be able to discriminate individual calls rather than entire passes. If that is the case, you can still manually parse out the TE events. It will be a bigger chore, but the data is there, albeit with extra noise. Prepare the recording as a single wave file, then open in a sound editing software like QuickTIme Pro or Acoustica that lets you view (and listen) the waveform and edit out the snippets to save as individual events. If AutoParsing calls from a Zoom H2, consider this improved method. * Despite accepting a stereo cable and having a “stereo” setting, many computer sound cards will just combine the two channels of a stereo signal.

You may also be running into the wav file format limitation. Wav files have a limit on the number of samples in the file. For a stereo 44.10 kHz/16 bit wav file (unfortunately there is no mono option on the zoom, which would double this) the max file duration possible is about 13.2 h. Even if you have more memory you still reach this file format limitation for a single file. To record longer you would need to stop a recording and start a new file, or you could record an mp3 file, but then have a massive file conversion to…

Acoustic species discrimination is still a relatively new “science” and it must be understood that any auto-classifier provides guidance and inference to species, but by virtue of the call variation from all species, the process of classification does produce false positives on species ID. The species ID process essentially amounts to a probabilistic process because the plasticity and resulting call repertoires of species results in so many areas of overlapping data space. Although some species do show a 100% correct rate for some situations, do note that rate describes the classifier’s ability to recognize ideal reference (i.e., good quality) files of the type on which the classifier was built, and a finite data set. You should expect actual field data to present unknown call types and sounds outside of the known library, and any such signals can potentially result in misclassifications. Only a smaller set of species-discriminating call varieties can provide confident species ID, e.g., the short, flat, above 26 kHz call types of Lano, and these are the type of calls that you would use to make confident decisions about presence . However many other call types from species fall into overlapping data space, e.g., the longer curved call types of Epfu and Lano, and SonoBat will output what can only be considered a probabilistic decision, the correctness of which will depend upon quality, the distance of the bat from the microphone, and probably the bat itself. For some species like Myso and Mylu back east we have yet to even recognize a species-discriminating call variant and the entire call repertoire apparently overlaps, even though the classifier shows some statistical difference. The take home message is that bats exhibit considerable plasticity in their calls and SonoBat and any other classification system must be considered fallible and serve merely as a guide and inference to classification.

Yes, each regional classifier employs a slightly different decision process based on the species suite included in the classifier. When you can exclude ambiguous species of concern then you gain much greater performance in classifying the species that you expect to be present in a geographic area. Therefore, applying this classifier to a geographic region outside the range of these species may result in some misclassifications of the out of range species.

There is currently is no system available that can provide a complete certainty and process everything for you, but SonoBat comes closest to that ideal than any other system. Bats have considerable plasticity in the calls they produce and within each species’ repertoire there can be some data space that overlaps in characteristics with parts form the repertoire of another species. Definitive species recognition relies upon the unique subset of each species’ repertoire. This also means that no one can identify each and every recording; for reasons of call plasticity and call quality. Noise and distance from the microphone greatly affects signal quality and classification in the same way that distance and backlight can make it difficult to identify birds. Unfortunately that’s the nature of the beast. It’s not so different than most other wildlife monitoring methodologies in that it requires some level of expertise. The current SonoBat classifiers provide batch processing and automated classification with idealized rates of performance listed in the classification notes accompanying the program. Even with the high quality data on which the US classifiers were built (11,000 call samples), species classification rates range from just below 90% to 100%, with acceptable classifications (those that come out with an acceptable level of confidence, e.g., in discriminating data space) range from 27% to 97%. So statistically, even with a 98% correct rate (and that’s ideal- for good data), the overlapping characteristics of calls will bring up some misclassifications for any substantial data set, particularly if recorded under less than ideal conditions. But, that is the state of the art, and most agencies that require this sort of survey work understand that, but do expect best possible practice. I hope this helps to understand this endeavor. The only reasonable solution to get data analyzed thoroughly at this time would involve working with someone that already has the expertise to oversee the analysis. According to the 2014 Indiana Bat Summer Survey Guidelines developed by the USF&WS: “At a minimum, for each site/night a program considered Indiana presence likely, review all files from that site/night. Qualitative analysis must also include a comparison of the results of each acoustic ID program by site and night (including: number of call files flagged as probable Indiana bats by each tool used; an evaluation of other species identified by the acoustic ID program; individual file level agreements and disagreements on Indiana bats between programs; and a qualitative analysis of ALL probable Indiana bat call sequences to further evaluate that the correct ID has been recommended by the program used).” And, also according to the USF&WS: “Individuals qualified to conduct qualitative analysis of acoustic bat calls typically have experience: (1) gathering known calls. This provides a valuable resource in understanding how bat calls change and the variation present in them; (2) identifying bat calls recorded in numerous habitat types; (3) familiarity with the species likely to be encountered within the project area; and (4) individuals must have multiple years of experience and must have stayed current with qualitative ID skills. A resume (or similar documentation) must be submitted along with final acoustic survey reports for anyone making final…