Bat Echolocation Researc h - Bat Conservation International

Figure 3: Effect of division ratio. The same sequence of 9 consecutive
calls of Euderma maculatum as displayed at division ratios of A: 4, B: 8,
and C: 16. Note that even at a division ratio of 16, these calls could be
easily identified as Euderma, although they may be difficult to see among
low-frequency noise. Many displays of Euderma calls have more dots
than these. Note that a division ratio of 4 in general should not be used,
since frequencies higher than about 40 kHz will be aliased down to lower
values and could be misleading. The extra detail afforded by using 4 over
8 would not be of any consequence to recognizing the species.
who use acoustics for species identification is that some
species are easy to identify, some are identifiable under
favorable conditions, and some are hard to distinguish.
This accords with my own experience using Anabat. Furthermore,
reports about the problems experienced by
other workers are similar to the problems I encounter
myself. For example, the comments by Ahlén and
Baagøe (2000) on “other Myotis species” sound very close
to my own experiences with certain groups of Myotis in
North America. Furthermore, the general tone of the
particular identification issues discussed by Ahlén and
Baagøe sounds very close to my own impressions of
identifying bats using Anabat in North America or Australia.
I therefore suggest that for each of the methods –
ZCA, spectral analysis and auditory observation – the
problems of species identification are similar. Each
approach has its strengths and weaknesses, and to its
own adherents, each is superior.
SPECIFIC CRITICISMS OF ANABAT
Over the years, Anabat has faced a number of criticisms,
many of which I feel are unjustified. These often
show a lack of familiarity with the system, or are based on
prejudices over what a bat-call analysis system should provide.
I discuss a range of these common criticisms below.
Anabat isn’t as sensitive as other systems. While this is true,
it is not a simple issue. ZCA is inherently less sensitive
than spectral analysis, mainly because it is not possible
to extract a weak signal from noise in a separate frequency
band. This often limits the sensitivity to which a
ZCA system can be set. A heterodyne system is the most
Section 3: Ultrasound Species Identification
sensitive, although it can not simultaneously
monitor all frequencies used by bats, or simultaneously
detect bats using widely different frequencies.
With time expansion, any sensitivity
advantage is offset by the fact that it can only
monitor for a small proportion of the time. In
practical terms, Anabat is less sensitive, but this
doesn’t necessarily mean it will detect fewer
bats (see Corben and Fellers 2001).
Anabat isn’t sensitive enough. This clearly is not
the case. I routinely use Anabat for bat-survey
purposes, and I don’t find the sensitivity to be a
problem. Greater sensitivity would be advantageous
but it is not necessary, any more than it is
necessary to use larger mist nets. What matters
is not the sensitivity itself, but rather that sampling
strategies are appropriate to the equipment
being used. As long as a detector is capable of
detecting a particular species, it can be used to sample
that species, and Anabat is capable of detecting any
known echolocating bat. As with other systems, detection
ranges for whispering bats may be very small, but
Anabat easily detects other species at distances adequate
for general survey purposes.
Anabat doesn’t have a flat frequency response. Air does not
have a flat frequency response, and the frequency
response of air varies with the weather. Thus nothing a
detector can do will provide a flat frequency response
for the overall signal path from bat to observer. By
design, Anabat has a response, which makes it less sensitive
to low frequencies. This helps make Anabat effective
as a general-purpose instrument. Increasing the sensitivity
to low frequencies leads to excessive interference
from insects, wind, and other audible sounds. Fortunately,
low-frequency bat calls are not strongly attenuated by
the atmosphere and tend to be inherently loud, so the
bats producing them are usually easily detected.
Anabat is inaccurate. Fenton (2000) criticized the accuracy
of Anabat, claiming that its use imposed a sacrifice
in this regard. He illustrated alleged discrepancies
between the 2 systems he evaluated in Fig. 3 (Fenton
2000). That figure shows Anabat displaying frequencies
13 kHz higher than those displayed by the Pettersson
system for the same parts of the same calls. In fact, the
accuracy with which Anabat measures time intervals,
and therefore frequencies, is dependent on the crystalcontrolled
oscillators in the hardware, and these provide
an accuracy that is at least comparable to that of any
spectral-analysis system. Accuracy of either system is
easily sufficient for species identification, and neither
system would gain advantage from greater accuracy.
With properly functioning equipment, the differences
depicted in Fenton’s Fig. 3 could not possibly be real.
Using either spectral analysis or Anabat, it is necessary
to ensure that measurements are made from calls of sufficient
quality. For example, it would be pointless to make
measurements of maximum frequency from the recordings
of either system depicted in Fig. 3 of Fenton (2000),
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