Bat Echolocation Researc h - Bat Conservation International

96
detail is not helpful for species identification, then it is
superfluous. An excessive division ratio results in too
much averaging and insufficient detail in the display.
The optimum division ratio for practical use is a matter
of compromise between these competing needs. I use a
division ratio of 16 for most purposes, although 8 is a
better choice for displaying very steep calls of short
duration, especially at low frequency.
Zero-crossings Analysis ignores the intensity of the
original signal and only responds to the highest intensity
frequency component at any instant. These limitations
have little, and in many cases no, practical influence
on the usefulness of ZCA for bat-call identification.
One consequence, however, is that a ZCA-based system
is inherently less sensitive than a system based on spectral
analysis, since ZCA lacks the ability to separate
simultaneous signals of different frequencies.
USE OF ZCA IN ACTIVE MONITORING
With active monitoring, a visual display of bat-call
frequency characteristics is generated in real time by
feeding the output of an Anabat detector into a laptop
computer through an interfacing device called a
ZCAIM. The Anabat software running on the computer
draws the display on the screen and saves data into files
stored on the hard disk for later retrieval and more
detailed analysis if required.
When I undertake active monitoring, I try to observe
any bats detected acoustically by illuminating them with
a spotlight. This allows me to see features that aid identification.
Such features include color, wing shape, flight
pattern and feeding behavior, and some other distinctive
characters such as the long ears or tails of certain
species. The combination of visual observations with call
features displayed on the screen allows the greatest likelihood
of identifying free-flying bats.
I find that some groups of bat species are hard to distinguish
acoustically but easy to identify visually. Examples
include Lasionycteris noctivagans, Eptesicus fuscus and
Tadarida brasiliensis in North America, and Vespadelus darlingtoni
versus Miniopterus schreibersii, Scotorepens orion versus
Scoteanax ruepellii and Mormopterus beccarrii versus Saccolaimus
flaviventris in Australia. Many species look very similar
in the field but are easily identified acoustically,
examples being Myotis yumanensis versus M. lucifugus and
Nyctinomops macrotis versus N. femorosaccus in North America,
and Vespadelus darlingtoni versus V. pumilus, Scotorepens
orion versus S. greyii, and species of the families Hipposideridae
and Rhinolophidae in Australia. Thus, I find
acoustic and visual cues to be complementary, and the
combination of both is typically much more powerful
than either by itself. (See Limpens this volume.)
Active monitoring is also an excellent tool for learning
how a bat’s calls change with the varying circumstances
under which it flies. A real-time display, such as
that offered by Anabat, in combination with visual
observations, provides an observer with an immediate
link between the behavior or circumstances of a bat and
the types of calls it produces. This link enhances comprehension
of a species’ acoustic repertoire. Understanding
such variation is essential to developing effective
identification criteria.
With practice, it is quite easy to visually observe bats
and to make use of information on the computer screen
at virtually the same time. The most difficult part of the
process is often locating a bat with the spotlight, especially
because it is usually undesirable to illuminate the
bat before it has made its closest approach. Most bats are
repelled by the light, typically turning away from it and
consequently changing their calls and also reducing the
likelihood of the observer obtaining adequate views.
Actually seeing the necessary features of a flying bat is
not easy and requires practice. Much of the skill required
involves understanding the kinds of views that are most
informative, and developing the ability to make the best
use of the brief moments when a bat is in the best position
for viewing. This is analogous to the problem of
observing critical identification features on many birds,
such as distant birds of prey or seabirds.
USE OF ZCA IN PASSIVE RECORDING
With passive recording, a detector and storage system
are deployed so as to record bats in the absence of
any human observer. Using Anabat, such systems have
typically been implemented using a detector, ZCAIM
and laptop computer, though tape-recorders have often
been used for storage.
To make passive recording easier, I designed a device
called a Storage ZCAIM, which replaces the
ZCAIM/computer combination with a single, small, lowpower
device that stores all recorded data on a Compact
Flash card. It can be powered for several nights using AA
batteries, and the data can be downloaded from the
Compact Flash card as Anabat files ready to view.
Passive-recording systems can be deployed near the
ground, but can also be raised into the tree canopy or
suspended from a balloon. Passive recording offers many
options not open to active monitoring. Using ZCA,
many passive-recording systems can be deployed by a
single operator, providing insight into spatial heterogeneity
not otherwise available. Passive recording can
also be conducted in places difficult for active monitoring,
for example, to avoid disturbing local landowners.
Furthermore, passive recording largely overcomes the
problem of temporal variation, since it is easy to collect
data all night or for many consecutive nights. Long-term
passive-recording stations using ZCA are now in use,
allowing bats to be recorded all night every night, year
after year.
Passive recording is less effective for species identification
than active monitoring, mainly because visual
cues are lacking. Passive monitoring also records bats at
a lower rate. In experiments I conducted, active monitoring
recorded 3 times as many bats and 3 times as
Bat Echolocation Research: tools, techniques & analysis