Bat Echolocation Researc h - Bat Conservation International

ential power of data. Hayes (1997) noted that because of
the range of inherent variability in data collected at a
single point, this type of sampling may obscure patterns
or lead to inferences about variation of biological significance
incorrectly. Without an estimate of within habitat
variation (by comparing mean levels – and variance – of
use of homogenous units), between-habitat comparisons
cannot be made. Randomization cannot replace the use
of multiple units in a habitat, because no estimate of
within-habitat variability can be made using just 1 or 2
detectors. Typically, in category 2 and 3 papers, single
detector systems were used to collect data and then findings
were compared across time and space to assess differential
habitat use. Failure to account for temporal
variation at sampling locations presumes that use of
habitat is static. Gannon et al. (2003) argue that to
assume static spatial and temporal use of habitat by bats
is inaccurate. Moreover, failure to account for spatial and
temporal variation results in generation of false models
of habitat use (at all levels of call classification).
ARE ACOUSTIC DETECTORS THE SILVER BULLET?
Due to observed spatial and temporal variation in bat
activity (both within and across habitats), concurrent
sampling should be adopted whenever possible. Sampling
points need to be established a priori with sampling
effort equally distributed among points. Concurrent data
collection at multiple sampling points is the best form of
replication. Without an estimate of within-habitat variation,
between-habitat comparisons cannot be made. In
cases where concurrent data collection is not possible
(for example, because of equipment costs, limited access
to sites, or endangered species), alternative techniques
may be available (some of these issues are addressed by
Jones et al. this volume). In most cases, the study should
not be done if the study design is inadequate to address
the question or if the equipment inventory is insufficient.
Clearly, researchers using acoustic detectors to draw conclusions
about habitat use by bats must address the
underlying assumptions made when conducting their
studies. Clearly stating these assumptions not only assists
other scientists to evaluate how the study was conducted,
but serves to anchor conclusions in biological reality.
This helps to ensure that the data will be applied in context.
Sherwin et al. (2000) emphasized that data from
acoustic studies may generate patterns, which are artificial.
Furthermore, the assumptions may preclude the
exclusive use of acoustic detectors for investigating differential
use of habitat by bats. However, even limiting or
unrealistic assumptions should be listed if they are relevant
to the study design (Hayes 2000).
We provide an example of how assumptions (Table
2) can be defined for use in echolocation-monitoring
studies that use acoustic detectors. Assuming captures of
call sequences are correlated with habitat type (Assumption
1) allows the investigator to align the proper classification
(such as guild or ensemble) for calls. This
Section 2: Acoustic Inventories
assumption is valid unless habitat is a narrow strip of
vegetation (such as a wind row or strip of trees bordering
successive clear cuts) where habitat may appear distinct,
but from the scale that bats operate in, may in fact
be discontinuous (Assumption 6). We considered each
call sequence to be independent of the next (Assumption
2). This is a valid assumption as long as bat activity
is not high. With high bat activity, many con-specifics
as well as multiple species fly over detectors simultaneously.
High calling activity is when more than 2 bats (or
2 species of bat) are calling in a call sequence at 1 time
and these multiple bats will be represented on a single
call sequence file. If multiple detectors are operating
concurrently, examination of call sequences containing
search phase call-types (Assumption 4) will provide
additional information to determine if calls are independent.
Moreover, if sets of detectors are run for multiple
nights concurrently at different sites within the same
habitat type, true replication has occurred (Assumption
8). If this same set of detectors are maintained and operated
over time to include multiple seasons and multiple
years, then spatial and temporal scales can be examined
for call-sequence data (Assumption 10). If sequences of
multiple bats cannot be determined to be independent
(contradicting Assumption 2), calls and call sequences
should be discarded from further analysis. Captures can
be defined as a discrete sequence of search-phase calls
(Assumptions 3, 4, 7).
How call sequences are defined (we observed 5
groups in the literature: species, species-groups, soundgroups,
guilds, and all calls; Assumptions 5 and 6) can
result in dramatically different conclusions. If investigators
cite the convention that they follow, then their
study can be interpreted at the proper scale. Calls are the
unit of classification, not species or bats. For instance,
identifying call sequences to species has the most biological
significance at the local level. For investigations
at the landscape level, guilds (or bat ensembles; Patterson
et al 2003) allow ecological inference at a coarser
scale. Early papers using heterodyne detectors may have
actually followed a guild concept (in theory) by identifying
calls as sound groups (popular categories were 25
and 40 kHz). This manner of grouping calls provides a
repeatable method of classifying acoustic data but offers
little resolution on the question of differential use of
habitat by species of bats.
Other considerations when using detectors include
differential detection of lower intensity species (e.g.,
Corynorhinus) or bats that are specialized aerial hawkers
(e.g., Tadarida; Assumption 9). Not all species are detected
equally by acoustic detectors and this is a bias that
must be adressed. The study design and the resulting
interpretation of call data should provide compensation
for differentially detectable species.
We stress that any study that produces extensions of
species ranges, suggests management needs, or even
documents new aspects of natural history, should not be
based on acoustic data alone (Assumption 11). Acoustic
41