Data from: Estimating population density of insectivorous bats based on stationary acoustic detectors: a case study

1. Automated recording units are commonly used by consultants to assess
environmental impacts and to monitor animal populations. Although
estimating population density of bats using stationary acoustic detectors
is key for evaluating environmental impacts, estimating densities from
call activity data is only possible through recently developed numerical
methods, as the recognition of calling individuals is impossible. 2. We
tested the applicability of generalized random encounter models (gREMs)
for determining population densities of three bat species (Common
pipistrelle Pipistrellus pipistrellus, Northern bat Eptesicus nilssonii,,
and Natterer’s bat Myotis nattereri) based on passively collected
acoustical data. To validate the results, we compared them to (i) density
estimates from the literature and to (ii) Royle-Nichols (RN) models of
detection/non-detection data. 3. Our estimates for M. nattereri matched
both the published data and RN-model results. For E. nilssonii, the gREM
yielded similar estimates to the RN-models, but the published estimates
were more than twice as high. This discrepancy might be because the
high-altitude flight of E. nilssonii is not accounted for in gREMs.
Results of gREMs for P. pipistrellus were supported by published data but
were approximately 10 times higher than those of RN-models. RN-models use
detection/non-detection data and this loss of information probably
affected population estimates of very active species like P. pipistrellus.
4. gREM models provided realistic estimates of bat population densities
based on automatically recorded call activity data. However, the average
flight altitude of species should be accounted for in future analyses. We
suggest including flight altitude in the calculation of the detection
range to assess the detection sphere more accurately and to obtain more
precise density estimates.