Data from: Potential for coupling the monitoring of bush-crickets with established large-scale acoustic monitoring of bats

1. Monitoring biodiversity over large spatial and temporal scales is
crucial for assessing the impact of global changes and environmental
mitigation measures. However, large-scale monitoring of invertebrates
remains poorly developed despite the importance of these organisms in
ecosystem functioning. Exciting possibilities applicable to professional
and citizen science are offered by new recording techniques and methods of
semi-automated species recognition based on sound detection. 2. Static
broad-spectrum detectors deployed to record throughout whole nights have
been recommended for standardised acoustic monitoring of bats, but they
have the potential to also collect acoustic data for other species groups.
Large-scale deployment of such systems is only viable when combined with
robust automated species identification algorithms. Here we examine the
potential of such a system for detecting, identifying and monitoring
bush-crickets (Orthoptera of the family Tettigoniidae). We use incidental
sound recordings generated by an extensive citizen science bat survey and
recordings from intensive site surveys to test a semi-automated step-wise
method with a classifier for assigning species identities. We assess
species’ diel activity patterns to make recommendations for survey timing
and interpretation of existing nocturnal datasets and consider the
feasibility of determining site occupancy. 3. Of six species of
bush-crickets, the species classifier achieved over 85% accuracy for
three, speckled bush-cricket, dark bush-cricket and Roesel’s bush-cricket.
It should be possible to automatically scan recordings for these species
with minimal manual validation. Further refinement of the classifier is
required for the three remaining species, in particular for the
acoustically similar short-winged conehead and long-winged conehead. Diel
activity patterns are species specific and it may be necessary to adjust
the hours over which the detectors record to increase detection of key
species, but this must be weighed against the costs in terms of increased
memory and battery use and equipment security during daytime. 4. We
conclude that with logistical support and centralised semi-automated
species identification it is now possible for the public to contribute to
large-scale acoustic monitoring of Orthoptera whilst recording bats.
Further innovation of sound classifier algorithms is needed and would be
aided by improved reference sound libraries from multiple locations
spanning species’ ranges.