@article {53088, title = {Body size information in large-scale acoustic bat databases}, journal = {PeerJ}, volume = {6}, year = {2018}, month = {Jan-01-2018}, pages = {e5370}, abstract = {

Background
Citizen monitoring programs using acoustic data have been useful for detecting population and community patterns. However, they have rarely been used to study broad scale patterns of species traits. We assessed the potential of acoustic data to detect broad scale patterns in body size. We compared geographical patterns in body size with acoustic signals in the bat species Pipistrellus pipistrellus. Given the correlation between body size and acoustic characteristics, we expected to see similar results when analyzing the relationships of body size and acoustic signals with climatic variables.

Methods
We assessed body size using forearm length measurements of 1,359 bats, captured by mist nets in France. For acoustic analyses, we used an extensive dataset collected through the French citizen bat survey. We isolated each bat echolocation call (n = 4,783) and performed automatic measures of signals, including the frequency of the flattest part of the calls (characteristic frequency). We then examined the relationship between forearm length, characteristic frequencies, and two components resulting from principal component analysis for geographic (latitude, longitude) and climatic variables.

Results
Forearm length was positively correlated with higher precipitation, lower seasonality, and lower temperatures. Lower characteristic frequencies (i.e., larger body size) were mostly related to lower temperatures and northern latitudes. While conducted on different datasets, the two analyses provided congruent results.

Discussion
Acoustic data from citizen science programs can thus be useful for the detection of large-scale patterns in body size. This first analysis offers a new perspective for the use of large acoustic databases to explore biological patterns and to address both theoretical and applied questions.

}, doi = {10.7717/peerj.5370}, url = {https://peerj.com/articles/5370}, author = {Penone, Caterina and Kerbiriou, Christian and Julien, Jean-Fran{\c c}ois and Marmet, Julie and Le Viol, Isabelle} } @article {47341, title = {Large-scale semi-automated acoustic monitoring allows to detect temporal decline of bush-crickets}, journal = {Global Ecology and Conservation}, volume = {6}, year = {2016}, month = {Jan-04-2016}, pages = {208 - 218}, abstract = {

Monitoring biodiversity over large spatial and temporal scales is crucial to assess 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. The development of new recording techniques and new methods of automatic species recognition based on sound detection and easily applicable within a citizen-science framework, offers interesting possibilities. However, the value of such protocols has not been tested for the study of temporal trends on a large spatial scale.

We used an acoustic region-wide citizen-monitoring program of Orthoptera, conducted along roads, to assess the relevance of automatic species recognition methods to detect temporal trends while taking into account spatial and seasonal patterns of two Orthoptera species activity (Tettigonia viridissima Linnaeus, 1758, and Ruspolia nitidula Scopoli, 1786) at a large scale. Additionally, we tested the effect of climate and land-use variables on spatio-temporal abundance patterns using generalized linear mixed models. We found negative temporal trends for the two species across the survey period (2006\–2012). The spatial variations were largely explained by the geoclimatic conditions and, to a lesser extent, by land use (negative effects of urbanization). The temporal variations were highly correlated to the climatic conditions of the year, and of the previous year (nonlinear effect of temperature, precipitation).

To our knowledge, this paper describes the first successful attempt to calculate large-scale temporal trends of insect populations on the basis of an automatic identification process of acoustic data. We argue that acoustic monitoring along roads, coupled with the automatic recognition of species sounds, offers several advantages for assessing Orthoptera biodiversity response to global changes and environmental measures.

}, keywords = {automated signal recognition, bioacoustics, citizen monitoring program, Climate, Tettigoniida, trends}, issn = {23519894}, doi = {10.1016/j.gecco.2016.02.008}, url = {http://linkinghub.elsevier.com/retrieve/pii/S2351989415300329}, author = {Jeliazkov, Alienor and Bas, Yves and Kerbiriou, Christian and Julien, Jean-Fran{\c c}ois and Penone, Caterina and Le Viol, Isabelle} }