02443nas a2200181 4500008004100000245006400041210006300105260001600168300001000184490000600194520191200200100002102112700002502133700002702158700001802185700002202203856003602225 2018 eng d00aBody size information in large-scale acoustic bat databases0 aBody size information in largescale acoustic bat databases cJan-01-2018 ae53700 v63 a

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.

1 aPenone, Caterina1 aKerbiriou, Christian1 aJulien, Jean-François1 aMarmet, Julie1 aLe Viol, Isabelle uhttps://peerj.com/articles/537002604nas a2200217 4500008004100000022001400041245008100055210006900136260000900205300001000214490000600224520190300230100002702133700001702160700002302177700001902200700002202219700002202241700001802263856010502281 2015 eng d a2167-835900aFirst description of underwater acoustic diversity in three temperate ponds.0 aFirst description of underwater acoustic diversity in three temp c2015 ae13930 v33 a

The past decade has produced an increased ecological interest in sonic environments, or soundscapes. However, despite this rise in interest and technological improvements that allow for long-term acoustic surveys in various environments, some habitats' soundscapes remain to be explored. Ponds, and more generally freshwater habitats, are one of these acoustically unexplored environments. Here we undertook the first long term acoustic monitoring of three temperate ponds in France. By aural and visual inspection of a selection of recordings, we identified 48 different sound types, and according to the rarefaction curves we calculated, more sound types are likely present in one of the three ponds. The richness of sound types varied significantly across ponds. Surprisingly, there was no pond-to-pond daily consistency of sound type richness variation; each pond had its own daily patterns of activity. We also explored the possibility of using six acoustic diversity indices to conduct rapid biodiversity assessments in temperate ponds. We found that all indices were sensitive to the background noise as estimated through correlations with the signal-to-noise ratio (SNR). However, we determined that the AR index could be a good candidate to measure acoustic diversities using partial correlations with the SNR as a control variable. Yet, research is still required to automatically compute the SNR in order to apply this index on a large data set of recordings. The results showed that these three temperate ponds host a high level of acoustic diversity in which the soundscapes were variable not only between but also within the ponds. The sources producing this diversity of sounds and the drivers of difference in daily song type richness variation both require further investigation. Such research would yield insights into the biodiversity and ecology of temperate ponds.

1 aDesjonquères, Camille1 aRybak, Fanny1 aDepraetere, Marion1 aGasc, Amandine1 aLe Viol, Isabelle1 aPavoine, Sandrine1 aSueur, Jerome uhttps://bio.acousti.ca/content/first-description-underwater-acoustic-diversity-three-temperate-ponds02861nas a2200277 4500008004100000022001300041245010200054210006900156260001600225300001400241490000600255520200300261653003302264653001702297653003102314653001202345653001702357653001102374100002302385700001402408700002502422700002702447700002102474700002202495856006602517 2016 eng d a2351989400aLarge-scale semi-automated acoustic monitoring allows to detect temporal decline of bush-crickets0 aLargescale semiautomated acoustic monitoring allows to detect te cJan-04-2016 a208 - 2180 v63 a

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.

10aautomated signal recognition10abioacoustics10acitizen monitoring program10aClimate10aTettigoniida10atrends1 aJeliazkov, Alienor1 aBas, Yves1 aKerbiriou, Christian1 aJulien, Jean-François1 aPenone, Caterina1 aLe Viol, Isabelle uhttp://linkinghub.elsevier.com/retrieve/pii/S2351989415300329