<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">VanSchaik, Jack</style></author><author><style face="normal" font="default" size="100%">Zhao, Zhao</style></author><author><style face="normal" font="default" size="100%">Gasc, Amandine</style></author><author><style face="normal" font="default" size="100%">Omrani, Hichem</style></author><author><style face="normal" font="default" size="100%">Bryan C. Pijanowski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Contributions of MIR to soundscape ecology. Part 2: Spectral timbral analysis for discriminating soundscape components</style></title><secondary-title><style face="normal" font="default" size="100%">Ecological Informatics</style></secondary-title><short-title><style face="normal" font="default" size="100%">Ecological Informatics</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-02-2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://linkinghub.elsevier.com/retrieve/pii/S1574954118301900</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Soundscape ecology evaluates biodiversity and environmental disturbances by investigating the interaction among soundscape components (biological, geophysical, and human-produced sounds) using data collected with autonomous recording units. Current analyses consider the acoustic properties of frequency and amplitude resulting in varied metrics, but rarely focus on the discrimination of soundscape components. Computational musicologists analyze similar data but consider a third acoustic property, timbre.&lt;/p&gt;
&lt;p&gt;Here, we investigated the effectiveness of spectral timbral analysis to distinguish among dominant soundscape components. This process included manually labeling and extracting spectral timbral features for each recording. Then, we tested classification accuracy with linear and quadratic discriminant analyses on combinations of spectral timbral features.&lt;/p&gt;
&lt;p&gt;Different spectral timbral feature groups distinguished between biological, geophysical, and manmade sounds in a single field recording. Furthermore, as we tested different combinations of spectral timbral features that resulted in both high and very low accuracy results, we found that they could be ordered to &amp;ldquo;sift&amp;rdquo; out field recordings by individual dominant soundscape component.&lt;/p&gt;
&lt;p&gt;By using timbre as a new acoustic property in soundscape analyses, we could classify dominant soundscape components effectively. We propose further investigation into a sifting scheme that may allow researchers to focus on more specific research questions such as understanding changes in biodiversity, discriminating by taxonomic class, or to inspect weather-related events.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gasc, Amandine</style></author><author><style face="normal" font="default" size="100%">Gottesman, Benjamin L.</style></author><author><style face="normal" font="default" size="100%">Francomano, Dante</style></author><author><style face="normal" font="default" size="100%">Jung, Jinha</style></author><author><style face="normal" font="default" size="100%">Durham, Mark</style></author><author><style face="normal" font="default" size="100%">Mateljak, Jason</style></author><author><style face="normal" font="default" size="100%">Bryan C. Pijanowski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Soundscapes reveal disturbance impacts: biophonic response to wildfire in the Sonoran Desert Sky Islands</style></title><secondary-title><style face="normal" font="default" size="100%">Landscape Ecology</style></secondary-title><short-title><style face="normal" font="default" size="100%">Landscape Ecol</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Conservation biology</style></keyword><keyword><style  face="normal" font="default" size="100%">disturbance</style></keyword><keyword><style  face="normal" font="default" size="100%">Remote sensing</style></keyword><keyword><style  face="normal" font="default" size="100%">Sonic timelapse</style></keyword><keyword><style  face="normal" font="default" size="100%">Soundscape</style></keyword><keyword><style  face="normal" font="default" size="100%">Wildfire</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct-07-2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://link.springer.com/10.1007/s10980-018-0675-3</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Context&lt;br /&gt;
	While remote sensing imagery is effective for quantifying land cover changes across large areas, its utility for directly assessing the response of animals to disturbance is limited. Soundscapes approaches&amp;mdash; the recording and analysis of sounds in a landscape&amp;mdash; could address this shortcoming.&lt;/p&gt;
&lt;p&gt;Objectives&lt;br /&gt;
	In 2011, a massive wildfire named &amp;lsquo;&amp;lsquo;the Horseshoe 2 Burn&amp;rsquo;&amp;rsquo; occurred in the Chiricahua National Monument, Arizona, USA. We evaluated the impact of this wildfire on acoustic activity of animal communities.&lt;/p&gt;
&lt;p&gt;Methods&lt;br /&gt;
	In 2013, soundscape recordings were col- lected over 9 months in 12 burned and 12 non-burned sites in four ecological systems. The seasonal and diel biological acoustic activity were described using the &amp;lsquo;&amp;lsquo;Bioacoustic Index&amp;rsquo;&amp;rsquo;, a detailed aural analysis of sound sources, and a new tool called &amp;lsquo;&amp;lsquo;Sonic Time- lapse Builder&amp;rsquo;&amp;rsquo; (STLB).&lt;/p&gt;
&lt;p&gt;&lt;br /&gt;
	Results&lt;br /&gt;
	Seasonal biophony phenology showed a diurnal peak in June and a nocturnal peak in October in all ecological systems. On June mornings, acoustic activity was lower at burned than at non-burned sites in three of four ecological systems, due to a decreased abundance of cicadas directly impacted by the death of trees. Aural analyses revealed that 55% of recordings from non-burned sites contained insect sounds com- pared to 18% from burned sites. On October nights, orthopteran activity was more prevalent at some burned sites, possibly due to post-fire emergence of herbaceous.&lt;/p&gt;
&lt;p&gt;Conclusions&lt;br /&gt;
	Soundscape approaches can help address long-term conservation issues involving the responses of animal communities to wildfire. Acoustic methods can serve as a valuable complement to remote sensing for disturbance-based landscape management.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Desjonquères, Camille</style></author><author><style face="normal" font="default" size="100%">Rybak, Fanny</style></author><author><style face="normal" font="default" size="100%">Depraetere, Marion</style></author><author><style face="normal" font="default" size="100%">Gasc, Amandine</style></author><author><style face="normal" font="default" size="100%">Le Viol, Isabelle</style></author><author><style face="normal" font="default" size="100%">Pavoine, Sandrine</style></author><author><style face="normal" font="default" size="100%">Sueur, Jerome</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">First description of underwater acoustic diversity in three temperate ponds.</style></title><secondary-title><style face="normal" font="default" size="100%">PeerJ</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PeerJ</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">e1393</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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&amp;#39; 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.&lt;/p&gt;
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