<?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%">Linke, Simon</style></author><author><style face="normal" font="default" size="100%">Gifford, Toby</style></author><author><style face="normal" font="default" size="100%">Desjonquères, Camille</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Six steps towards operationalising freshwater ecoacoustic monitoring</style></title><secondary-title><style face="normal" font="default" size="100%">Freshwater Biology</style></secondary-title><short-title><style face="normal" font="default" size="100%">Freshw Biol</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ecoacoustics</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecological Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">freshwater</style></keyword><keyword><style  face="normal" font="default" size="100%">passive acoustics</style></keyword><keyword><style  face="normal" font="default" size="100%">underwater sounds</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb-01-2021</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://onlinelibrary.wiley.com/toc/13652427/65/1</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">65</style></volume><pages><style face="normal" font="default" size="100%">1 - 6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;1. Applications in bioacoustics and its sister discipline ecoacoustics have increased exponentially over the last decade. However, despite knowledge about aquatic bioacoustics dating back to the times of Aristotle and a vast amount of background literature to draw upon, freshwater applications of ecoacoustics have been lagging to date.&lt;/p&gt;
&lt;p&gt;2.In this special issue, we present nine studies that deal with underwater acoustics, plus three acoustic studies on water‐dependent birds and frogs. Topics include automatic detection of freshwater organisms by their calls, quantifying habitat change by analysing entire soundscapes, and detecting change in behaviour when organisms are exposed to noise.&lt;/p&gt;
&lt;p&gt;3.We identify six major challenges and review progress through this special issue. Challenges include characterisation of sounds, accessibility of archived sounds as well as improving automated analysis methods. Study design considerations include characterisation analysis challenges of spatial and temporal variation. The final key challenge is the so far largely understudied link between ecological condition and underwater sound.&lt;/p&gt;
&lt;p&gt;4.We hope that this special issue will raise awareness about underwater soundscapes as a survey tool. With a diverse array of field and analysis tools, this issue can act as a manual for future monitoring applications that will hopefully foster further advances in the field.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></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%">Lin, Tzu‐Hao</style></author><author><style face="normal" font="default" size="100%">Tsao, Yu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Source separation in ecoacoustics: A roadmap towards versatile soundscape information retrieval</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">acoustic habitat</style></keyword><keyword><style  face="normal" font="default" size="100%">biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">ecosystem dynamics</style></keyword><keyword><style  face="normal" font="default" size="100%">machine learning</style></keyword><keyword><style  face="normal" font="default" size="100%">passive acoustics</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal processing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://onlinelibrary.wiley.com/doi/abs/10.1002/rse2.141</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;A comprehensive assessment of ecosystem dynamics requires the monitoring of biological, physical and social changes. Changes that cannot be observed visually may be trackable acoustically through soundscape analysis. Soundscapes vary greatly depending on geophysical events, biodiversity and human activities. However, retrieving source‐specific information from geophony, biophony and anthropophony remains a challenging task, due to interference by simultaneous sound sources. Audio source separation is a technique that aims to recover individual sound sources when only mixtures are accessible. Here, we review techniques of monoaural audio source separation with the fundamental theories and assumptions behind them. Depending on the availability of prior information about the source signals, the task can be approached as a blind source separation or a model‐based source separation. Most blind source separation techniques depend on assumptions about the behaviour of the source signals, and their performance may deteriorate when the assumptions fail. Model‐based techniques generally do not require specific assumptions, and the models are directly learned from labelled data. With the recent advances of deep learning, the model‐based techniques can yield state‐of‐the‐art separation performance, accordingly facilitate content‐based audio information retrieval. Source separation techniques have been adopted in several ecoacoustic applications to evaluate the contributions from biodiversity and anthropogenic disturbance to soundscape dynamics. They can also be employed as nonlinear filters to improve the recognition of bioacoustic signals. To effectively retrieve ecological information from soundscapes, source separation is a crucial tool. We believe that the future integrations of ecological hypotheses and deep learning can realize a high‐performance source separation for ecoacoustics, and accordingly improve soundscape‐based ecosystem monitoring. Therefore, we outline a roadmap for applying source separation to assist in soundscape information retrieval and hope to promote cross‐disciplinary collaboration.&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%">González Correa, José Miguel</style></author><author><style face="normal" font="default" size="100%">Bayle Sempere, Just-Tomás</style></author><author><style face="normal" font="default" size="100%">Juanes, Francis</style></author><author><style face="normal" font="default" size="100%">Rodney A. Rountree</style></author><author><style face="normal" font="default" size="100%">Ruíz, Juan Francisco</style></author><author><style face="normal" font="default" size="100%">Ramis, Jaime</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Recreational boat traffic effects on fish assemblages: First evidence of detrimental consequences at regulated mooring zones in sensitive marine areas detected by passive acoustics</style></title><secondary-title><style face="normal" font="default" size="100%">Ocean &amp; Coastal Management</style></secondary-title><short-title><style face="normal" font="default" size="100%">Ocean &amp; Coastal Management</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">bioacoustics</style></keyword><keyword><style  face="normal" font="default" size="100%">Croaker</style></keyword><keyword><style  face="normal" font="default" size="100%">Drummer</style></keyword><keyword><style  face="normal" font="default" size="100%">Fish assemblage</style></keyword><keyword><style  face="normal" font="default" size="100%">Mooring</style></keyword><keyword><style  face="normal" font="default" size="100%">Motorboat noise</style></keyword><keyword><style  face="normal" font="default" size="100%">passive acoustics</style></keyword></keywords><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/S0964569118301972https://api.elsevier.com/content/article/PII:S0964569118301972?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0964569118301972?httpAccept=text/plain</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">168</style></volume><pages><style face="normal" font="default" size="100%">22 - 34</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We assess the impact of recreational boat traffic on sensitive habitats in the Western Mediterranean using passive acoustics. We compared underwater sounds in three regulated mooring locations vs a pristine location; and temporal differences in the pristine location vs the nearest mooring between high and low touristic seasons. We measured the number of pulses/minute, fish pulse patterns, and percentage of boat noise occurrence and its relative average power level. At the pristine location, the call rates and their complexity were significantly higher and the motorboat noise was significantly lower. The temporal trend of biophonic sounds decreased significantly in the pristine location. In contrast, in the mooring sites, the motorboat noise decreased significantly and the fish calls remained at low levels in both seasons. In conclusion, motorboat noise negatively affects the complexity of the fish assemblages but could be conditioned to their historic uses.&lt;/p&gt;
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