02822nas a2200253   4500008004100000022001300041245010200054210006900156260001600225300001100241490000700252520184800259653002402107653003002131653001702161653001202178653002402190653002902214653002302243100002502266700002202291700002202313856023302335       2018                        eng d  a2351989400aPairing camera traps and acoustic recorders to monitor the ecological impact of human disturbance0 aPairing camera traps and acoustic recorders to monitor the ecolo  cJan-10-2018  ae004930 v163 a<p>Over the past two decades, the use of camera traps and acoustic monitoring in the investigation of animal ecology have grown rapidly, with each technique enhancing broad-scale wildlife surveying. Camera traps are a cost-effective, noninvasive means of sampling communities of mid-to large-terrestrial species, and acoustic recording devices capture human sounds and sound-producing animals, including species of mammals, birds, anurans, and insects. Rarely are these techniques combined, despite the advantages of merging their respective strengths. Namely, camera traps paired with acoustic recorders can evaluate the abundance, distribution, and behavior of multiple guilds and trophic levels across landscapes while concurrently monitoring multiple human stressors in real time. Moreover, integrating these approaches enhances detection accuracy and strengthens statistical inference at multiple survey scales. We conducted a literature review, and found only 13 studies that combine camera traps and acoustic recorders, 8 of which either compared the ability of each technique to detect species of interest or discussed the advantages of each technique. We outline potential questions that can be addressed by pairing acoustic recorders and camera traps, including enabling the simultaneous assessment of noise pollution and its impacts on mammal and avian communities. Furthermore, we discuss how the analysis of data from each technique face similar challenges; thus, simultaneous innovation offers the ability to apply solutions to both techniques and amplify their respective strengths. Digital technologies and big data are changing nature conservation in increasingly profound ways and integration of camera traps and acoustic recorders will facilitate new, transformative discoveries to meet modern conservation challenges.</p>
10aacoustic monitoring10aAnthropogenic disturbance10abiodiversity10aCameras10aCommunity structure10aInventory and monitoring10aMultiple stressors1 aLendrum, Patrick, E.1 aCrooks, Kevin, R.1 aWittemyer, George  uhttps://linkinghub.elsevier.com/retrieve/pii/S2351989418303573https://api.elsevier.com/content/article/PII:S2351989418303573?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S2351989418303573?httpAccept=text/plain01998nam a2200253   4500008004100000020002200041022001400063245006900077210006900146260004400215300001400259490001000273520123900283653001701522653001701539653002301556100002001579700001401599700001701613700001901630700001801649700002201667856005501689       2018                        eng d  a978-3-030-03990-5  a0302-974300aInvestigation of Unsupervised Models for Biodiversity Assessment0 aInvestigation of Unsupervised Models for Biodiversity Assessment  aChambSpringer International Publishing  a160 - 1710 v113203 a<p>Significant animal species loss has been observed in recent decades due to habitat destruction, which puts at risk environmental integrity and biodiversity. Traditional ways of assessing biodiversity are limited in terms of both time and space, and have high cost. Since the presence of animals can be indicated by sound, recently acoustic recordings have been used to estimate species richness. Bioacoustic sounds are typically recorded in habitats for several weeks, so contain a large collection of different sounds. Birds are of particular interest due to their distinctive calls and because they are useful ecological indicators. To assess biodiversity, the task of manually determining how many different types of birds are present in such a lengthy audio is really cumbersome. Towards providing an automated support to this issue, in this paper we investigate and propose a clustering based approach to assist in automated assessment of biodiversity. Our approach first estimates the number of different species and their volumes which are used for deriving a biodiversity index. Experimental results with real data indicates that our proposed approach estimates the biodiversity index value close to the ground truth.</p>
10abioacoustics10abiodiversity10aUnsupervised model1 aMitrovic, Tanja1 aXue, Bing1 aLi, Xiaodong1 aRao, KVSN Rama1 aGarg, Saurabh1 aMontgomery, James  uhttp://link.springer.com/10.1007/978-3-030-03991-2