The impact of environmental factors in birdsong acquisition using automated recorders

The use of automatic acoustic recorders is becoming a principal method to survey birds in their natural habitats, as it is relatively noninvasive while still being informative. As with any other sound, birdsong degrades in amplitude, frequency, and temporal structure as it propagates to the recorder through the environment. Knowing how different birdsongs attenuate under different conditions is useful to, for example, develop protocols for deploying acoustic recorders and improve automated detection methods, an essential part of the research field that is becoming known as ecoacoustics. This article presents playback and recapture (record) experiments carried out under different environmental conditions using twenty bird calls from eleven New Zealand bird species in a native forest and an open area, answering five research questions: (1) How does birdsong attenuation differ between forest and open space? (2) What is the relationship between transmission height and birdsong attenuation? (3) How does frequency of birdsong impact the degradation of sound with distance? (4) Is birdsong attenuation different during the night compared to the day? and (5) what is the impact of wind on attenuation? Bird calls are complex sounds; therefore, we have chosen to use them rather than simple tones to ensure that this complexity is not missed in the analysis. The results demonstrate that birdsong transmission was significantly better in the forest than in the open site. During the night, the attenuation was at a minimum in both experimental sites. Transmission height affected the propagation of the songs of many species, particularly the flightless ones. The effect of wind was severe in the open site and attenuated lower frequencies. The reverberations due to reflective surfaces masked higher frequencies (8 kHz) in the forest even at moderate distances. The findings presented here can be applied to develop protocols for passive acoustic monitoring. Even though the attenuation can be generalized to frequency bands, the structure of the birdsong is also important. Selecting a reasonable sampling frequency avoids unnecessary data accumulation because higher frequencies attenuate more in the forest. Even at moderate distances, recorders capture significantly attenuated birdsong, and hence, automated analysis methods for field recordings need to be able to detect and recognize faint birdsong.     

Acoustic localization of terrestrial wildlife: Current practices and future opportunities

Autonomous acoustic recorders are an increasingly popular method for low‐disturbance, large‐scale monitoring of sound‐producing animals, such as birds, anurans, bats, and other mammals. A specialized use of autonomous recording units (ARUs) is acoustic localization, in which a vocalizing animal is located spatially, usually by quantifying the time delay of arrival of its sound at an array of time‐synchronized microphones. To describe trends in the literature, identify considerations for field biologists who wish to use these systems, and suggest advancements that will improve the field of acoustic localization, we comprehensively review published applications of wildlife localization in terrestrial environments. We describe the wide variety of methods used to complete the five steps of acoustic localization: (1) define the research question, (2) obtain or build a time‐synchronizing microphone array, (3) deploy the array to record sounds in the field, (4) process recordings captured in the field, and (5) determine animal location using position estimation algorithms. We find eight general purposes in ecology and animal behavior for localization systems: assessing individual animals' positions or movements, localizing multiple individuals simultaneously to study their interactions, determining animals' individual identities, quantifying sound amplitude or directionality, selecting subsets of sounds for further acoustic analysis, calculating species abundance, inferring territory boundaries or habitat use, and separating animal sounds from background noise to improve species classification. We find that the labor‐intensive steps of processing recordings and estimating animal positions have not yet been automated. In the near future, we expect that increased availability of recording hardware, development of automated and open‐source localization software, and improvement of automated sound classification algorithms will broaden the use of acoustic localization. With these three advances, ecologists will be better able to embrace acoustic localization, enabling low‐disturbance, large‐scale collection of animal position data.     

The Use of Automated Bioacoustic Recorders to Replace Human Wildlife Surveys: An Example Using Nightjars

To be able to monitor and protect endangered species, we need accurate information on their numbers and where they live. Survey methods using automated bioacoustic recorders offer significant promise, especially for species whose behaviour or ecology reduces their detectability during traditional surveys, such as the European nightjar. In this study we examined the utility of automated bioacoustic recorders and the associated classification software as a way to survey for wildlife, using the nightjar as an example. We compared traditional human surveys with results obtained from bioacoustic recorders. When we compared these two methods using the recordings made at the same time as the human surveys, we found that recorders were better at detecting nightjars. However, in practice fieldworkers are likely to deploy recorders for extended periods to make best use of them. Our comparison of this practical approach with human surveys revealed that recorders were significantly better at detecting nightjars than human surveyors: recorders detected nightjars during 19 of 22 survey periods, while surveyors detected nightjars on only six of these occasions. In addition, there was no correlation between the amount of vocalisation captured by the acoustic recorders and the abundance of nightjars as recorded by human surveyors. The data obtained from the recorders revealed that nightjars were most active just before dawn and just after dusk, and least active during the middle of the night. As a result, we found that recording at both dusk and dawn or only at dawn would give reasonably high levels of detection while significantly reducing recording time, preserving battery life. Our analyses suggest that automated bioacoustic recorders could increase the detection of other species, particularly those that are known to be difficult to detect using traditional survey methods. The accuracy of detection is especially important when the data are used to inform conservation.     

Birdsong Denoising Using Wavelets

Automatic recording of birdsong is becoming the preferred way to monitor and quantify bird populations worldwide. Programmable recorders allow recordings to be obtained at all times of day and year for extended periods of time. Consequently, there is a critical need for robust automated birdsong recognition. One prominent obstacle to achieving this is low signal to noise ratio in unattended recordings. Field recordings are often very noisy: birdsong is only one component in a recording, which also includes noise from the environment (such as wind and rain), other animals (including insects), and human-related activities, as well as noise from the recorder itself. We describe a method of denoising using a combination of the wavelet packet decomposition and band-pass or low-pass filtering, and present experiments that demonstrate an order of magnitude improvement in noise reduction over natural noisy bird recordings.     

The sound of the illegal: Applying bioacoustics for long-term monitoring of illegal cattle in protected areas

Passive acoustic monitoring coupled with automated signal recognition software has been widely used in recent years as an effective and affordable tool for wildlife monitoring and to combat illegal activities within protected areas. Here, we evaluate this technique to monitor the patterns of illegal cattle occurrence in the Brazilian Pantanal over a complete annual cycle. We aim to provide one of the first assessments of the performance of automated signal recognition software to detect ungulates. Cattle occurrences reached their maximum during the end of the dry season when lowland areas provide excellent pastures for cattle. In contrast, cattle occurrences were very low during the rainy season when the study area was seasonally inundated. Automated software was an efficient tool that was able to detect approximately three-quarters of cow calls within the recordings. Passive acoustic monitoring can be used to direct patrols to areas where illegal activities, such as cattle and poaching or logging, have been confirmed, which could be a method that would be especially well suited for remote areas, such as tropical forests. Future studies should evaluate whether there is a relationship between cattle grazing intensity and its associated impacts on wildlife and flora. Rapid advances in automated recognition and the recent development of low-cost recorders foresee a new era of acoustic ecology for improved conservation in the short term.     

Automated classification of bat echolocation call recordings with artificial intelligence

Acoustic recorders are commonly used to remotely monitor and collect data on bats (Order Chiroptera). These efforts result in many acoustic recordings that must be classified by a bat biologist with expertise in call classification in order to obtain useful information. The rarity of this expertise and time constraints have prompted efforts to automatically classify bat species in acoustic recordings using a variety of learning methods. There are several software programs available for this purpose, but they are imperfect and the United States Fish and Wildlife Service often recommends that a qualified acoustic analyst review bat call identifications even if using these software programs. We sought to build a model to classify bat species using modern computer vision techniques. We used images of bat echolocation calls (i.e., plots of the pulses) to train deep learning computer vision models that automatically classify bat calls to species. Our model classifies 10 species, five of which are protected under the Endangered Species Act. We evaluated our models using standard model validation procedures, and performed two external tests. For these tests, an entire dataset was withheld from the procedure before splitting the data into training and validation sets. We found that our validation accuracy (92%) and testing accuracy (90%) were higher than when we used Kaleidoscope Pro and BCID software (65% and 61% accuracy, respectively) to evaluate the same calls. Our results suggest that our approach is effective at classifying bat species from acoustic recordings, and our trained model will be incorporated into new bat call identification software: WEST-EchoVision.     

Measuring nocturnal seabird activity and status using acoustic recording devices: applications for island restoration

ABSTRACT Nocturnal burrow‐nesting seabirds breeding on isolated oceanic islands pose challenges to conventional monitoring techniques, resulting in their frequent exclusion from population studies. These seabirds have been devastated by nonnative predator introductions on islands worldwide. After predators are eradicated, recovery has been poorly quantified, but evidence suggests some nocturnal seabird populations have been slow to return. We evaluated the use of automated acoustic recorders and call‐recognition software to investigate nocturnal seabird recovery after removal of introduced Arctic foxes (Alopex lagopus) in the Aleutian Archipelago, Alaska. We compared relative seabird abundance among islands by examining levels of vocal activity. We deployed acoustic recorders on Nizki‐Alaid, Amatignak, and Little Sitkin islands that had foxes removed in 1975, 1991, and 2000, respectively, and on Buldir, a predator‐free seabird colony. Despite frequent gales, only 2.9% of 2230 recording hours from May to August of 2008 and 2009 were unusable due to wind noise. Recording quality and call recognition model success were highest when recording devices were placed at sites offering some wind shelter. We detected greater vocal activity of Fork‐tailed (Oceanodroma furcata) and Leach's (O. leucorhoa) storm‐petrels and Ancient Murrelets (Synthliboramphus antiquus) on islands with longer time periods since fox eradication. Also, by detecting chick calls in the automated recordings, we confirmed breeding by Ancient Murrelets on an island thought to be abandoned due to fox predation. Acoustic monitoring allowed us to examine the relative abundance of seabirds at remote sites. If a link between vocalizations and population dynamics can be made, acoustic monitoring could be a powerful census method.     

Psychoacoustic sampling as a reliable,non-invasive method to monitor orthopteran species diversity in tropical forests

We evaluated trained listener—based acoustic sampling as a reliable and non-invasive method for rapid assessment of ensiferan species diversity in tropical evergreen forests. This was done by evaluating the reliability of identification of species and numbers of calling individuals using psychoacoustic experiments in the laboratory and by comparing psychoacoustic sampling in the field with ambient noise recordings made at the same time. The reliability of correct species identification by the trained listener was 100 % for 16 out of 20 species tested in the laboratory. The reliability of identifying the numbers of individuals correctly was 100% for 13 out of 20 species. The human listener performed slightly better than the instrument in detecting low frequency and broadband calls in the field, whereas the recorder detected high frequency calls with greater probability. To address the problem of pseudoreplication during spot sampling in the field, we monitored the movement of calling individuals using focal animal sampling. The average distance moved by calling individuals for 17 out of 20 species was less than 1.5 m in half an hour. We suggest that trained listener—based sampling is preferable for crickets and low frequency katydids, whereas broadband recorders are preferable for katydid species with high frequency calls for accurate estimation of ensiferan species richness and relative abundance in an area.     

Manipulations of sensory experiences during development reveal mechanisms underlying vocal learning biases in zebra finches

Biological predispositions in learning can bias and constrain the cultural evolution of social and communicative behaviors (e.g., speech and birdsong), and lead to the emergence of behavioral and cultural “universals.” For example, surveys of laboratory and wild populations of zebra finches (Taeniopygia guttata) document consistent patterning of vocal elements (“syllables”) with respect to their acoustic properties (e.g., duration, mean frequency). Furthermore, such universal patterns are also produced by birds that are experimentally tutored with songs containing randomly sequenced syllables (“tutored birds”). Despite extensive demonstrations of learning biases, much remains to be uncovered about the nature of biological predispositions that bias song learning and production in songbirds. Here, we examined the degree to which “innate” auditory templates and/or biases in vocal motor production contribute to vocal learning biases and production in zebra finches. Such contributions can be revealed by examining acoustic patterns in the songs of birds raised without sensory exposure to song (“untutored birds”) or of birds that are unable to hear from early in development (“early‐deafened birds”). We observed that untutored zebra finches and early‐deafened zebra finches produce songs with positional variation in some acoustic features (e.g., mean frequency) that resemble universal patterns observed in tutored birds. Similar to tutored birds, early‐deafened birds also produced song motifs with alternation in acoustic features across adjacent syllables. That universal acoustic patterns are observed in the songs of both untutored and early‐deafened birds highlights the contribution motor production biases to the emergence of universals in culturally transmitted behaviors.     

Detecting tropical nocturnal birds using automated audio recordings

ABSTRACT Nocturnal bird assemblages are poorly known in most tropical locations, and information about their presence and behavior is often limited to the results of dawn or dusk surveys. We investigated the use of manual‐ and automatic‐detection methods to identify nocturnal birds in acoustic recordings made at Soberania National Park, Republic of Panama. Five nocturnal species were detected in dusk recordings, and a sixth species (Great Potoo, Nyctibius grandis) was detected only after dark. Automatic data template detectors (DTD's) were developed and used to detect Crested Owls (Lophostrix cristata), Black‐and‐White Owls (Ciccaba nigrolineata), Vermiculated Screech‐Owls (Megasops guatemalae), and Great Potoos. Manual analysis of 300 h of overnight recordings allowed us to quantify DTD performance. Sensitivity, the proportion of known calls of target species identified by DTDs, ranged from 0.17 for Black‐and‐White Owls to 0.79 for Vermiculated Screech‐Owls. Positive predictive value, the proportion of detected sounds that corresponded to the target species, ranged from 0.39 for Black‐and‐White Owls to 0.60 for Crested Owls. Our results demonstrate that a combination of manual and automated analysis of audio recordings can provide a verifiable, systematic method to determine the presence of nocturnal birds in tropical forests, investigate temporal activity, and calculate detection probability.     

Vocal behavior of Great Curassows,a vulnerable Neotropical bird

ABSTRACT The Cracidae rank among the most threatened families of Neotropical birds, and studies of their vocal behavior may help guide conservation and monitoring efforts. We describe the vocal behavior of Great Curassows (Crax rubra), a little‐studied Cracid species currently listed as vulnerable. From 2008 to 2010, we recorded curassows in northwest Costa Rica using both handheld and automated digital recorders. Analysis of recordings revealed that Great Curassows had a vocal repertoire of five call types. Yip and bark calls are sex‐specific alarm calls of short duration (0.12 and 0.08 s, respectively). The descending whistle is a longer duration alarm call (2.18 s) produced primarily by males. The snarl is a short call (0.67 s) associated with a threat display produced by adults with dependent young. The boom call was the most common Great Curassow vocalization, and was given only by males. Boom calls are long (8.86 s), low‐frequency (<150 Hz), multisyllable calls comprised of four stereotyped phrases. Great Curassows often uttered boom calls well before dawn, with a peak in activity at dawn and the hours following. Males produced bouts of repeated boom calls that lasted an average of 35 min, but sometimes continued for more than 5 h. Boom calls were given from February to June, with a peak in late April and early May when breeding begins. Discriminant analysis of boom calls of birds from 10 different locations revealed interindividual variation in call structure that may be useful for bioacoustic monitoring of individuals. Our results suggest that automated recorders might provide a way to monitor the abundance of male curassows because their boom calls are given frequently during the period from February to June and can be detected at distances up to 250 m.     

Animal Sound Identifier (ASI): software for automated identification of vocal animals

Automated audio recording offers a powerful tool for acoustic monitoring schemes of bird, bat, frog and other vocal organisms, but the lack of automated species identification methods has made it difficult to fully utilise such data. We developed Animal Sound Identifier (ASI), a MATLAB software that performs probabilistic classification of species occurrences from field recordings. Unlike most previous approaches, ASI locates training data directly from the field recordings and thus avoids the need of pre‐defined reference libraries. We apply ASI to a case study on Amazonian birds, in which we classify the vocalisations of 14 species in 194 504 one‐minute audio segments using in total two weeks of expert time to construct, parameterise, and validate the classification models. We compare the classification performance of ASI (with training templates extracted automatically from field data) to that of monitoR (with training templates extracted manually from the Xeno‐Canto database), the results showing ASI to have substantially higher recall and precision rates.     

Testing the conspecific attraction hypothesis with Dupont's Larks,a resident species of songbird in central Spain

Some birds use social cues, such as the presence of conspecifics, when selecting breeding habitat. This phenomenon, known as conspecific attraction, has been well‐documented in migratory species, but has not been assessed for resident species of birds. We used Dupont's Larks (Chersophilus duponti) as a model species to determine if conspecific attraction plays a role in habitat selection by resident species of birds. At our study site in Soria province in central Spain, we monitored two potential habitat patches and one managed site where management actions had provided apparently suitable habitat. At each site, we broadcast recordings of the songs and calls of male Dupont's Larks, and monitored their presence during the breeding season and dispersal period in 2018 using automated recorders and field surveys. No birds were attracted to our study sites. Our results suggest that management of patches of suitable habitat should occur close to areas (within 1 km) already occupied by Dupont's Larks to encourage natural colonization because, based on our results, playback of conspecific vocalizations may not attract the species to new breeding areas. However, additional studies are needed before drawing conclusions about the effectiveness of conspecific attraction for this and other resident species of birds.     

Applying bioacoustic methods for long-term monitoring of a nocturnal wetland bird

Bioacoustic monitoring is becoming more and more popular as a non-invasive method to study populations and communities of vocalizing animals. Acoustic pattern recognition techniques allow for automated identification of species and an estimation of species composition within ecosystems. Here we describe an approach where on the basis of long term acoustic recordings not only the occurrence of a species was documented, but where the number of vocalizing animals was also estimated. This approach allows us to follow up changes in population density and to define breeding sites in a changing environment. We present the results of five years of continuous acoustic monitoring of Eurasian bittern (Botaurus stellaris) in a recent wetland restoration area. Using a setup consisting of four four-channel recorders equipped with cardioid microphones we recorded vocal activity during entire nights. Vocalizations of bitterns were detected on the recordings by spectrogram template matching. On basis of time differences of arrival (TDOA) of the acoustic signals at different recording devices booming bitterns could be mapped using hyperbolic localization. During the study period not only changes in the number of calling birds but also changes in their spatial distribution connected with changes in habitat structure could be documented. This semi-automated approach towards monitoring birds described here could be applied to a wide range of monitoring tasks for animals with long distance vocalizations.     

大鹰鹃鸣声的日节律

鸟类的鸣唱具有吸引配偶和保卫领域的功能,多为雀形目雄性鸟类发出,在其婚配、繁殖中起重要作用。非雀形目鸟类缺乏内鸣肌,发出的声音较为单调。但杜鹃科(Cuculidae)等少数非雀形目鸟类,利用鸣叫来吸引异性和宣示领域,功能上类似雀形目鸟类的鸣唱。鸟类在繁殖期面临觅食等基本生理活动与求偶行为的时间权衡。而鸣唱是雄性鸟类在繁殖期耗能较多的求偶行为,鸣唱的活跃程度受到外界环境和鸟类自身习性的影响。通过研究鸟类鸣声的日节律,有助于了解鸟类对生活史策略的响应。本研究于2016年和2017年鸟类繁殖季在北京小龙门森林公园(40°00′N,115°26′E)进行。2016年和2017年在大鹰鹃(Hierococcyx sparverioides)活动区利用录音机(美国Wildlife Acoustics公司,型号SM4)分别录制了3 d和43 d的录音。通过Kaleidoscope Pro 4.0.3软件(美国Wildlife Acoustics公司),量化录音并提取反应大鹰鹃鸣声特征的参数,进而自动识别出录音中大鹰鹃的鸣声。在优化识别条件后,对大鹰鹃鸣声识别的正确率可以达到60.26%,探测率可以达到44.71%。发现大鹰鹃有两个鸣叫的高峰,一个在3:00时,另一个在19:00时。与同域分布的其他鸟类相比,大鹰鹃鸣声的高峰时段持续的时间更长,且具有夜间鸣叫的特点。结合大鹰鹃的生活史,我们对其鸣声日节律进行了讨论。     

Comparison of audio recording system performance for detecting and monitoring songbirds

ABSTRACT Acoustic recording systems are being used more frequently to estimate habitat occupancy or relative abundance, and to monitor population trends over time. A potential concern with digital recording systems is that changes in technology could affect detectability of birds and cause bias in trend estimates based on counts of birds detected. We evaluated several currently available commercial recording systems ranging from low‐cost multipurpose digital recorders to custom‐designed wildlife recorders (US$250–$7000 price range) to examine possible differences among systems in species detection. We made recordings during Breeding Bird Surveys (BBS) counts using several units concurrently, and asked several expert birders to listen to the recordings in a factorial design. We found that birders detected, on average, 10% fewer species on some units compared to others, though there was high variance. Analysis of a subset of recordings, using spectrograms and repeated listening, suggested that ～90% of species on each BBS stop could be clearly detected on all units. The remaining species could be identified on at least one unit, but were hard or impossible to detect on others. We found that the recording unit with the lowest empirical signal‐to‐noise‐ratio (SNR) had the lowest number of birds detected on the BBS recordings, and that frequency‐specific SNR differed among units. Missed detections were likely related to variation in internal noise and frequency‐dependent sensitivity of the units, and were an issue for all systems regardless of price. We caution that researchers using recorders need to consider variation among recording systems in their study design, particularly for long‐term monitoring programs.     

野生动物声音定位系统模拟实验及精度分析

声音通讯是动物交流的重要手段。利用声音定位野生动物,可以降低对动物的干扰,并且不受光线和生境的限制。2013年4~5月,在河南董寨国家级自然保护区利用鸣禽的鸣唱录音,检验了利用声音定位的精度。共选择4个样方,在样方的四个边角各放1台录音机,并在样方内随机选择播放点,播放雀形目鸟类的鸣唱。通过同一段声音到达不同录音机的时间差定位声源的位置,并与实际测量的位置相比较。结果得出5种鸣禽基于鸣声定位的平均精度为(1.89±0.99)m。本研究为该项技术在国内鸟类研究中的首次尝试,希望能为利用声音监测野生动物提供参考。     

A Comparative Study of the Songs and Alarm Calls of some Parus Species

Titmice vocalizations are presented with a view to examining variation within and between species. Analyses are derived from field recordings of British Parus species, and from available disc recordings. Spectrographic and oscillographic analyses are made of territorial song and alarm calls. The extent of song divergence and alarm call convergence is illustrated and discussed in addition to data on variation of these calls within species. Some brief notes on field behaviour are included and methods of sound production in birds discussed.     

Extending bioacoustic monitoring of birds aloft through flight call localization with a three‐dimensional microphone array

Bioacoustic localization of bird vocalizations provides unattended observations of the location of calling individuals in many field applications. While this technique has been successful in monitoring terrestrial distributions of calling birds, no published study has applied these methods to migrating birds in flight. The value of nocturnal flight call recordings can increase with the addition of three‐dimensional position retrievals, which can be achieved with adjustments to existing localization techniques. Using the time difference of arrival method, we have developed a proof‐of‐concept acoustic microphone array that allows the three‐dimensional positioning of calls within the airspace. Our array consists of six microphones, mounted in pairs at the top and bottom of three 10‐m poles, arranged in an equilateral triangle with sides of 20 m. The microphone array was designed using readily available components and costs less than $2,000 USD to build and deploy. We validate this technique using a kite‐lofted GPS and speaker package, and obtain 60.1% of vertical retrievals within the accuracy of the GPS measurements (±5 m) and 80.4% of vertical retrievals within ±10 m. The mean Euclidian distance between the acoustic retrievals of flight calls and the GPS truth was 9.6 m. Identification and localization of nocturnal flight calls have the potential to provide species‐specific spatial characterizations of bird migration within the airspace. Even with the inexpensive equipment used in this trial, low‐altitude applications such as surveillance around wind farms or oil platforms can benefit from the three‐dimensional retrievals provided by this technique.