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Visualization of temporal change in soundscape power of a Michigan lake habitat over a 4-year period
Abstract
Soundscape Ecology is an emerging area of science that does not focus on the identification of species in the soundscape but attempts to characterize sounds by organizing them into those produced by biological organisms such as birds, amphibians, insects or mammals; physical environmental factors such as thunder, rainfall or wind; and sounds produced by human entities such as airplanes, automobiles or air conditioners. The soundscape changes throughout the day and throughout the seasons. The soundscape components that create the sound occur at different frequencies. A set of metrics termed soundscape power was computed and visualized to examine the patterns of daily and seasonal change in the soundscape.
... The sound generates from every activity in any form destroys the soundscape of urban areas (Schafer 1993). The organized study of the relationships among organisms, humans, and their surroundings is known as Soundscape ecology (Schafer 1977(Schafer , 1993Gage and Axel 2014;Pijanowski et al. 2011aPijanowski et al. , 2011b or it is "the study of the soundscape's influence on the physical reactions or behavioural characteristics of the system's living things" (Gage and Axel 2014;Truax 1999). ...
... The sound generates from every activity in any form destroys the soundscape of urban areas (Schafer 1993). The organized study of the relationships among organisms, humans, and their surroundings is known as Soundscape ecology (Schafer 1977(Schafer , 1993Gage and Axel 2014;Pijanowski et al. 2011aPijanowski et al. , 2011b or it is "the study of the soundscape's influence on the physical reactions or behavioural characteristics of the system's living things" (Gage and Axel 2014;Truax 1999). ...
... These sounds originating from a landscape depend upon the time of the day, land pattern, weather/season, etc. The soundscape is deteriorating by different human activities such as the celebration of festivals Swain et al. 2013); activities in commercial banks, offices, and industries Goswami 2014a, 2014b;Goswami and Swain 2012b;Goswami et al. 2013;Goswami 2012a, 2012b;Goswami and Swain 2012a;Swain et al. 2012aSwain et al. , 2012b; road activities (Goswami 2009(Goswami , 2011Goswami 2013a, 2013b;Swain et al. 2012aSwain et al. , 2012bSwain et al. , 2016Goswami 2014a, 2014b;Pradhan et al. 2012aPradhan et al. , 2012b and other activities Goswami and Swain 2011;Gage and Axel 2014;Goswami and Swain 2017;Goswami 2018a, 2018b;Sahu et al. 2014;Krause 2012;Szeremeta and Zannin 2009;Warren et al. 2006;Zannin et al. 2006); and sounds produced by animals for communication during the mating time and other instances (Bradbury and Vehrencamp 2011). Presently, our environment is highly affected by vehicular traffic, which is a major anthropogenic activity (Gage and Axel 2014;Goswami 2012). ...
The soundscape study of an eastern Indian coastal city (Puri) has been investigated. Acoustic data were collected at 36 sampling locations during two time intervals in and around Puri. A number of noise indices, namely, Lmin, Lmax, and Leq, were calculated to demonstrate the noise level of this city. Noise maps are generated using ARC-GIS to investigate the impact of road traffic noise on the soundscape of the city. The response of the public was appraised by a questionnaire. Due to variable traffic features, the equivalent noise level (Leq) as well as peak (L10) and background noise (L90) levels varied with location and time of the day. It was found that socio-demographic characteristics have no bearing on the amount of annoyance. However, a link was observed between age, hearing condition, and noise perception, as well as between gender and impacts of noise.
... Over the last decades, soundscape ecology and, more recently, ecoacoustics, have repeatedly shown that distal and proximal forms of natural soundscapes, which are soundscapes marginally influenced by human activity, are structured in space and time (e.g., Rodriguez et al., 2014;Gage and Axel, 2014). Natural soundscapes convey information that can be extracted using a variety of signalprocessing methods to assess ecological patterns and processes of a given environment Sueur and Farina, 2015;Farina and Gage, 2017;Sugai et al., 2019;Sethi et al., 2020). ...
... Current knowledge in soundscape ecology and ecoacoustics suggests that discrimination among proximal natural soundscapes is based on acoustic cues associated with "biophony" (the combined sound that living organisms produce in a given habitat), "geophony" (the combined sound resulting from geophysical events, such as the wind, thunder, water flow, or earth movement), and habitat sound propagation characteristics (Krause, 1987;Forrest, 1994;Pijanowski et al., 2011;Sueur and Farina, 2015;Krause, 2016;Farina and Gage, 2017;Grinfeder et al., 2022). These cues may vary with biological and geophysical cycles (e.g., biophony peaks at dawn and dusk, and during spring) Gage and Axel, 2014). Because biological and geophysical sounds originate from a considerable variety of sources, they may be difficult to characterize. ...
... However, a few general properties have been put forward. Biophony is often assumed to correspond to mid-high audio frequency components ($2-11 kHz) (Gage and Axel, 2014;Farina and Gage, 2017) with relatively slow temporal modulations and fine harmonic structure (Lewicki, 2002;Theunissen and Elie, 2014). However, many animal vocalizations show low-frequency components (<1 kHz), fast fluctuations, and inharmonic or noisy characteristics (Hauser, 1996;Bradbury and Vehrencamp, 2011). ...
A previous modelling study reported that spectro-temporal cues perceptually relevant to humans provide enough information to accurately classify "natural soundscapes" recorded in four distinct temperate habitats of a biosphere reserve [Thoret, Varnet, Boubenec, Ferriere, Le Tourneau, Krause, and Lorenzi (2020). J. Acoust. Soc. Am. 147, 3260]. The goal of the present study was to assess this prediction for humans using 2 s samples taken from the same soundscape recordings. Thirty-one listeners were asked to discriminate these recordings based on differences in habitat, season, or period of the day using an oddity task. Listeners' performance was well above chance, demonstrating effective processing of these differences and suggesting a general high sensitivity for natural soundscape discrimination. This performance did not improve with training up to 10 h. Additional results obtained for habitat discrimination indicate that temporal cues play only a minor role; instead, listeners appear to base their decisions primarily on gross spectral cues related to biological sound sources and habitat acoustics. Convolutional neural networks were trained to perform a similar task using spectro-temporal cues extracted by an auditory model as input. The results are consistent with the idea that humans exclude the available temporal information when discriminating short samples of habitats, implying a form of a sub-optimality.
... The soundscape varies in different landscape spaces. Scholars have conducted various studies on urban forests and other public open spaces, which mainly focused on soundscape changes [9][10][11][12][13] and quality evaluation [14][15][16][17][18][19][20]. Ali Jahani et al. assessed the role of birdsong components in the psychological recovery of urban visitors and developed a decision support system as a practical tool [21]. ...
... The data resolution is set to 16 bit and the audio format was WAV. After sampling, we randomly intercepted 2 min of sound files within one hour [11], and had an average of 992 min of sound clips per day. ...
... Different entities in the soundscape produce sounds at different frequencies [11]. Sound signals depict frequency on the vertical axis of the spectrum and time on the horizontal axis. ...
We explored the spatial and temporal characteristics of the urban forest area soundscape by setting up monitoring points (70 × 70 m grid) covering the study area, recorded a total of 52 sound sources, and the results showed that: (1) The soundscape composition of the park is dominated by natural sounds and recreational sounds. (2) The diurnal variation of sound sources is opposite to that of temperature, 6:00–9:00 is the best time for the public to perceive birdsong, and after 18:00, the park is dominated by insect chirps. (3) The PSD (power spectral density) and the SDI (soundscape diversity index) of the park are greatly affected by public recreation behaviors, and some recreation behaviors may affect the vocal behavior of organisms such as birds. (4) Spaces with high canopy density can attract more birdsong and recreational sounds in summer, and the combination of “tree + lake” can attract more birdsong. Vegetation has a significant dampening effect on traffic sound. (5) Landscape spatial elements, such as the proportion of hard ground, sky, trees, and shrubs, have a significant impact on changes in the PSD, the SDI and different kinds of sound sources. The research results provide effective data support for improving the soundscape of urban forests.
... The PSD value for each 1 kHz frequency interval for each recording was then normalized using min-max normalization method and ranged from 0 to 1 for each of the 10 frequency intervals to facilitate comparison across recordings collected at different sites. The normalized PSD was termed soundscape power (SP) [52], it reflects the distribution of signals with different frequencies in the soundscape and was then constructed. ...
... Eco-acoustics basically assumes that communities with high diversity levels are able to generate a richer acoustic environment [16,19,20]; the acoustic index at the most active moment of acoustic activity in a day was chosen as the representative of that day. Bird species richness, which can be intuitively described by the number of species [52], was estimated by manually listening to the bird sound in the acoustic data, with the help of an experienced birdwatcher. ...
... The results were shown in Table 3. throphony, such as human talking and car honks are most prevalent between 1 and 2 kHz [13], just as shown in Figure 4e,f. Results in Figure 5 and Table 3 showed that sounds in range of 1-2 kHz were in considerable proportion, suggesting that there was remarkable anthropogenic interference [52]. Manually listening to the sounds also verified that there were sounds from human activities because all sampling sites were very close to the residential area of the protect and research station. ...
Passive acoustic sensor-based soundscape analysis has become an increasingly important ecological method for evaluation of ecosystem conditions using acoustic indices. Understanding the soundscape composition and correlations between acoustic indices and species richness of birds, the most important sound source in the ecosystem, are of great importance for measuring biodiversity and the level of anthropogenic disturbance. In this study, based on yearlong sound data obtained from five acoustic sensors deployed in Dalongtan, Shennongjia National Park, we analyzed the soundscape composition by comparing the distributions of the soundscape power in different frequency ranges, and examined the correlations between acoustic indices and bird species richness by means of the Spearman rank correlation coefficient method. The diurnal dynamic characteristics of acoustic indices in different seasons were also described. Results showed that the majority of sounds were in the frequency of 2-8 kHz, in which over 50% sounds were in 2-6 kHz, commonly considered the bioacoustic frequency range. The Acoustics Complexity Index, Bioacoustic Index, and Normalized Difference Soundscape Index were significantly correlated with bird species richness, suggesting that these indices can be used for evaluation of bird species richness; Apparent diurnal dynamic patterns of bird acoustic activities were observed in spring, summer, and autumn; however, the intensity and duration of bird acoustic activities in summer is larger/longer than in spring and autumn.
... As indicators of the characteristics of variation animal communities (Gasc et al., 2016), soundscapes provide acoustic diversity information at individual, population, species and community levels (Gasc et al., 2013). The established positive relationship between acoustic diversity with faunal species richness and diversity serves as the theoretical basis for the application of acoustic indices to ecological monitoring (Do Nascimento et al., 2020;Farina and Gage, 2017;Gage and Axel, 2014;Gasc et al., 2013;Pijanowski et al., 2011b). ...
... Just as the normalized difference vegetation index (NDVI) measures vegetation health, Normalized Difference Soundscape Index (NDSI) (Kasten et al., 2012) is proposed to be a measure of ecosystem health (Gage and Axel, 2014). Like the NDVI, NDSI uses a simple algorithm to compress a large amount of information into an ecological index. ...
... Our studies grouped and visualized different acoustic communities partitioned in the limited bandwidth over time and frequencies, which provide us more information about the peak of activity for urban species to establish the pattern of their activities, as well as possibly to inform ways to protect species, such as those that are sensitive to human disturbance or are too rare to find in conventional field surveys. (Gage and Axel, 2014). ...
Urban foresters are addressing the challenge of urban biodiversity loss through management plans in the context of rapid urbanization. Protecting the integrity of the urban ecosystem requires long-term monitoring and planning for resilience as well as effective management. The soundscape assessment has attracted attention in this field, but applying the soundscape assessment in urban ecological monitoring requires a protocol that links soundscapes to the impact of resource management on biodiversity over time. The effective processing and visualization of large-scale data also remains an important challenge. The aim of this study was to better understand the relationship between soundscape and physical environment, and examine the feasibility of this innovative soundscape approach in highly urbanized areas. Soundscape recordings were collected for 20 urban parks twice on 4 consecutive days in Spring. A total of 691,200 min of sound material were automatically obtained. In order to track the spatio-temporal patterns of a soundscape and determine its potential suitability for ecosystem monitoring, our study characterized soundscape information by adopting 4 widely used acoustic indices: acoustic diversity index (ADI), bioacoustic index (BIO), normalized difference vegetation index (NDSI), and power spectral density (PSD). Daily patterns of PSD have provided a potential connection between soundscapes and bird songs, and 1–2 kHz presented a similar pattern that was linked to human activity. Through further modeling, we tested the relationship of soundscapes to physical environment characteristics. The results showed the importance of habitat vegetation structure for acoustic diversity. More vertical heterogeneity, with an uneven canopy height or multilayered vegetation, was associated with more acoustic diversity. This suggests that clearing ground cover may have a significant negative impact on wildlife. Our results suggest that soundscape approaches provide a way to quickly synthesize large-scale recording data into meaningful patterns that can track changes in bird songs and ecosystem conditions. The proposed approach would enable regular assessment of urban parks and forests to inform adaptive planning and management strategies that can maintain or enhance biodiversity.
... While a variety of acoustic metrics and indices are available (BradferLawrence et al., 2019), the intention of this study was to utilize the figurative "lens" of soundscape power (Kasten et al., 2012) and NDSI (Gage and Axel, 2014) to describe the current state of the Aialik Bay coastal wilderness. Soundscape power has been successfully used to describe soundscapes in southcentral Alaska (Mullet et al., 2016(Mullet et al., , 2017a and coastal soundscapes in the Pacific Northwest (Ritts et al., 2016). ...
... Computations derived soundscape power after Kasten et al. (2012) as the normalized power spectral density (watts/kHz) at 1 kHz frequency intervals for the frequency ranges of 1000-11,000 Hz for each fiveminute sound recording. The NDSI was calculated as the ratio of soundscape power (normalized watts/kHz) corresponding to frequency intervals commonly associated with technophony (1-2 kHz) and biophony (>2 kHz) as described by Gage and Axel (2014). ...
I recorded the ambient sounds at three locations in the wilderness of Aialik Bay in Kenai Fjords National Park, Alaska between 25 June and 21 September 2019. My aim was to capture an ecoacoustic snapshot of the coastal soundscape to provide a comparable baseline for evaluating wilderness characteristics defined by the Wilderness Act of 1964. I visually and empirically characterized the Aialik Bay wilderness soundscape using the acoustic metrics of soundscape power (normalized watts/kHz) and Normalized Difference Soundscape Index (NDSI) from 5373 five-minute recordings, combined with visual and aural spectral examination of 4386 recordings. Soundscape power exhibited similar patterns across frequency intervals with sound sources primarily occurring in the low-frequency (1–2 kHz) and mid-frequency (2–5 kHz) intervals. Significant differences within frequency intervals between sites suggested the presence of distinct sonotopes. Low-frequency sounds were dominant across all three sites with peak soundscape power values across study days and 24 h timeframes attributed to wind and occasional periods of technophony emitted from commercial tour boats and private boating activities. Low-frequency geophony from wave action was ever present. Technophony exhibited some predictable patterns consistent with the timing of sightseeing boat tours. Peak values of soundscape power at mid-frequencies were attributed to the geophony of rain. Although biophonies were less common than geophonies, the choruses of songbirds were prevalent in July and promptly occurred daily between 0300 and 0600. Biophonies generally declined over the course of the day. All sites displayed negative NDSI values over most study days and consistently negative values over 24 h time frames, indicating a soundscape primarily influenced by low-frequency geophony and periods of technophony. However, NDSI values showed patterns and peaks similar to biophonies at mid-frequency intervals indicating biophony was still a notable contribution to this geophony-dominant soundscape. Despite the acoustic footprint of motorboat noise detected at all sample sites, the soundscape of the Aialik Bay wilderness was dominated by the natural sounds of geophony, biophony, and occasional periods of natural quiet indicative of a wilderness only partially impacted by technophony.
... These databases cover a wide variety of terrestrial biomes (e.g., forests, savannahs, grasslands, meadows, chaparrals, tundras, deserts) affected to different degrees by human activity. These include open and closed habitats from tropical, sub-tropical, temperate and arctic biomes that are often recorded with a relatively high temporal resolution (in most cases, 1 min every 15 min) for many months and seasons, and sometimes for several years (e.g., Gage & Axel, 2013). Figure 2 shows two-dimensional amplitude-modulation (2D-AMi) spectra computed by a model of human auditory processing (Thoret et al., 2020;Varnet et al., 2017) for a corpus of five natural soundscapes recorded in distinct terrestrial biomes on different continents at dawn or early morning: a boreal forest, a tropical forest, a temperate forest, a desert, and a savannah. ...
Research in hearing sciences has provided extensive knowledge about how the human auditory system processes speech and assists communication. In contrast, little is known about how this system processes "natural soundscapes," that is the complex arrangements of biological and geophysical sounds shaped by sound propagation through non-anthropogenic habitats [Grinfeder et al. (2022). Frontiers in Ecology and Evolution. 10: 894232]. This is surprising given that, for many species, the capacity to process natural soundscapes determines survival and reproduction through the ability to represent and monitor the immediate environment. Here we propose a framework to encourage research programmes in the field of "human auditory ecology," focusing on the study of human auditory perception of ecological processes at work in natural habitats. Based on large acoustic databases with high ecological validity, these programmes should investigate the extent to which this presumably ancestral monitoring function of the human auditory system is adapted to specific information conveyed by natural soundscapes, whether it operate throughout the life span or whether it emerges through individual learning or cultural transmission. Beyond fundamental knowledge of human hearing, these programmes should yield a better understanding of how normal-hearing and hearing-impaired listeners monitor rural and city green and blue spaces and benefit from them, and whether rehabilitation devices (hearing aids and cochlear implants) restore natural soundscape perception and emotional responses back to normal. Importantly, they should also reveal whether and how humans hear the rapid changes in the environment brought about by human activity.
... The recording parameters were set to a sampling frequency of 44.1 kHz, a resolution of 16 bits, and stereo sampling, with audio format saved in the WAV format. A total of 560 min of audio recordings were acquired through the collection of two-minute sound clips every two hours randomly (Gage and Axel 2014). If the center of the grid was inaccessible, appropriate adjustments were made to ensure data acquisition. ...
Acoustic indicators serve as an effective means of assessing the quality of urban green space soundscape. The informative, easy accessibility and non-invasive nature of acoustic monitoring renders it an excellent tool for studying the interaction among the natural environment, wildlife, and human activities. Urban green space is essential in the urban ecosystem and constitutes the primary location for public outdoor recreation. However, the existing methods for monitoring public recreational behavior, such as on-site observation, drone observation, or questionnaire interviews, require significant labor or professional expertise. All of these methods have their limitations, so there is still much to be researched in the acoustic indices and recreational behavior. As a result, the potential for using acoustic characteristics to monitor public recreational behavior remains underexplored. To address this gap, this study investigates the potential of 5 widely used acoustic indices and acoustic intensity for monitoring public recreational behavior: Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Richness (AR), Normalized Difference Soundscape Index (NDSI), and Power Spectral Density (PSD). Data were collected from 35 monitoring points in urban green spaces during the opening hours (6:00–22:00) to analyze the relationship between these indices and public recreational behavior. The findings indicate that (1) ACI, ADI, and AR daily exhibited multi-peak daily variation characteristics similar to those of public recreational behavior, displaying a “W” shape, while NDSI exhibits opposite variation characteristics; (2) the spatial variation characteristics of ACI, ADI, and AR change in response to the green space, and these changes align with public recreational behavior; (3) the correlation analysis and generalized linear mixed model construction further demonstrate that acoustic indices are effective in capturing the dynamic activities of visitor behavior; and (4) PSD undergoes significant temporal dynamic changes along the frequency gradient, with different frequency intervals reflecting the activity information of different recreational behaviors. In conclusion, this research highlights the effectiveness of using acoustic indices to analyze both the spatial and temporal variation char- acteristics of public recreational behavior in urban green spaces. The results can provide valuable data support for the enhancement and renovation of urban green spaces.
... The group stopped at each site for five minutes, standing or sitting while carefully listening to sound elements and feeling the thermal environment, then filled out a questionnaire online. The experimental process is shown in Figure 2. The primary leader was also responsible for using equipment to collect data, including temperature, global temperature, humidity, wind speed, and the LAeq (a weighted equivalent continuous sound level), for a continuous period of 5 min [64]. ...
Studying the impact of various factors on environmental perception is crucial because humans live in an environment where these factors interact and blend. The thermal-acoustic environment is the major factor that affects the overall perception of urban parks. This study focuses on urban parks in the subtropical region, with Xihu Park in Fuzhou, China, as the research area. Through measurements and questionnaires, this study explores the effects of the thermal-acoustic environment in urban parks on subjective evaluation (thermal assessment, acoustic assessment, and overall environmental assessment). The results reveal that: (1) a higher temperature significantly increases the sensation of heat and lowers thermal comfort, heat acceptance, and overall thermal environment evaluation scores. The type of sound source has a significant positive impact on thermal assessment, and the higher the ranking of the sound source type, the greater its positive impact on thermal assessment. (2) Regarding acoustic evaluation, higher sound pressure level is associated with more negative subjective ratings of loudness, harshness, intensity, and excitement. In contrast, positive sound sources can enhance comfort, preference, disorder, coordination, and overall soundscape evaluation. Additionally, temperature increases tend to result in more negative harshness, intensity, and coordination ratings. The interaction between temperature and sound pressure level also significantly affects subjective loudness, harshness, and intensity. (3) Overall environmental evaluation is also affected by temperature, with increasing temperatures leading to decreased comfort and satisfaction while increasing irritation. High sound pressure environments result in worse overall irritation ratings, while positive sound sources can significantly enhance overall comfort, irritation, and satisfaction ratings. Furthermore, the interaction between temperature and sound pressure level significantly impacts overall irritation and satisfaction ratings. These findings are significant for managing and improving the park’s thermal environment and soundscape, providing a practical framework for landscape architects.
... The group stopped at each site for five minutes, standing or sitting while carefully listening to sound elements and feeling the thermal environment, then filled out a questionnaire online. The experimental process is shown in Figure 2. The primary leader was also responsible for using equipment to collect data, including temperature, global temperature, humidity, wind speed, and the LAeq (a weighted equivalent continuous sound level), for a continuous period of 5 min [64]. ...
... ic sounds. These values may also reflect bird diversity, as NDSI reflects anthropogenic noise at low values (Gage, Axel, 2014) and bird species diversity at high values (Fuller et al., 2015). Values of diversity-based indices (ADI and H) also increased with forest age. ...
We investigated the properties of the sounds recorded on the territory of the National Park “Homilshanski Lisy” (Kharkiv region, Ukraine). Recordings were made at five points (in mature, middle-aged, and young oak forests, overgrown clear-cut and aspen forests). Data collection was carried out using on-site positioning of AudioMoth autonomous recorders, located on trees at a height of 1.5 m. The recording was made from April 11 to July 10, 2020, for 3 h in the morning and evening with a 5-min duration followed by a 10-min pause (24 recordings per day). Six acoustic indices (AIs) were calculated: Acoustic complexity index (ACI), acoustic diversity index (ADI), acoustic evenness index (AEI), bioacoustic index (BI), normalized difference soundscape index (NDSI), and acoustic entropy index (H). For the analysis, we used the Friedman test as well as a nonparametric analysis of the variance of the distance matrix and Tukey’s test. The results of the analysis showed the statistical significance of the influence of forest type, date and time of recording, as well as the effect of their pairwise interactions on all six acoustic indices, both in the morning and evening. For three indices – ACI, BI, and NDSI – the highest average values were noted in a mature oak forest and the lowest was in overgrown clear-cuts. We performed a PCA to reduce the number of variables and obtain insight into the variable relevance. The cumulative percentage of variance, explained by the first three principal components, is 84.5%. The first principal component is associated with H, BI, AEI, and ADI. The second and third principal components are associated with NDSI and ACI. The obtained results correspond to the results of quantitative bird counts carried out earlier in this area.
... The Sound Pressure Level (SPL) is a logarithmic measure of a ratio of the sound pressure of a sound to a reference sound pressure. Intensity indices were used for noise level assessment or in ecological studies, for example to assess avian biophony in various environments (Barber et al. 2010, Francis et al. 2011, González-Oreja et al. 2012, Gage and Axel 2014, Rodriguez et al. 2014. The inconvenience of these indices is that they do not provide any information on the number/identity of sound sources or on the frequency composition of the soundscape, which makes them inappropriate to estimate acoustic richness. ...
Passive acoustic monitoring can be used to assess the presence of vocal species. Automatic estimation of such information is critical for allowing diversity monitoring over long-time spans. Among the existing tools, α-acoustic indices have been originally designed to assess the richness/complexity of terrestrial soundscapes. However, their use in marine environments is impacted by fundamental differences between terrestrial and marine soundscapes. The aim of this study was to determine how they vary depending on the abundance and sound type richness of fish sounds. Fourteen indices used in terrestrial environments were tested. Indices were calculated on files from three sources: a controlled environment (playback of artificial tracks in a pool), in-situ playbacks (playback of natural soundscapes), and a natural environment (only natural sounds). The controlled experiment showed that some indices were correlated to sound abundance but not to sound type richness, implying that they are not capable of distinguishing the different types of fish sounds. With in-situ playbacks, indices were not able to capture differences, neither in terms of sound abundance nor sound type diversity. In the natural environment, there was no correlation between most of the indices and the abundance of sound. They were impacted by mass-phenomena of biological sounds (e.g., the Pomacentridae sounds in shallow reefs) that cannot inform on fish acoustic diversity. In contrast to terrestrial environments, frequency-bands in coastal marine soundscapes do not provide ecologically relevant information on diversity. Overall, indices do not appear suitable to infer marine fish sound diversity.
... In Figure 9, the average shape index (SHAPE) over 24 h was shown to rise rapidly at dawn chorus to reach the peak of the day, falling rapidly and remaining steady until dusk, when the chorus rose rapidly again, and then fluctuated and fell until the morning. The daily pattern of SHAPE is consistent with previous studies of other acoustic indices [27,31,102,103], thus reflecting a daily activity pattern and highlighting distinct dawn and dusk bird choruses. However, compared to other indices that only focus on sound intensity, SHAPE provides a new perspective on patterns of complexity of bird songs: songs of the dawn and dusk choruses tended to be more complex and elaborate than daytime songs. ...
In the context of rapid urbanization, urban foresters are actively seeking management monitoring programs that address the challenges of urban biodiversity loss. Passive acoustic monitoring (PAM) has attracted attention because it allows for the collection of data passively, objectively, and continuously across large areas and for extended periods. However, it continues to be a difficult subject due to the massive amount of information that audio recordings contain. Most existing automated analysis methods have limitations in their application in urban areas, with unclear ecological relevance and efficacy. To better support urban forest biodiversity monitoring, we present a novel methodology for automatically extracting bird vocalizations from spectrograms of field audio recordings, integrating object-based classification. We applied this approach to acoustic data from an urban forest in Beijing and achieved an accuracy of 93.55% (±4.78%) in vocalization recognition while requiring less than ⅛ of the time needed for traditional inspection. The difference in efficiency would become more significant as the data size increases because object-based classification allows for batch processing of spectrograms. Using the extracted vocalizations, a series of acoustic and morphological features of bird-vocalization syllables (syllable feature metrics, SFMs) could be calculated to better quantify acoustic events and describe the soundscape. A significant correlation between the SFMs and biodiversity indices was found, with 57% of the variance in species richness, 41% in Shannon’s diversity index and 38% in Simpson’s diversity index being explained by SFMs. Therefore, our proposed method provides an effective complementary tool to existing automated methods for long-term urban forest biodiversity monitoring and conservation.
... Soundscape construction is considered a new trend of thought that stimulates the potential of designers [15][16][17][18] and challenges the traditional dominance of vision in today′s space design. Previous studies have conducted soundscape change [19][20][21][22], quality assessment [23,24], spatial correlation [25], and restoration research [26] for different spatial environments. In terms of sound scene preferences, the difference in sound source types [27], sound source preferences, and perception experiences [28] have been the focus of attention in previous research. ...
Soundscape is an important part and one of the main factors of the underground space environment. Field surveys were conducted to evaluate the soundscape of underground commercial spaces and to compare it with the soundscape of the above-ground commercial spaces between two cities (Lu’an City and Hefei City) in China, consequently presenting the construction strategy of the soundscape of underground commercial spaces in urban areas. The results showed that the sound in the shopping center, which people found comfortable, was at the lower to intermediate level. The main sounds that people perceived as “general” sounds were environmental sounds such as music, the humming of the air conditioning, people talking, walking, and the hawking of the stores. Nevertheless, “very comfortable” sounds were background music and the sound of live performances, which were indicated in the majority of people’s opinions on evaluating a comfortable feeling, thus reflecting the impact of the sound of mall music on people′s cognitive psychology. Therefore, it is necessary to control the volume of environmental noise at a certain level so that people’s health is not adversely affected. It also helps shoppers to feel more comfortable psychologically and physiologically.
... There is continued debate surrounding methodological best practice, for example in terms of survey design Mooney et al., 2020;Sugai et al., 2020), data visualisation (Gage & Axel, 2014;Towsey et al., 2014) and the utility of various analytical approaches for rapidly summarising the soundscape in a management context (Alcocer et al., 2022;Bradfer-Lawrence et al., 2019;Gasc et al., 2015;Ross, Friedman, et al., 2021). ...
1. Passive Acoustic Monitoring (PAM) has emerged as a transformative tool for applied ecology, conservation, and biodiversity monitoring, but its potential contribution to fundamental ecology is less often discussed, and fundamental PAM studies tend to be descriptive, rather than mechanistic.
2. Here, we chart the most promising directions for ecologists wishing to use the suite of currently available acoustic methods to address long-standing fundamental questions in ecology and explore new avenues of research. In both terrestrial and aquatic habitats, PAM provides an opportunity to ask questions across multiple spatial scales and at fine temporal resolution, and to capture phenomena or species that are difficult to observe. In combination with traditional approaches to data collection, PAM could release ecologists from myriad limitations that have, at times, precluded mechanistic understanding.
3. We discuss several case studies to demonstrate the potential contribution of PAM to biodiversity estimation, population trend analysis, assessing climate change impacts on phenology and distribution, and understanding disturbance and recovery dynamics. We also highlight what is on the horizon for PAM, in terms of near-future technological and methodological developments that have the potential to provide advances in coming years.
4. Overall, we illustrate how ecologists can harness the power of PAM to address fundamental ecological questions in an era of ecology no longer characterised by data limitation.
... The Brown treecreeper, for example, was found in both shrub and non-shrub recording locations, despite being a tree dependent species (Doerr et al. 2006). Moreover, although we can estimate how far sound travels in the environment, it is impossible to establish a definitive detection radius for recorders, as it depends on environmental conditions such as humidity, time of day, and seasonality; (Gage and Axel 2014), land use and vegetation cover (Morton 1975) among other species-specific behaviours. Despite these limitations, we also successfully detected a threatened species (Pink cockatoo, L. leadbeateri), reinforcing the utility of acoustic recording for conservation and biodiversity monitoring purposes. ...
Context
Semi-arid landscapes are naturally heterogeneous with several factors influencing this variation. Fauna responses and adaptations vary in xeric environments, and the scale of observation is important. Biodiversity monitoring at several scales can be challenging, and acoustics are an alternative to this issue.
Objectives
We investigated how audible biodiversity is influenced by environmental factors (e.g.: vegetation metrics, climatic variables, etc.) across a fine spatial scale, aiming to provide a better understanding of the variation in audible species across recording locations placed close together. These results will improve the current knowledge on ecoacoustics as a tool for measuring ecological processes in this biome, and better inform conservation plans.
Methods
We collected data in the semi-arid region in Queensland, Australia placing 24 recorders 200 m apart for 48 h. We also sampled environmental attributes (e.g.: temperature and vegetation structure metrics) and used acoustic indices in a time-series algorithm to categorise sound into classes. Bird species and feeding guilds were also identified.
Results
We found significant differences between proximate sensors, demonstrating that soundscape differences occur across fine spatial scales. Birds and insects were the predominant biophonic sound observed and both groups were associated with shrub cover and subcanopy height. Environments with higher shrub and subcanopy cover had a higher percentage of all birds’ feeding guilds and insects. Sixty-three bird species were identified, including a threatened bird species in Queensland.
Conclusion
We show biodiversity is influenced by vegetation heterogeneity across fine spatial scales in semi-arid regions, identifying which attributes sustain higher levels of biodiversity activity. Our study reveals the practicality of acoustic surveys for this biodiversity monitoring by covering a large area in 48 h. However, we caution that scale is an important consideration when designing surveys.
... Scholars have conducted various studies on different spatial environments such as urban forests, green spaces and communities. The main concerns are soundscape change [27][28][29][30][31], quality evaluation [32][33][34][35][36], spatial dependence [37], and restoration studies [38]. In terms of soundscape preference, scholars have studied sound source preference [39], sound source type [40], perceptual experience [41], and demographic-sociological [42] differences. ...
Urban forest parks improve the environment by reducing noise, which can promote the development of physical and mental health. This study aimed to investigate the soundscape preferences of visitors in different spaces. It also provides practical suggestions for the study of urban green-space soundscapes. This study took the example of Moon Island Forest Park in Lu’an City, based on the questionnaire field survey that acquired public soundscape perception data. SPSS 26.0 was used to analyze five different spatial soundscape perception preferences in Moon Island Forest Park, starting from the subjective evaluation of users’ soundscape perception, based on user preference for different spatial sound source types. A one-way analysis of variance (ANOVA) was used and a separate analysis of soundscape preferences in each space was undertaken; the mean (SD) was also used to reveal the respondents’ preference for each sound-source perceptual soundscape. The study found that the five dimensions of different spaces were significantly correlated with sound perception preferences. First, the same sound source had different perceptual characteristics and differences in different functional areas. Second, different spatial features were influenced differently by typical sound sources. Third, in each functional area, water sound was the main sound source of positive impact and mechanical sound was the main source of negative impact. Mechanical sound had the greatest negative impact on the overall area. Overall, natural sound provided the most popular significant contribution to the soundscape preference; second was the human voice, and mechanical sound produced a negative effect. The results of these studies were analyzed from the perspective of soundscape characteristics in different spaces, providing a more quantitative basis for urban forest park soundscape design.
... Another research shows that passerines occupied more proportion in acoustic space, especially in the morning, and non-passerines were prominent in the dusk hours during the observation windows [18]. Furthermore, some non-passerines, which produce sounds at a low frequency, are more vulnerable to the geographical environment and artificial sounds, while passerines may be more sensitive to interference from other species that produce sounds at similar frequencies [19,20]. Although vocal communication can play equally significant functions among different bird taxa, the study of the acoustic patterns and ecology of vocal activity in non-passerines has received much less attention than in passerine species [21]. ...
There is an abundance of bird species in subtropical areas, but studies on the vocal behavior of non-passerines in subtropical regions are limited. In this study, passive acoustic monitoring was used to investigate the temporal acoustic patterns of the vocal activities of the Oriental Turtle Dove (Streptopelia orientalis) in Yaoluoping National Nature Reserve (YNNR) in eastern China. The results show that the vocal production of the Oriental Turtle Dove exhibited a seasonal variation, peaking in the period April–August. Additionally, its diurnal vocal activity displayed a bimodal pattern in late spring and summer, with the first peak in the morning and a secondary peak at dusk. Among weather factors, temperature significantly affected the temporal sound pattern of the Oriental Turtle Dove, instead of humidity and precipitation. This study, which was focused on sound monitoring technology, provides knowledge for further research on bird behavior and ecology. In the future, long-term sound monitoring could be used for managing and conserving bird biodiversity.
... Soundscapes can represent the health of an environment if acoustical niches correlate with ecological niches of vocal animals (Farina et al., 2011;Fuller et al., 2015;Gage & Axel, 2014;Kasten et al., 2012). Soundscapes can be used to detect early signs of bird stress or disturbance related to habitat or climate changes (Doser et al., 2020;Sueur & Farina, 2015). ...
Climate change is increasing aridity in grassland and desert habitats across the southwestern United States, reducing available resources and drastically changing the breeding habitat of many bird species. Increases in aridity reduce sound propagation distances, potentially impacting habitat soundscapes, and could lead to a breakdown of the avian soundscapes in the form of loss of vocal culture, reduced mating opportunities, and local population extinctions. We developed an agent-based model to examine how changes in aridity will affect both sound propagation and the ability of territorial birds to audibly contact their neighbors. We simulated vocal signal attenuation under a variety of environmental scenarios for the south, central semi-arid prairies of the United States, ranging from contemporary weather conditions to predicted droughts under climate change. We also simulated how changes in physiological conditions, mainly evaporative water loss (EWL), would affect singing behavior. Under contemporary and climate change-induced drought conditions, we found that significantly fewer individuals successfully contacted all adjacent neighbors than did individuals in either the contemporary or predicted climate change conditions. We also found that at higher sound frequencies and higher EWL, fewer individuals were able to successfully contact all their neighbors, particularly in drought and climate change drought conditions. These results indicate that climate change-mediated aridification may alter the avian soundscape, such that vocal communication no longer effectively functions for mate attraction or territorial defense. As climate change progresses, increased aridity in current grasslands may favor shifts toward low-frequency songs, colonial resource use, and altered songbird community compositions.
... Substantial changes in natural soundscapes have occurred due to increases in human use (Slabbekoorn et al., 2010;Butler et al., 2016;Buxton et al., 2017;Duarte et al., 2021), and a recent body of research has focused on anthropogenic noise and its detrimental impacts on organism physiology and behavior (e.g., Luczkovich and Sprague, 2008;de Soto et al., 2013;Hawkins and Popper, 2017;Jones et al., 2020). Increasing attention is also being given to soundscape measurement and analysis as an approach to monitor the impacts of human disturbance and climate change on biodiversity (Gage and Axel, 2014;Krause and Farina, 2016;Lamont et al., 2022). Far less is known about climate-driven changes to the soundscape and the biological drivers of those potential alterations, particularly for acoustically-rich ocean habitats. ...
The ocean’s soundscape is fundamental to marine ecosystems, not only as a source of sensory information critical to many ecological processes but also as an indicator of biodiversity and habitat health. Yet, little is known about how ecoacoustic activity in marine habitats is altered by environmental changes such as temperature. The sounds produced by dense colonies of snapping shrimp dominate temperate and tropical coastal soundscapes worldwide and are a major driver broadband sound pressure level (SPL) patterns. Field recordings of soundscape patterns from the range limit of a snapping shrimp distribution showed that rates of snap production and associated SPL were closely positively correlated to water temperature. Snap rates changed by 15-60% per °C change in regional temperature, accompanied by fluctuations in SPL between 1-2 dB per °C. To test if this relationship was due to a direct effect of temperature, we measured snap rates in controlled experiments using two snapping shrimp species dominant in the Western Atlantic Ocean and Gulf of Mexico ( Alpheus heterochaelis and A. angulosus ). Snap rates were measured for shrimp held at different temperatures (across 10-30 °C range, with upper limit 2°C above current summer mean temperatures) and under different social groupings. Temperature had a significant effect on shrimp snap rates for all social contexts tested (individuals, pairs, and groups). For individuals and shrimp groups, snap production more than doubled between mid-range (20°C) and high (30°C) temperature treatments. Given that snapping shrimp sounds dominate the soundscapes of diverse habitats, including coral reefs, rocky bottoms, seagrass, and oyster beds, the strong influence of temperature on their activity will potentially alter soundscape patterns broadly. Increases in ambient sound levels driven by elevated water temperatures has ecological implications for signal detection, communication, and navigation in key coastal ecosystems for a wide range of organisms, including humans.
... Soundscapes can represent the health of an environment if acoustical niches correlate with ecological niches of vocal animals (Farina et al., 2011;Kasten et al., 2012;Gage and Axel, 2014;Fuller et al., 2015). Soundscapes can be used to detect early signs of bird stress related to changes in habitat or climate (Sueur and Farina, 2015). ...
Climate change is increasing aridity in grassland and desert habitats across the southwestern United States, reducing available resources and drastically changing the breeding habitat of many bird species. Increases in aridity reduce sound propagation distances, potentially impacting habitat soundscapes, and could lead to a breakdown of the avian soundscapes in the form of loss of vocal culture, reduced mating opportunities, and local population extinctions. We developed an agent-based model to examine how changes in aridity will affect both sound propagation and the ability of territorial birds to audibly contact their neighbors. We simulated vocal signal attenuation under a variety of environmental scenarios for the south central semi-arid prairies of the United States, ranging from contemporary weather conditions to predicted droughts under climate change. We also simulated how changes in physiological conditions, mainly evaporative water loss (EWL), would affect singing behavior. Under contemporary and climate change induced drought conditions, we found significantly fewer individuals successfully contacted all adjacent neighbors than did individuals in either the contemporary or predicted climate change conditions. We also found that at higher sound frequencies and higher EWL, fewer individuals were able to successfully contact all their neighbors, particularly in the drought and climate change drought conditions. These results indicate that climate change-mediated aridification may disrupt the avian soundscape, such that vocal communication no longer effectively functions for mate attraction or territorial defense. As climate change progresses increased aridity in current grasslands may favor shifts toward low frequency songs, colonial resource use, and altered songbird community compositions.
... Events Per Second was correlated with Low Frequency Cover and Temporal Entropy and showed a clear peak during the day, but no peaks at dawn and dusk. This might have related to an increase in geophony and anthropophony during the day recordings (Figure 2), which should both be related to Low Frequency Cover (Gage and Axel, 2014;Shaw et al., 2021). The two-species mixtures were a result of establishment failure of Cordia alliodora. ...
In this ecoacoustic study we used the setting of a tropical tree diversity planted forest to analyze temporal patterns in the composition of soundscapes and to test the effects of tree species richness on associated biodiversity measured as acoustic diversity. The analysis of soundscapes offers easy, rapid and sustainable methods when assessing biodiversity. During the last years the quantification of regional or global acoustic variability in sounds and the analysis of different soundscapes has been evolving into an important tool for biodiversity conservation, especially since case studies confirmed a relationship between land-use management, forest structure and acoustic diversity. Here we analyzed soundscapes from two seasons (dry and rainy season) and aurally inspected a subset of audio recordings to describe temporal patterns in soundscape composition. Several acoustic indices were calculated and we performed a correlation analysis and a non-metric multidimensional scaling analysis to identify acoustic indices that: (i) were complementary to each other and such represented different aspects of the local soundscapes and (ii) related most strongly to differences in acoustic composition among tree species richness, season and day phase. Thus, we chose “High Frequency Cover,” “Bioacoustic Index,” and “Events Per Second” to test the hypothesis that acoustic diversity increases with increasing tree species richness. Monocultures differed significantly from polycultures during night recordings, with respect to High Frequency Cover. This index covers sounds above 8 kHz and thus represents part of the orthopteran community. We conclude that increasing tree species richness in a young tropical forest plantation had positive effects on the vocalizing communities. The strongest effects were found for acoustic activity of the orthopteran community. In contrast to birds, orthopterans have smaller home ranges, and are therefore important indicator species for small scale environmental conditions.
... ;Bormpoudakis, Sueur, & Pantis, 2013;Gage & Axel, 2014;Fuller et al., 2015;Grant & Samways, 2016).Different acoustic indices express different behavior and highlight different aspects of a soundscapeTowsey, Zhang, Cottman-Fields et al., 2014). For example: the acoustic complexity index (ACI)(Pieretti, Farina, & Morri, 2011) showed high sensitivity to the dynamics of bird choruses, while an index of acoustic cover (CVR) was most sensitive in response to continuous cicada choruses. ...
Rapid changes of the biosphere observed in recent years are caused by both small and large scale drivers, like shifts in temperature, transformations in land-use, or changes in the energy budget of systems. While the latter processes are easily quantifiable, documentation of the loss of biodiversity and community structure is more difficult. Changes in organismal abundance and diversity are barely documented. Censuses of species are usually fragmentary and inferred by often spatially, temporally and ecologically unsatisfactory simple species lists for individual study sites. Thus, detrimental global processes and their drivers often remain unrevealed. A major impediment to monitoring species diversity is the lack of human taxonomic expertise that is implicitly required for large-scale and fine-grained assessments. Another is the large amount of personnel and associated costs needed to cover large scales, or the inaccessibility of remote but nonetheless affected areas.
To overcome these limitations we propose a network of Automated Multisensor stations for Monitoring of species Diversity (AMMODs) to pave the way for a new generation of biodiversity assessment centers. This network combines cutting-edge technologies with biodiversity informatics and expert systems that conserve expert knowledge. Each AMMOD station combines autonomous samplers for insects, pollen and spores, audio recorders for vocalizing animals, sensors for volatile organic compounds emitted by plants (pVOCs) and camera traps for mammals and small invertebrates. AMMODs are largely self-containing and have the ability to pre-process data (e.g. for noise filtering) prior to transmission to receiver stations for storage, integration and analyses. Installation on sites that are difficult to access require a sophisticated and challenging system design with optimum balance between power requirements, bandwidth for data transmission, required service, and operation under all environmental conditions for years. An important prerequisite for automated species identification are databases of DNA barcodes, animal sounds, for pVOCs, and images used as training data for automated species identification. AMMOD stations thus become a key component to advance the field of biodiversity monitoring for research and policy by delivering biodiversity data at an unprecedented spatial and temporal resolution.
... Developments in data acquisition, storage, and processing have led to Passive Acoustic Monitoring (PAM) approaches-so called because recorders can collect data autonomously-increasingly being adopted for a wide array of ecological applications and conservation management (Lomolino et al. 2015;Deichmann et al. 2018;Gasc et al. 2018;Burivalova et al. 2019aBurivalova et al. , 2019bElise et al. 2019;Sethi et al. 2020aSethi et al. , 2020bDuarte et al. 2021;Keitt & Abelson 2021). Despite its increasing popularity, there remains considerable debate surrounding methodological best practice in PAM studies, for example in terms of survey design Sugai et al. 2020), data visualisation (Gage & Axel 2014;Towsey et al. 2014), and the utility of a suite of acoustic indices for rapidly summarising the soundscape when applied in a management context Bradfer-Lawrence et al. 2019;Ross et al. 2021b). Regardless, PAM is now widely accepted as a useful addition to the environmental monitoring toolkit (Gibb et al. 2019;Guan et al. 2021). ...
Through global environmental change, humans are modifying the planet at an unprecedented rate and scale, triggering the ongoing biodiversity and climate crises. Ecological stability and the consistency of nature’s contributions to people are fundamental to the continued sustainability of human societies. Stability is a complex and multidimensional concept including components such as variability in time and space and the resistance to and recovery from disturbances. Global change has the potential to destabilise ecosystems, but the form and strength of the relationship between different global change drivers and dimensions of stability remains understudied, precluding general or mechanistic understanding. Here, I combine theory, a field experiment, and observational data from a high-resolution acoustic monitoring network to reveal the potential for multiple global change drivers to erode multidimensional ecological stability. Critically, I also show how biodiversity and natural habitats can buffer the destabilising effects of global environmental change on ecosystems and soundscapes, providing vital insurance against disturbance. In an era characterised by unrelenting global change and intensifying disturbance regimes, my results provide a key step towards a generalisable understanding—and ultimately management—of the stability of ecosystems and their contributions to human wellbeing.
... For example, the acoustic diversity index is based on the Shannon diversity index (Shannon and Weaver, 1964). NDSI (Gage and Axel, 2014) measures the ratio between biophony (biological sounds) and anthrophony (human and technological sounds) and is derived from NDVI, an index used in the remote sensing analysis of vegetation (Pettorelli, 2013). Acoustic indices have been used in different contexts such as to evaluate the differences in faunal beta-diversity between forests and plantations (Hayashi et al., 2020), to detect rainfall in acoustic recordings (Sánchez-Giraldo et al., 2020), to examine differences among indices representing taxonomic groups (e.g., birds, anurans, mammals and insects) (Ferreira et al., 2018), to relate indices with bird diversity (Tucker et al., 2014), and to identify frog species (Brodie et al., 2020). ...
High rates of biodiversity loss caused by human-induced changes in the environment require new methods for large scale fauna monitoring and data analysis. While ecoacoustic monitoring is increasingly being used and shows promise, analysis and interpretation of the big data produced remains a challenge. Computer-generated acoustic indices potentially provide a biologically meaningful summary of sound, however, temporal autocorrelation, difficulties in statistical analysis of multi-index data and lack of consistency or transferability in different terrestrial environments have hindered the application of those indices in different contexts. To address these issues we investigate the use of time-series motif discovery and random forest classification of multi-indices through two case studies. We use a semi-automated workflow combining time-series motif discovery and random forest classification of multi-index (acoustic complexity, temporal entropy, and events per second) data to categorize sounds in unfiltered recordings according to the main source of sound present (birds, insects, geophony). Our approach showed more than 70% accuracy in label assignment in both datasets. The categories assigned were broad, but we believe this is a great improvement on traditional single index analysis of environmental recordings as we can now give ecological meaning to recordings in a semi-automated way that does not require expert knowledge and manual validation is only necessary for a small subset of the data. Furthermore, temporal autocorrelation, which is largely ignored by researchers, has been effectively eliminated through the time-series motif discovery technique applied here for the first time to ecoacoustic data. We expect that our approach will greatly assist researchers in the future as it will allow large datasets to be rapidly processed and labeled, enabling the screening of recordings for undesired sounds, such as wind, or target biophony (insects and birds) for biodiversity monitoring or bioacoustics research.
... type or indicators Classify or map habitat type or indicators (e.g., land cover, functional group) from terrestrial laser imageryRehush et al. (2018) Autonomous camera-trap images Individual animal recognition Identify or count individual animals using individual recognition (e.g., Facial recognition) from camera-trap imagesSchofield et al. (2019) Terrestrial animal species Classify species of terrestrial animals (often medium-to largesized mammals such as primates, ungulates, and felids) from terrestrial camera-trap imagesYu et al. (2013) Aquatic animal species Classify aquatic animal species from underwater camera-trap imagesZhang et al. (2016) Non-autonomous camera images in field or laboratory Microorganism Classify the taxonomic group of a microorganism from closerange or microscopic images Buetti-Dinh et al.(2019),Cheng et al. (2019) models for identifying bat species are welldeveloped and commercially available (e.g., Kaleidoscope Pro, SonoBat). To our knowledge, no pre-trained models are widely available for other taxa aside from the recently released BirdNET model(Kahl et al. 2021), although models for bird species, and for anurans to a certain degree, are an active area of development and improvement(Acevedo et al. 2009, Aide et al. 2013, Bedoya et al. 2014, Gage and Axel 2014, Priyadarshani et al. 2018, Lapp et al. 2021). ...
A core goal of the National Ecological Observatory Network (NEON) is to measure changes in biodiversity across the 30‐yr horizon of the network. In contrast to NEON’s extensive use of automated instruments to collect environmental data, NEON’s biodiversity surveys are almost entirely conducted using traditional human‐centric field methods. We believe that the combination of instrumentation for remote data collection and machine learning models to process such data represents an important opportunity for NEON to expand the scope, scale, and usability of its biodiversity data collection while potentially reducing long‐term costs. In this manuscript, we first review the current status of instrument‐based biodiversity surveys within the NEON project and previous research at the intersection of biodiversity, instrumentation, and machine learning at NEON sites. We then survey methods that have been developed at other locations but could potentially be employed at NEON sites in future. Finally, we expand on these ideas in five case studies that we believe suggest particularly fruitful future paths for automated biodiversity measurement at NEON sites: acoustic recorders for sound‐producing taxa, camera traps for medium and large mammals, hydroacoustic and remote imagery for aquatic diversity, expanded remote and ground‐based measurements for plant biodiversity, and laboratory‐based imaging for physical specimens and samples in the NEON biorepository. Through its data science‐literate staff and user community, NEON has a unique role to play in supporting the growth of such automated biodiversity survey methods, as well as demonstrating their ability to help answer key ecological questions that cannot be answered at the more limited spatiotemporal scales of human‐driven surveys.
... For example, entry 2.3 of ISO 12913-1:2014 [118] defines "soundscape" as "acoustic environment as perceived or experienced and/or understood by a person or people, in context." However, the same term is used without this implication in contexts other than human hearing, in air [119]- [121], and in water [122]- [124]. For this reason, the definition of "soundscape" according to ISO 18405:2017 [46] (entry 3.1.1.3) ...
Applications of underwater acoustics include sonar, communication, geophysical imaging, acoustical oceanography, and bioacoustics. Specialists typically work with little interdisciplinary interaction, and the terminology they employ has evolved separately in each discipline, to the point that transdisciplinary misunderstandings are common. Furthermore, increasing societal concern about possible detrimental effects of underwater noise on aquatic animals has led national and international regulators to require monitoring of underwater noise, with a consequent need for interdisciplinary harmonization of terminology. By adopting a common language, we facilitate the effective communication of concepts and information in underwater acoustics, whether for research, technology, or regulation. In the words of William H. Taft, “Don't write so that you can be understood, write so that you can't be misunderstood.” Clear definitions of widely used terms are needed, such as those used for the characterization of sound fields (e.g., “soundscape” and “ambient noise”), sound sources (“source level” and “source waveform”), sound propagation (“transmission loss” and “propagation loss”), and sound reception (“hearing threshold” and “frequency weighting function”). Terms that are used synonymously in one application have different meanings in another (examples include “hearing threshold” versus “detection threshold” and “transmission loss” versus “propagation loss”). Distinct definitions for these and many other acoustic terms are provided in a standard published in April 2017 by the International Organization for Standardization, ISO 18405. This article summarizes ISO 18405 and the process that led to the published definitions, including the reasons for omitting some terms.
... The development of soundscape indices (also referred to as acoustic indexes) has allowed for unique, rich, and informative quantitative measurement and characterization of diverse landscapes Pijanowski et al. 2011;Farina 2013, Villanueva-Rivera et al. 2011;Zhao et al. 2019). For example, researchers have used soundscape indices to characterize change in ecosystems, phenology, circadian rhythms, and biological diversity (Sueur et al. 2008b, Gasc et al. 2013Gage and Axel 2014;Pieretti et al. 2015;Buxton et al. 2017;Quinn et al. 2018;Whalen et al. 2019;Gerber et al. 2020, Schindler et al. 2020. The specifics of each index are discussed in the aforementioned citations, reviewed by (Bradfer-Lawrence et al. 2019), and summarized in the methods below. ...
ContextMost data collection and analyses in soundscape ecology have focused on summer or breeding seasons in urban or protected landscapes, missing important acoustic dynamics in winter, non-breeding periods and in agricultural landscapes, a land-use that constitutes 39% of ice-free surface globally.Objectives
To address these gaps, we examined the variation of winter soundscapes across a rural agricultural landscape of Nebraska, USA. We compared high and low traffic sites, testing if traffic levels affected soundscape structure.Methods
We recorded sound over two winters at 19 sites located adjacent to major and minor roadways. We calculated eight unique soundscape indexes to quantify the soundscape over time as a function of traffic and land cover. We applied filters at 80, 1000, and 2000 Hz.ResultsWe found clear statistical differences between high and low traffic sites in 7 of 8 soundscape indexes. Soundscape varied throughout the day, but not throughout the season. There was a clear negative correlation between technophony (human-derived sounds) and biophony (ecologically derived sounds) across sites. We found that not all indices may be suitable for all ecosystems.Conclusions
We quantified the effects of noise pollution on the soundscape of understudied habitats during winter months. By using soundscape indexes as surrogates for biodiversity, acoustic sampling could be an effective method for monitoring biodiversity when traditional methods may be ineffective or too costly. However, caution needs to be taken when choosing indices.
... Recent studies indicate that acoustic metrics respond to different spatial scales, with the magnitude of their associations with landscape elements being affected by how the scale delimiting the soundscape is defined and in which such attributes are estimated (Dooley and Brown, 2020;Dein and Rüdisser, 2020). Likewise, the connection between acoustic metrics and landscape elements may respond to the temporal dynamics of the soundscape, varying in magnitude across seasons or even emerging only at specific daily periods (Gage and Axel, 2014;Mullet et al., 2016). ...
tSoundscape research has acquired a paramount role in biodiversity conservation as it may provide timelyand reliable information about the ecological integrity. The relationship between soundscape complexityand ecological integrity in highly biodiverse environments, as well as the factors affecting this relation-ship require a thorough understanding. We determined how the soundscape relates to the landscapeecological integrity at different spatial and temporal scales in a montane forest in the northern Andes ofColombia. Between May–July 2018 we obtained acoustic recordings from 31 sampling sites in the pro-tected area of a hydropower plant, and estimated nine acoustic indices and an ecological integrity index(EII) derived from fragmentation, connectivity, and habitat quality. Five of the acoustic indices, linked tothe evenness of the acoustic signals and levels of the biophonic signals, were associated with changesin the EII and indicated the presence of more even, saturated, and acoustically rich soundscapes in siteswith higher integrity. Relationships between acoustic indices and the EII were stronger at a smaller spa-tial scale (100 m) and responded to daily variation of the soundscape, with the strongest associationsoccurring mainly from sunrise to noon. We show that acoustic indices measuring the evenness of theacoustic activity distribution and the number of frequency peaks reliably reflect the changes in the eco-logical integrity, and can be integrated with remote sensing as a tool for landscape management. Ourresults highlight the soundscape analysis as a feasible approach for the monitoring and conservationplanning of acoustically unknown and threatened Andean landscapes.
... However, they have been mostly used in research focused on specific aspects of the environment (oftentimes the information about biodiversity that could be obtained with the biophony, or environmental information in general), paying less attention to other components (human generated sound but also rain or wind, for example) and also often filtering part of the frequency spectrum accordingly (Gasc et al., 2015;. Other research focused on specific indices, like acoustic complexity (Pieretti et al., 2011;Farina et al., 2018Farina et al., , 2021 or the Normalized Difference Soundscape Index (Gage and Axel, 2014;Ritts et al., 2016), showing how they reveal a variety of environmental information. In most of the cases (with the exception of Farina et al. who use a common acoustic event library for all sites), each recording site is processed separately in these studies, and the samples are not gathered in a single database, which does not allow for the direct comparison of sonic or acoustic patterns across sites. ...
Soundscapes are increasingly used as innovative entry doors in environmental studies. Facing huge libraries of sound files which cannot be processed manually, acoustic indices provide an overview to the information contained in them, as well as to allow for automatic processing. Studies dealing with such indices have, however, focused more on specific topics or indices than on the overall characteristics of the soundscapes they were analyzing. The aim of this paper is to propose a holistic approach to soundscapes. Our hypothesis is that sufficient number and variety of indices can help frame the characteristics of sound environments and that the use of clustering algorithms allows us to group them in families and study the distribution of those across space and time, revealing a geography that will not necessarily coincide with the obvious landscape/visual geography. To demonstrate this point, we have run indices analysis and classification on a soundscapes database recorded in the Sonoran Desert region (Southeastern Arizona, USA). The results show that sound indices reveal temporal variations and patterns of soundscapes and point out to sometimes surprising similarities between otherwise different environments. As sound indices capture a wealth of information which characterizes the environment at a given place and time, they could be used as proxies to continuous monitoring without having to store extreme amounts of data.
... The oceans abound with natural physical sounds (from wind, rain, polar ice, and seismic activity), biological sounds (from crustaceans, fishes, and marine mammals), and anthropogenic sounds (from transport, construction, offshore exploration, and mining). Soundscapes naturally change over time because of temporal cycles in weather (e.g., cyclones and annual monsoon [1,2]) and animal behaviour (e.g., diurnal foraging patterns, lunar spawning, seasonal mating, and annual migration [3][4][5][6]). However, in many habitats, soundscapes further change with patterns of human presence (e.g., temporary construction or summer recreation [7]) and some have changed steadily over time with increasing intensity of anthropophony (e.g., due to shipping [8]). ...
Marine soundscapes consist of cumulative contributions by diverse sources of sound grouped into: physical (e.g., wind), biological (e.g., fish), and anthropogenic (e.g., shipping)—each with unique spatial, temporal, and frequency characteristics. In terms of anthropophony, shipping has been found to be the greatest (ubiquitous and continuous) contributor of low-frequency underwater noise in several northern hemisphere soundscapes. Our aim was to develop a model for ship noise in Australian waters, which could be used by industry and government to manage marine zones, their usage, stressors, and potential impacts. We also modelled wind noise under water to provide context to the contribution of ship noise. The models were validated with underwater recordings from 25 sites. As expected, there was good congruence when shipping or wind were the dominant sources. However, there was less agreement when other anthropogenic or biological sources were present (i.e., primarily marine seismic surveying and whales). Off Australia, pristine marine soundscapes (based on the dominance of natural, biological and physical sound) remain, in particular, near offshore reefs and islands. Strong wind noise dominates along the southern Australian coast. Underwater shipping noise dominates only in certain areas, along the eastern seaboard and on the northwest shelf, close to shipping lanes.
... Audio recordings, however, are comparably effective at capturing changing patterns in wildlife presence or behavior Pijanowski et al., 2011a) and deliver data with millisecond-level temporal resolution. With recent advances in storage capacity and energy efficiency, acoustic recorders can now capture months or years of data between servicing periods (Gage and Axel, 2014;Gibb et al., 2019;Hill et al., 2018), making this technology highly useful for assessing the animal impacts of unpredictable pulse disturbances. ...
Disturbance regimes and biodiversity—two factors that govern the stability of ecosystems—are changing rapidlydue to anthropogenic forces including climate change. Determining whether ecosystems retain their structure and function through intensifying disturbance regimes is an urgent task. However, quantitatively assessing the resilience of natural systems is a complex and challenging endeavor, especially for animal communities, for which datasets around disturbance events are scarce. Here, we apply an emerging remote sensing tech-nology—the recording and analysis of soundscapes—to quantify the resilience of Puerto Rican coral reef and dry forest animal communities in relation to Hurricane Maria, which struck the island in September 2017. Using recordings collected between March 2017 and January 2018 at three terrestrial and three marine sites, we measured three dimensions of resilience—the magnitude of the impacts (resistance), the spatial pattern of the impacts (heterogeneity), and the diversity and timeline of functional responses (recovery)—across eight sound types representing different broad taxonomic groups. While the coral reef communities exhibited high resistance to the storm, all sound types within the dry forest were significantly impacted, with two of the three insect choruses and bird vocalizations at dawn declining approximately 50% in the weeks following Hurricane Maria. The mid-frequency insect sound type returned to pre-storm levels after 56 days, while bird vocalizations returned after 67 days, though seasonal and lunar patterns underscored the importance of long-term data for accurately measuring trajectories of recovery. This study demonstrates that soundscape methodologies can help to quantify elusive dimensions of animal community resilience in order to better understand how biodiversity and ecosystem functioning will change under novel disturbance regimes.
... Acoustic indices have been used as biodiversity surrogates (Depraetere et al., 2011;Sueur et al., 2008) and have facilitated our understanding of ecosystems and how they are structured and change across spatiotemporal scales (Gage and Axel, 2014;Priyadarshani et al., 2018;Towsey et al., 2014). However, some contention surrounds the use of acoustic indices as surrogates for biodiversity where they can be limited in their utility in certain environments (e.g. ...
As the rate of urbanisation continues to increase, widespread habitat clearing within peri-urban landscapes contributes to significant environmental impacts, including loss of biological diversity. Acoustic recording has recently been identified as an effective tool for monitoring biodiversity and ecosystem health. With increasing pressure from urbanisation, it is critical that spatial and temporal variability in biodiversity is mapped across future development sites to enable sound decision-making and to deliver ecological urban design outcomes. This study used ecoacoustic monitoring to map biodiversity patterns in space and time to identify hot spots and hot moments of biodiversity activity across a peri-urban landscape in south-east Queensland, Australia. In this study, a hot spot represents an increase in acoustic activity at a given spatial location, whereas hot moments represent an increase in acoustic activity at a given time point. An acoustic index (Acoustic Complexity Index, ACI) was used as a proxy for biodiversity and visualised through spatial interpolation. The acoustic data were statistically modelled using Boosted Regression Trees (BRT). This approach enabled predictors related to acoustic complexity to be identified, including vegetation and landform. Results of this study have shown that ecoacoustic data can be used to map hot spots and hot moments of biodiversity and support more informed conservation decision-making in future urban planning frameworks, to avoid or mitigate negative impacts on biodiversity.
... It targets single sound sources (i.e., single species or noise) or all the sound sources in a given environment (i.e., the soundscape). The marine soundscape is shaped by three components: biophony (signals and vocalizations produced by marine mammals, fishes, invertebrates), geophony (i.e., sounds from waves and rain, undersea earthquakes) and anthropophony (human-produced noise from shipping, industrial activities, oil and gas explorations) (Pieretti, 2017;Putland et al., 2017;Gage and Axel, 2014;Mullet, 2016;Farina, 2013;Pijanowski, 2011;Krause, 1987). PAM technologies allow the collection of large acoustic datasets (including species' presence/absence and their behavioral alterations due to external factors (Burivalova et al., 2019), consequently enabling the investigation of ecological patterns at different spatial and temporal scales (Erbe, 2015;Haver, 2018;Merchant, 2016). ...
The analysis of temporal trends and spatial patterns of marine sounds can provide crucial insights to assess the abundance, distribution, and behavior of fishes and of many other species. However, data on species-specific temporal and seasonal changes are still extremely limited. We report here the result of the longest recording ever conducted (five years, from 2014 to 2018) on fish vocalization. Findings from the Eastern Taiwan Strait (ETS) revealed a periodic fish chorusing pattern, with peaks in summer and almost complete silence, for ~2 months, during winter. Chorusing pattern was influenced by abiotic parameters, including temperature, tides and moon phase. We also report, for the first time, that extreme weather events (e.g., typhoons, storms with sediment resuspension) caused the cessation of the chorusing. The chorusing pattern explored in this long-term study provides important baseline data to understand the impact of climate change and of climate-driven extreme/episodic events on the phenology of fishes; this work also provides evidence that changes in the ambient conditions might significantly alter the phenology of vocalizing marine species.
Resumo
As paisagens sonoras são a resultante do conjunto de sons emitidos por fontes antrópicas e naturais. A análise do som como forma de poluição, exige métodos mais elaborados que a análise de ruídos. O objetivo do presente estudo é apresentar as potencialidades da avaliação da paisagem sonora com equipamentos de baixo custo, visando agregar informações relativas a biofonia e antropofonia de áreas urbanas. Foram avaliadas amostras obtidas em área urbana residencial, no município de Rondonópolis, MT. As gravações foram executadas com um gravador portátil baseado em tecnologia open source (Audiomoth©), com taxa de amostragem a 96KHz, em intervalos de 10s com pausas de 50s, de forma contínua por 48h. Os arquivos gerados foram analisados com o pacote soundecology no ambiente R (R software v. 4.2.2), para o cálculo dos índices de diversidade acústica (ADI), diferença normalizada da paisagem acústica (NDSI), índice bioacústico (BI), índice de diversidade acústica (ADI) e índice de uniformidade acústica (AEI). Os resultados possibilitaram avaliar o perfil da paisagem sonora urbana, subsidiando a discussão relativa aos impactos da poluição sonora na fauna urbana. Palavras-chave: Poluição, fauna, som.
Abstract
Soundscapes are the result of the set of sounds emitted by anthropic and natural sources. Sound analysis as a form of pollution requires more elaborate methods than noise analysis. The objective of the present study is to present the potentialities of the evaluation of the soundscape with low-cost equipment, aiming at adding information related to the biophony and anthropophony of urban areas. Samples obtained from urban residential, in Rondonopolis City, MT, were evaluated. The recordings were performed with a portable recorder based on open-source technology (Audiomoth©), with a sampling rate of 96KHz, in intervals of 10s with pauses of 50s, continuously for 48h. The generated files were analyzed with the soundecology package in the R environment (R software v. 4.2.2), for the calculation of the acoustic diversity indices (ADI), normalized difference of the acoustic landscape (NDSI), bioacoustic index (BI), index Acoustic Diversity Index (ADI) and Acoustic Uniformity Index (AEI). The results show as possible to evaluate the profile of the urban soundscape, supporting the discussion on the impacts of noise pollution on urban fauna.
A sonotope is characterized as a sonic patch that forms a hierarchical link between a finer, local scaled acoustic community and the coarser landscape scaled sonoscape. Unfortunately, the concept of sonotopes has yet to be empirically supported. We tested the hypothesis that a spatially explicit sample of sonic information from a heterogeneous landscape would exhibit spatially unique sonotopes with distinct spatio-temporal patterns and acoustic communities. We used the Acoustic Complexity Index (ACI tf ) to analyze sonic information (WAV) gathered from an array of 10 sound recorders deployed within a lattice of 10, 4-ha hexagonal sample sites distributed evenly throughout a 48-ha undivided heterogeneous landscape in Northern Italy. We examined the temporal patterns of sonic activity (ACI tf ) between seasons (March – July and August – November 2021) and across five astronomical periods of a 24-h day (Night I, Morning Twilight, Day, Evening Twilight, and Night II). We used cluster analyses to identify sonotopes from groupings of similar ACI tf values for each sample site and visualized the spatial arrangements of sonotopes throughout our study area between seasons and among astronomical periods. Sonic activity from bird biophonies increased in March – July during the Day but in August – November greater sonic activity shifted to crepuscular and nocturnal periods with the biophonies from crickets. Sonotopes exhibited spatially unique, dynamic arrangements of patch size and placement depending on the season and astronomical period. We discuss how acoustic communities and continuous geophonies play a role in the arrangement of sonotopes and their relation to the sonoscape.
O objetivo foi avaliar a influência da cobertura da vegetação sobre a paisagem sonora de um fragmento da floresta urbana em Curitiba, Paraná. Em 14 locais de coleta na parte interna e externa do fragmento, foram coletados os níveis do som ambiente com compensação em A (simulando a recepção humana) (dB (A)) e equivalente (dBeq) para a classificação do som no local, durante o outono de 2018. Foram utilizados um decibelímetro DEC-470 para avaliar a pressão sonora e fotografias tomadas em lente olho-de-peixe para avaliar o Fator de Visão do Céu (FVC) e o Limitação do Céu (LIM). Constatou-se maiores níveis de pressão sonora e dBeq nos locais P1 e P11, com 75,5 (56,2 dBeq), e 76,5 dB (A) (56,1 dBeq), respectivamente. Os menores valores de dBeq foram registrados nos locais P3, P4, P7 e P8 com 46,4, 46,9, 47,1 e 47,6 dBeq. O maior FVC foi 0,828 no P1 e o menor 0,070 no P4, no exterior e interior do fragmento, respectivamente. O FVC e os valores médios da pressão sonora apresentaram um coeficiente de correlação de 0,57. Há uma relação diretamente proporcional entre o FVC e o ruído.
O objetivo foi avaliar a influência da cobertura da vegetação sobre a paisagem sonora de um fragmento da floresta urbana em Curitiba, Paraná. Em 14 locais de coleta na parte interna e externa do fragmento, foram coletados os níveis do som ambiente com compensação em A (simulando a recepção humana) (dB (A)) e equivalente (dBeq) para a classificação do som no local, durante o outono de 2018. Foram utilizados um decibelímetro DEC-470 para avaliar a pressão sonora e fotografias tomadas em lente olho-de-peixe para avaliar o Fator de Visão do Céu (F
VC) e o Limitação do Céu (LIM). Constatou-se maiores níveis de pressão sonora e
dBeq nos locais P1 e P11, com 75,5 (56,2 dBeq), e 76,5 dB (A) (56,1 dBeq), respectivamente. Os menores valores de dB eq foram registrados nos locais P3, P4, P7 e P8 com 46,4, 46,9, 47,1 e 47,6 dBeq. O maior FVC foi 0,828 no P1 e o menor 0,070 no P4, no exterior e interior do fragmento, respectivamente. O FVC e os valores médios da pressão sonora apresentaram um coeficiente de correlação de 0,57. Há uma relação diretamente proporcional entre o FVC e o ruído.
Soundscape ecology has enabled researchers to investigate natural interactions among biotic and abiotic sounds as well as their influence on local animals. To expand the scope of soundscape ecology to encompass substrate-borne vibrations (i.e. vibroscapes), we developed methods for recording and analyzing sounds produced by ground-dwelling arthropods to characterize the vibroscape of a deciduous forest floor using inexpensive contact microphone arrays followed by automated sound filtering and detection in large audio datasets. Through the collected data, we tested the hypothesis that closely related species of Schizocosa wolf spider partition their acoustic niche. In contrast to previous studies on acoustic niche partitioning, two closely related species - S. stridulans and S. uetzi - showed high acoustic niche overlap across space, time, and/or signal structure. Finally, we examined whether substrate-borne noise, including anthropogenic noise (e.g., airplanes) and heterospecific signals, promotes behavioral plasticity in signaling behavior to reduce the risk of signal interference. We found that all three focal Schizocosa species increased the dominant frequency of their vibratory courtship signals in noisier signaling environments. Also, S. stridulans males displayed increased vibratory signal complexity with an increased abundance of S. uetzi , their sister species with which they are highly overlapped in the acoustic niche.
Passive acoustic monitoring has developed rapidly as a tool for ecological assessments, and the use of acoustic indices to assess biodiversity in urban forests promises to be a low-cost and efficient analytical approach. However, the accuracy of using acoustic indices to characterize biodiversity may be compromised by excessive human interference. The acoustic complexity index (ACI) and normalized difference soundscape index (NDSI) were chosen to determine their application value, and explore the spatiotemporal patterns of change in the soundscape of a newly established suburban forest park in China. To understand the influence of drivers such as different sound source types, road distance, and vegetation structure on the soundscape, the Eastern Suburb Forest Park was selected as the study area, and 55 recording points (200 m intervals, 5 × 11 grids) were set up using a systematic grid. Passive acoustic monitoring was performed for four consecutive days in each season, and the spatiotemporal variation of the soundscape was visualized based on indices interpolation. The results showed that when using ACI and NDSI to rapidly assess biodiversity in urban forest environments, attention needs to be paid to the implications of seasonal fluctuations on indices. The temporal variation of the soundscape was closely related to the natural rhythms and vocal activity intensity of organisms. Distance to a nearby main road, distance to water, and structural complexity of vegetation were key factors influencing spatial variation. The findings support the use of acoustic methods to assess the characteristics of soundscapes in human-built urban forests. Soundscape mapping visualizes hotspots and moments of ecoacoustic activity, and has great potential for development in the conservation and management of suburban forest soundscapes.
Soundscapes have been likened to acoustic landscapes, encompassing all the acoustic features of an area. The sounds that make up a soundscape can be grouped according to their source into biophony (sounds from animals), geophony (sounds from atmospheric and geophysical events), and anthropophony (sounds from human activities). Natural soundscapes have changed over time because of human activities that generate sound, alter land-use patterns, remove animals from natural settings, and result in climate change. These human activities have direct and indirect effects on animal distribution patterns and (acoustic) behavior. Consequently, current soundscapes may be very different from those a few hundred years ago. This is of concern as natural soundscapes have ecological value. Losing natural soundscapes may, therefore, result in a loss of biodiversity and ecosystem functioning. The study of soundscapes can identify ecosystems undergoing change and potentially document causes (such as noise from human activities). Methods for studying soundscapes range from listening and creating visual (spectrographic) displays to the computation of acoustic indices and advanced statistical modeling. Passive acoustic recording has become an ecological tool for research, monitoring, and ultimately conservation management. This chapter introduces terrestrial and aquatic soundscapes, soundscape analysis tools, and soundscape management.
As biodiversity decreases worldwide, the development of effective techniques to track changes in ecological communities becomes an urgent challenge. Together with other emerging methods in ecology, acoustic indices are increasingly being used as novel tools for rapid biodiversity assessment. These indices are based on mathematical formulae that summarise the acoustic features of audio samples, with the aim of extracting meaningful ecological information from soundscapes. However, the application of this automated method has revealed conflicting results across the literature, with conceptual and empirical controversies regarding its primary assumption: a correlation between acoustic and biological diversity. After more than a decade of research, we still lack a statistically informed synthesis of the power of acoustic indices that elucidates whether they effectively function as proxies for biological diversity. Here, we reviewed studies testing the relationship between diversity metrics (species abundance, species richness, species diversity, abundance of sounds, and diversity of sounds) and the 11 most commonly used acoustic indices. From 34 studies, we extracted 364 effect sizes that quantified the magnitude of the direct link between acoustic and biological estimates and conducted a meta‐analysis. Overall, acoustic indices had a moderate positive relationship with the diversity metrics (r = 0.33, CI [0.23, 0.43]), and showed an inconsistent performance, with highly variable effect sizes both within and among studies. Over time, studies have been increasingly disregarding the validation of the acoustic estimates and those examining this link have been progressively reporting smaller effect sizes. Some of the studied indices [acoustic entropy index (H), normalised difference soundscape index (NDSI), and acoustic complexity index (ACI)] performed better in retrieving biological information, with abundance of sounds (number of sounds from identified or unidentified species) being the best estimated diversity facet of local communities. We found no effect of the type of monitored environment (terrestrial versus aquatic) and the procedure for extracting biological information (acoustic versus non‐acoustic) on the performance of acoustic indices, suggesting certain potential to generalise their application across research contexts. We also identified common statistical issues and knowledge gaps that remain to be addressed in future research, such as a high rate of pseudoreplication and multiple unexplored combinations of metrics, taxa, and regions. Our findings confirm the limitations of acoustic indices to efficiently quantify alpha biodiversity and highlight that caution is necessary when using them as surrogates of diversity metrics, especially if employed as single predictors. Although these tools are able partially to capture changes in diversity metrics, endorsing to some extent the rationale behind acoustic indices and suggesting them as promising bases for future developments, they are far from being direct proxies for biodiversity. To guide more efficient use and future research, we review their principal theoretical and practical shortcomings, as well as prospects and challenges of acoustic indices in biodiversity assessment. Altogether, we provide the first comprehensive and statistically based overview on the relation between acoustic indices and biodiversity and pave the way for a more standardised and informed application for biodiversity monitoring.
Context
One mainstay of soundscape ecology is to understand acoustic pattern changes, in particular the relative balance between biophony (biotic sounds), geophony (abiotic sounds), and anthropophony (human-related sounds). However, little research has been pursued to automatically track these three components.
Objectives
Here, we introduce a 15-year program that aims at estimating soundscape dynamics in relation to possible land use and climate change. We address the relative prevalence patterns of these components during the first year of recording.
Methods
Using four recorders, we monitored the soundscape of a large coniferous Alpine forest at the France-Switzerland border. We trained an artificial neural network (ANN) with mel frequency cepstral coefficients to systematically detect the occurrence of silence and sounds coming from birds, mammals, insects (biophony), rain (geophony), wind (geophony), and aircraft (anthropophony).
Results
The ANN satisfyingly classified each sound type. The soundscape was dominated by anthropophony (75% of all files), followed by geophony (57%), biophony (43%), and silence (14%). The classification revealed expected phenologies for biophony and geophony and a co-occurrence of biophony and anthropophony. Silence was rare and mostly limited to night time.
Conclusions
It was possible to track the main soundscape components in order to empirically estimate their relative prevalence across seasons. This analysis reveals that anthropogenic noise is a major component of the soundscape of protected habitats, which can dramatically impact local animal behavior and ecology.
This study aims to recognise frog choruses using false-colour spectrograms and machine learning algorithms with acoustic indices. This can be a useful solution for improving the efficiency of long-term acoustic monitoring. Acid frogs, our target species, are a group of endemic frogs that are particularly sensitive to habitat change and competition from other species. The Wallum Sedgefrog (Litoria olongburensis) is the most threatened acid frog species facing habitat loss and degradation across much of their distribution, in addition to further pressures associated with anecdotally-recognised competition from their sibling species, the Eastern Sedgefrogs (Litoria fallax). Monitoring the calling behaviours of these two species is essential for informing L. olongburensis management and protection, and for obtaining ecological information about the process and implications of their competition. Considering the cryptic nature of L. olongburensis and the sensitivity of their habitat to human disturbance, passive acoustic monitoring is a suitable method for monitoring this species. However, manually processing this overwhelmingly large quantities of acoustic data collected is time-consuming and not feasible in the long-term. Therefore, there is a high demand for automated acoustic recognition methods to efficiently search long-duration recordings and identify target species. In this study, we propose a two-step scheme for quickly identifying frog choruses, which is first narrowing down the search scope by inspecting long-duration false-colour spectrograms and then recognising target acoustic signals using machine learning and acoustic indices. This method is efficient, time-saving and general, which means it can easily adopted to other species. Our research also provides insights on how to choose acoustic features that efficiently recognise species from larger scale field-collected recordings. The experimental results show that these techniques are useful in identifying choruses of the two competitive frog species with an accuracy of 76.7% on identifying four acoustic patterns (whether the two species occurred).
Continuous audio recordings are playing an ever more important role in conservation and biodiversity monitoring, however, listening to these recordings is often infeasible, as they can be thousands of hours long. Automating analysis using machine learning algorithms requires a feature representation. In this paper we propose a technique for learning a general feature representation from unlabelled audio using auto-encoders, which can be used for analysing environmental audio on a small timescale.
We start by segmenting the audio data into non-overlapping 1-s long chunks and generating audio spectrograms. These audio spectrograms are then used to train a basic auto-encoder, with the output of the encoder network being used to generate the feature representation. We have found that at a 1-s timescale, our feature representation offers marginal improvements over “acoustic indices”, a common representation for analysing environmental audio.
Madagascar is home to more than 10 000 plant species, 80% of which occur nowhere else in the world. With natural vegetation ranging from rainforest to unique spiny forest, Madagascar’s range of plant diversity makes it one of the world's most important biodiversity hotspots. In common with many other tropical countries, the flora of Madagascar is extremely threatened not only by habitat destruction for agriculture, fuelwood, building materials and so on, but also, in the case of certain species, by over-collection for the horticultural trade.
The CEPF Madagascar Vegetation Mapping Project is a three-year project (2003–2006), funded by the Critical Ecosystem Partnership Fund (CEPF) and managed jointly by The Royal Botanic Gardens, Kew, Missouri Botanical Garden, and Conservation International’s Center for Applied Biodiversity Science. The project is innovative in a number of ways. It employs state-of-the art remote sensing technology and methodologies to delimit Madagascar’s vegetation. It represents an all-inclusive collaboration between specialists from a wide range of botanical and conservation institutions, which has ensured the
most thoroughly ground-truthed vegetation map ever compiled for
Madagascar. Finally, through a series of workshops, it incorporates detailed consultations with the conservation community to ensure that the final products are of maximum relevance and utility to conservation planners and managers.
An accurate and updated vegetation map is imperative for conservation planning and natural resource management in Madagascar. It is also essential that the data on which such a map is based be made freely available, so that conservation organisations, government departments, academic institutions and other stakeholders can use them as an up-to-date standard dataset on which to base their activities. The electronic version of this atlas is available on Kew’s website (www.vegmad.org), and local experts were invited to continually improve and update the map. In order for a vegetation map to fulfil its intended role it must
accurately delimit areas with various vegetation types as they currently exist, and assign those areas to objective categories
that can be easily recognised in the field and that reliably reflect fundamental biological differences (primarily structural features, for example, physiognomy).
Madagascar is becoming increasingly aware of the need to protect its
biodiversity. The most immediate use of this vegetation map in conservation is likely to be by protected area managers who wish to understand the flora of their designated areas. It will also provide a valuable baseline for monitoring longer-term changes in vegetation inside and outside protected areas. However, Madagascar also provides an exceptionally high rate of species discovery and description, and this atlas will be used by field biologists attempting to identify potential sampling sites for biodiversity surveys, which will in turn yield data that is critical for biogeographic research and conservation planning.
At the 2003 World Parks Congress, Madagascar’s President Marc
Ravalomanana emphasised his country’s commitment to conservation by announcing its intent to triple the size of its existing protected area network. This admirable effort to prevent the extinction of many of Madagascar’s endemic species has become known as the ‘Durban Vision’. In order to ensure effective preservation of Madagascar’s biodiversity, the identification of sites for these new protected areas should follow a systematic process. A recent workshop on systematic conservation planning (November 2005, Antananarivo) highlighted the importance of using habitat types and indicators of habitat quality in addition to species distribution data when conducting conservation prioritisation analyses, concluding that this is the best way to produce robust conservation solutions. Because only a small proportion of Madagascar’s species have had their distributions documented, the vegetation types identified by this mapping project are good surrogates for habitat diversity and for the majority of the biota, which is so little known. In addition, conservation practitioners, including NGOs and donors, need information on trends in natural vegetation cover and quality in order to assess the outcomes of their conservation work. The Convention on Biological Diversity includes trends in the extent of habitats among its headline indicators for tracking progress towards the 2010 target (SBSTTA, 2004). The immediate focus of the Durban Vision group will be on establishing new protected areas (map 1) in remaining native vegetation, although subsequent attention could productively turn to managing that vegetation, and the habitat quality categories in the atlas provide valuable information. The atlas also provides important up-to-date information on native vegetation cover and quality, which maximises its potential to aid planning for future habitat restoration activities.
Assessment of ecosystem biodiversity by measurement of acoustic diversity was explored [B. L. Krause, Explorers J., Winter, 156–160 (1993)]. Specific acoustic indices (e.g., based on frequency spectrum) were developed and correlated with standard diversity indices (e.g., standard species abundance indices). Necessary technological infrastructures and analytic processes to measure acoustic dynamics of ecological biodiversity were explored. An automated web‐based infrastructure capable of capturing, processing, and relaying real‐time field measurements from multiple ecosystems to desktop and home computers was developed, tested, and implemented. Key infrastructure components were remote field instrumentation, remote computer processing, wireless digital relay instrumentation, Internet server, and automation, relational database, and website software. A dynamic digital library of ecological acoustic samples, correlated ecosystem attributes, and acoustic analysis methodologies was established. Library resources, including digital sound files captured from ecosystems, were made available to researchers and the public over the Internet [N. Metzger and M. Blumenthal, Realizing Info. Future, NAP, 113–119 (1994)]. Indices of acoustic ecosystem diversity were refined through application on existing digital ecosystem sound recordings and digital sounds captured from multiple ecosystems. The performance of these indices was compared to standard biodiversity indices applied to the same ecosystems.
The first iteration of the niche hypothesis and the foundational concepts for the field of Soundscape Ecology.
Anthropogenic sound is a potential stressor for marine mammals that may affect health, as has been demonstrated in other mammals. Therefore, we have initiated investigations on the effects of intense underwater sounds on nervous system activation and immune function in marine mammals. Blood samples were obtained before and after sound exposures (single underwater impulsive sounds (up to 200 kPa) produced from a seismic water gun and (or) single pure tones (up to 201 dB re 1 µPa) resembling sonar "pings" from a white whale, Delphinapterus leucas, and a bottlenose dolphin, Tursiops truncatus, to measure neural-immune parameters. Norepinephrine, epinephrine, and dopamine levels increased with increasing sound levels and were significantly higher after high-level sound exposures (>100 kPa) compared with low-level sound exposures (100 kPa) qu'après une exposition à un son de basse intensité (
Data are presented on ring-tailed lemur feeding ecology and resource use at the Beza Mahafaly Special Reserve in southwestern Madagascar. The phenological availability of food resources was sampled monthly from 199 trees and 31 species. Results indicate that Lemur catta feeding ecology is finely tuned to the seasonal nature of specific food resources. Key species provide important food items during critical periods of the reproductive cycle. During a drought year, mortality for mothers and infants increased dramatically, providing indirect evidence that this species is highly dependent on the phenological reliability of food resources. These results indicate that in such highly seasonal habitats, the loss of any key species could have enormous impact on ring-tailed lemur demography and survival.
Monitoring the natural environment is increasingly important as habit degradation and climate change reduce the world's biodiversity. We have developed software tools and applications to assist ecologists with the collection and analysis of acoustic data at large spatial and temporal scales. One of our key objectives is automated animal call recognition, and our approach has three novel attributes. First, we work with raw environmental audio, contaminated by noise and artefacts and containing calls that vary greatly in volume depending on the animal's proximity to the microphone. Second, initial experimentation suggested that no single recognizer could deal with the enormous variety of calls. Therefore, we developed a toolbox of generic recognizers to extract invariant features for each call type. Third, many species are cryptic and offer little data with which to train a recognizer. Many popular machine learning methods require large volumes of training and validation data and considerable time and expertise to prepare. Consequently we adopt bootstrap techniques that can be initiated with little data and refined subsequently. In this paper, we describe our recognition tools and present results for real ecological problems.
Current methods of evaluating wildlife habitat for management,purposes can be arranged in a hierarchy of increasing generality. The most general level is evaluation of wildlife habitat for entire com- munities on the basis of inferences drawn from vegetational structure. At the base of the hierarchy the high resolution studies, upon which accuracy at the higher hierarchical levels depends, usually assume that habitat quality for a species is positively correlated with the density of the species. If habitat quality for a wildlife species is a measure of the importance of habitat type in maintaining a particular species, habitat quality should be defined in terms of the survival and production characteristics, as well as the density, of the species occupying that habitat. Situations in which habitat quality thus defined is not expected to be positively
This paper on reports the production of a 1 km spatial resolution land cover classification using data for 1992-1993 from the Advanced Very High Resolution Radiometer (AVHRR). This map will be included as an at-launch product of the Moderate Resolution Imaging Spectroradiometer (MODIS) to serve as an input for several algorithms requiring knowledge of land cover type. The methodology was derived from a similar effort to create a product at 8 km spatial resolution, where high resolution data sets were interpreted in order to derive a coarse-resolution training data set. A set of 37 294 x 1 km pixels was used within a hierarchical tree structure to classify the AVHRR data into 12 classes. The approach taken involved a hierarchy of pair-wise class trees where a logic based on vegetation form was applied until all classes were depicted. Multitemporal AVHRR metrics were used to predict class memberships. Minimum annual red reflectance, peak annual Normalized Difference Vegetation Index (NDVI), and minimum channel three brightness temperature were among the most used metrics. Depictions of forests and woodlands, and areas of mechanized agriculture are in general agreement with other sources of information, while classes such as low biomass agriculture and high-latitude broadleaf forest are not. Comparisons of the final product with regional digital land cover maps derived from high-resolution remotely sensed data reveal general agreement, except for apparently poor depictions of temperate pastures within areas of agriculture. Distinguishing between forest and non-forest was achieved with agreements ranging from 81 to 92% for these regional subsets. The agreements for all classes varied from an average of 65% when viewing all pixels to an average of 82% when viewing only those 1 km pixels consisting of greater than 90% one class within the high-resolution data sets.
Ecological impacts from roads may be the rule rather than the exception in most of the conterminous United States. We measured the proportion of land area that was located within nine distances from the nearest road of any type, and mapped the results for 164 ecoregions and 2108 watersheds nationwide. Overall, 20% of the total land area was within 127 m of a road, and the proportion increased rapidly with distance, so that 83% was within 1061 m of a road, and only 3% was more than 5176 m away. For forest land area only, the proportions differed by less than 2% for all distances. Regions with more than 60% of their total land area within 382 m of a road may be at greatest risk of cumulative ecological impacts from roads. These regions include nearly all coastal zones, as well as substantial portions of the southeast US and the basins of the Ohio, Brazos, Colorado, Sacramento, and San Joaquin Rivers.
This article presents a unifying theory of soundscape ecology, which brings the idea of the soundscape—the collection of sounds that emanate from landscapes—into a research and application focus. Our conceptual framework of soundscape ecology is based on the causes and consequences of biological (biophony), geophysical (geophony), and human-produced (anthrophony) sounds. We argue that soundscape ecology shares many parallels with landscape ecology, and it should therefore be considered a branch of this maturing field. We propose a research agenda for soundscape ecology that includes six areas: (1) measurement and analytical challenges, (2) spatial-temporal dynamics, (3) soundscape linkage to environmental covariates, (4) human impacts on the soundscape, (5) soundscape impacts on humans, and (6) soundscape impacts on ecosystems. We present case studies that illustrate different approaches to understanding soundscape dynamics. Because soundscapes are our auditory link to nature, we also argue for their protection, using the knowledge of how sounds are produced by the environment and humans.
Using SPOT-4 VEGETATION data for near-real time mapping is new. In this Letter, a robust technique for cloud decontamination of the ten-day composites is presented. A forest-cover map of Madagascar is derived from monthly images from October 1998 to September 1999 with a user's accuracy of 87.8%.
The distribution of landbirds during migration in forested landscapes of eastern North America is poorly known. We describe (1) the distribution of landbirds in northern white cedar (Thuja occidentalis) dominated forests as a function of distance from northern Lake Huron in Michigan during spring and autumn migration, and (2) discuss factors that may affect the distribution of these migrants. Both long- and short-distance migrants in spring and fall were concentrated within 0.4 km of the Lake Huron shoreline. This pattern was particularly pronounced during spring when aquatic-hatched insects such as midges and their predators (e.g., spiders) are most common and occur in largest numbers near the shoreline. Both long- and short-distance migrant abundance was associated with midge abundance, after controlling for date, during spring migration but not during fall migration. Migrants may concentrate near the shoreline because of the barrier effect of Lake Huron and relatively abundant food resources, especially during spring migration. Terrestrial habitats adjacent to bodies of water, where aquatic-dependent invertebrates are relatively abundant may provide important stopover sites for landbird migrants. Our results suggest coastal areas within the Great Lakes region provide critical stopover habitat for landbird migrants and should be a focus of conservation efforts, especially given the increasing development pressure that threatens these areas.
Tropical deforestation is a key contributor to species extinction and climate change, yet the extent of tropical forests and their rate of destruction and degradation through fragmentation remain poorly known. Madagascar's forests are among the most biologically rich and unique in the world but, in spite of longstanding concern about their destruction, past estimates of forest cover and deforestation have varied widely. Analysis of aerial photographs (c. 1953) and Landsat images (c. 1973, c. 1990 and c. 2000) indicates that forest cover decreased by almost 40% from the 1950s to c. 2000, with a reduction in 'core forest' > 1 km from a non-forest edge of almost 80%. This forest destruction and degradation threaten thousands of species with extinction. Country-wide coverage of high-resolution validated forest cover and deforestation data enables the precise monitoring of trends in habitat extent and fragmentation critical for assessment of species' conservation status.
Animal and plant populations often occupy a variety of local areas and may experience different local birth and death rates in different areas. When this occurs, reproductive surpluses from productive source habitats may maintain populations in sink habitats, where local reproductive success fails to keep pace with local mortality. For animals with active habitat selection, an equilibrium with both source and sink habitats occupied can be both ecologically and evolutionarily stable. If the surplus population of the source is large and the per capita deficit in the sink is small, only a small fraction of the total population will occur in areas where local reproduction is sufficient to compensate for local mortality. In this sense, the realized niche may be larger than the fundamental niche. Consequently, the particular species assemblage occupying any local study site may consist of a mixture of source and sink populations and may be as much or more influenced by the type and proximity of other habitats a...
Offers a comprehensive introduction to distance sampling, a statistical method used by many biologists and conservationists to estimate animal abundance. The text discusses point transect sampling and line transect sampling and also describes several other related techniques. There are updates on study design and field methods, laser range finders, theodolites and the GPS and advice is given on a wide range of survey methods. Analysis methods have also been generalized, through the use of various types of multiplier and exercises for students in wildlife and conservation management are included.
Millions of birds migrate across the Gulf of Mexico each year. However, most studies of migration in this region involve sampling onshore locations during the day, potentially underrepresenting the diversity and abundance of migrants passing the region. We evaluated a potential solution to this problem by recording the flight calls of passing migrants from an oil platform located southeast of the Alabama coast in the Gulf of Mexico. We detected 2762 calls during 30 nights from 9 September to 2 November 1999, and were able to identify 2329 calls to species. Flight calls by nine species of birds represented 23% of all identified calls. The greatest number of calls during one night (1017 calls) and during a 1-h period (257 calls) were recorded on 10 September. The greatest number of calls was recorded 8 h after sunset, with a secondary peak 2 h after sunset. The peak prior to sunrise may indicate the formation of flocks at dawn, and the peak after sunset may have been caused by the first wave of migrants reaching the platform. However, call counts varied extensively, with 98% of all calls recorded during 13 nights and 40% on a single night, possibly resulting from hourly and nightly differences in bird numbers aloft, atmospheric conditions, and artificial lighting conditions. Although recording on oil platforms can be difficult because of mechanical, wind, and wave noise, our results suggest great potential for describing the species composition of passing vocal migrants and the temporal patterns of flight-calling behavior if quiet recording locations can be found. Moreover, flight call monitoring could be a critically important tool for bird conservation in this region, given recent proposals to develop wind power and the potential bird mortality associated with such developments.
The Great Lakes and nearby agricultural midwestern United States together represent a geographical challenge to migratory land birds during flight and stopover. We explored large-scale migratory responses of land birds encountering the Great Lakes as revealed by weather surveillance radars (WSR-88D) and two smaller specialized radars. Those responses reveal comprehensive landscape- or regional-scale migratory patterns that would otherwise have been difficult to infer. Analysis of radar echoes showed birds crossed the Great Lakes in large numbers, although we also found evidence of birds avoiding lake crossing in some locations. Around dawn, birds over water in numerous locations frequently exhibited an increase in migratory height (dawn ascent) and often an accompanying reorientation toward nearest land if they were within ∼28 km of shore. Those behavioral responses to the Great Lakes influence the resulting distribution of birds stopping over in the intervening terrestrial landscapes.
Urbanization has not only altered land cover types, but also changed acoustic environments to which animals must adapt or emigrate for effective communication. Although many studies have addressed the effects of urban noise on acoustic communication of vocal organisms, little work has been done to understand the acoustic characteristics and the interaction between biological and anthropogenic sounds across urban–rural landscapes. The objectives of this study were to investigate the spatial and temporal patterns of soundscape characteristics along an urban–rural gradient, and how soundscape properties are related to avian species community. We established 17 locations across the city of Lansing, Michigan from February to December 2006 to record environmental sounds. A multilevel regression model (MLRM) was used to understand the variability of acoustic power of biological and anthropogenic sounds (biophony and anthrophony) with temporal and spatial data structures. Canonical Correspondence Analysis (CCA) was employed to investigate how bird species respond along an environmental gradient.
A cultural, anthropological, and scientific overview of the ways in which the non-human animal world taught humans to dance and sing.
For this paper, we sampled a fenced and an unprotected portion of a dry gallery forest (the Beza Mahafaly Reserve) in southwestern Madagascar for structure and floristic composition. Seedling plots were also sampled to assess invasion and regeneration. A total of 923 plants ≥2.5 cm diameter at breast height (DBH) were censused in 25 transects. Sixty-nine species and 43 genera were represented. In plant density, diversity, and size classes of individuals, the forest is similar to many continental tropical dry forests in Africa and the Neotropics. Over 80 percent of those species identified were native, as were 26 percent of the genera. Unlike many insular forests, Beza Mahafaly is not being invaded by fast-growing exotic species. There were no noticable differences in density, diversity, size classes, or proportion of native species between transects within and outside of the protected reserve. Two distinct microhabitats were noticed. Individual plants were more dense on "drier" soils; whereas, large trees ≥25 cm DBH were over twice as frequent on "wetter" soils. The floristic composition also differed, with only two species of tree, Tamarindus indica and Azima tetracantha, being common to both habitats. The distribution and density of lemur populations within the forest appear to be directly related to microhabitat differences.
Ecological impacts from roads may be the rule rather than the exception in most of the conterminous United States. We measured the proportion of land area that was located within nine distances from the nearest road of any type, and mapped the results for 164 ecoregions and 2108 watersheds nationwide. Overall, 20% of the total land area was within 127 m of a road, and the proportion increased rapidly with distance, so that 83% was within 1061 m of a road, and only 3% was more than 5176 m away. For forest land area only, the proportions differed by less than 2% for all distances. Regions with more than 60% of their total land area within 382 m of a road may be at greatest risk of cumulative ecological impacts from roads. These regions include nearly all coastal zones, as well as substantial portions of the southeast US and the basins of the Ohio, Brazos, Colorado, Sacramento, and San Joaquin Rivers.
Human intervention in natural ecosystems was mapped using a three-category system indicating different levels of anthropogenic disturbance: undisturbed, partially disturbed, and human dominated. Source data were transferred onto a set of 10 equal-area base maps covering the world. The maps were digitized for analysis. The surface area of each region and the proportion in each of the three disturbance categories was determined, as well as a derived index of remaining natural habitat. Nearly 90 million km2 of undisturbed land remains on the planet, roughly 52% of earth's terrestrial area. However, the habitable portion of the planet, with areas of rock, ice, and barren land removed, is nearly three-quarters disturbed in some way. The biological significance of the global pattern of disturbance was assessed by examining disturbance categories for the eight biogeographic realms of Udvardy. Methodological advancements of this study over earlier efforts included an improved mapping resolution, and expanded categorization system, and employment of an ecologically-based definition of habitat. -from Authors
Although acoustic variables play a key role in understanding the ecology and behavior of vocal organisms, little work has been done to investigate whether acoustic signals can serve as an ecological variable to assess the current state of ecosystems. Our research was guided by two overarching questions. The first question is can environmental acoustics be used as ecological attributes that reflect ecosystem structure and processes? The second question is can environmental acoustics provide a key means to measure and monitor the biodiversity and distribution of vocal species? The study first developed analytical methods to understand acoustic properties including: (1) development and refinement of an Acoustic Habitat Quality Index using the distribution of acoustic power across different frequency spectrum bands; and (2) measurement and analysis of vocalizing species diversity using multiple methods of recording acoustic signals. The second part of the study investigated a new approach to surveying avian species using acoustic recordings. This analysis revealed that automated acoustic recordings facilitated simultaneous breeding bird surveys at multiple locations with minimal variability and high accuracy of bird community measures. Third, the study characterized the urban-rural variability using environmental sounds based on quantification of environmental acoustic properties across a gradient of ecosystems and landscapes. Finally, the study illustrated that using wireless sensor networks as a new sampling tool in ecology and environmental science provides tremendous opportunities to measure and monitor complex ecological variables at relevant spatial and temporal scales. The integration of acoustic research with the multi-science communities and advances in wireless sensor networks will potentially enable and enhance our understanding of ecological change and our ability to forecast changes in complex, interconnected ecosystems at scales ranging from the ecosystem to global level.
Linnaeus' original scientific description of Lemur catta, the ringtailed lemur, was based on a living animal brought to England in 1749. Although there were many brief descriptions of wild ringtailed lemurs, it was not until Jolly wrote her now classic book, Lemur Behavior, that we had our first detailed description of the natural history of these beautiful animals (Fig. 1). Since then, long-term field studies, mainly from two study sites in Madagascar, Berenty and Beza Mahafaly (Fig. 2), as well as studies on forest-living groups in captivity at the Duke University Primate Center in Durham, North Carolina, have greatly expanded our knowledge of the ecology and behavior of this species (Table 1, Box 1). Thirty-five years of research on this species at these various sites indicates that Lemur catta is proving to be every bit as complex in its behavior as are many anthropoid primates. This very complexity has been reflected in the current controversies and questions concerning the ecology and behavior of this species.