Table of Contents

Cover

Title Page

List of Contributors

Preface

Chapter 1: Ecoacoustics: A New Science

1.1 Ecoacoustics as a New Science
1.2 Characteristics of a Sound
1.3 Sound and its Importance
1.4 Ecoacoustics and Digital Sensors
1.5 Ecoacoustics Attributes
1.6 Ecoacoustics and Ecosystem Management
1.7 Quantification of a Sound
1.8 Archiving Ecoacoustics Recordings
1.9 Ecological Forecasting
References

Chapter 2: The Duality of Sounds: Ambient and Communication

2.1 Introduction
2.2 Vegetation and Ecoacoustics
2.3 Acoustic Resources, Umwelten, and Eco-fields
2.4 Sounds as Biological Codes
2.5 Sound as a Compass for Navigation
2.6 Geophonies from Sacred Sites – How to Incorporate Archeoacoustics into Ecoacoustics
References

Chapter 3: The Role of Sound in Terrestrial Ecosystems: Three Case Examples from Michigan, USA

3.1 Introduction
3.2 C1 Visualization of the Soundscape at Ted Black Woods, Okemos, Michigan during May 2016
3.4 C3 Disturbance in Terrestrial Systems: Tree Harvest Impacts on the Soundscape
References

Chapter 4: The Role of Sound in the Aquatic Environment

4.1 Overview on Underwater Sound Propagation
4.2 Sound Emissions and their Ecological Role in Marine Vertebrates and Invertebrates
4.3 Impacts of Anthropogenic Noise in Aquatic Environments
References

Chapter 5: The Acoustic Chorus and its Ecological Significance

5.1 Introduction
5.2 Time of Chorus
5.3 The Chorus Hypothesis
5.4 Choruses in Birds
5.5 Choruses in Amphibians
5.6 Choruses in the Marine Environment
5.7 Conclusions and Discussion
References

Chapter 6: The Ecological Effects of Noise on Species and Communities

6.1 Introduction
6.2 The Nature of Noise
6.3 Natural Sources of Noise
6.4 Anthropogenic Sources of Noise
6.5 Effects of Noise on the Animal World
6.6 How Animals Neutralize the Effect of Noise
6.7 Noise in Marine and Freshwater Systems
6.8 Conclusions
References

Chapter 7: Biodiversity Assessment in Temperate Biomes using Ecoacoustics

7.1 Introduction
7.2 Sound as Proxy for Biodiversity
7.3 Methods and Application of Ecoacoustics
7.4 Acoustic Communities as a Proxy for Biodiversity
7.5 Problems and Open Questions
7.6 Ecoacoustic Events: Concepts and Procedures
7.7 Conclusion
References

Chapter 8: Biodiversity Assessment in Tropical Biomes using Ecoacoustics: Linking Soundscape to Forest Structure in a Human-dominated Tropical Dry Forest in Southern Madagascar

8.1 Introduction
8.2 Methods
8.3 Results
8.4 Discussion
References

Chapter 9: Biodiversity Assessment and Environmental Monitoring in Freshwater and Marine Biomes using Ecoacoustics

9.1 Introduction
9.2 Freshwater Habitats
9.3 Marine Neritic Habitats
9.4 Marine Oceanic Habitats
9.5 Summary and Future Directions
References

Chapter 10: Integrating Biophony into Biodiversity Measurement and Assessment

10.1 Introduction
10.2 Biological Information in the Soundscape
10.3 Ecoacoustics in Biodiversity Assessment
10.4 Conclusion
References

Chapter 11: Landscape Patterns and Soundscape Processes

11.1 An Introduction to Landscape Ecology (Theories and Applications)
11.2 Relationship Between Landscape Ecology and Soundscape Ecology: A Semantic Approach
11.3 Acoustic Community and Landscape Mosaics
11.4 Ecoacoustics in a Changing Landscape
11.5 Conclusion
References

Chapter 12: Connecting Soundscapes to Landscapes: Modeling the Spatial Distribution of Sound

12.1 Introduction
12.2 Conceptualizing Soundscapes in Space and Time
12.3 Capturing Soundscapes in Space and Time
12.4 Sound Metrics and Interpreting Nature
12.5 A Soundscape Metric for Modeling
12.6 Discriminating the Components of a Soundscape
12.7 Generating a Predictive Soundscape Model
12.8 Conclusion
References

Chapter 13: Soil Acoustics

13.1 Introduction
13.2 Soil Insect Acoustics
13.3 Compost Activating Agent Acoustics
13.4 Soil Aggregate Slaking Acoustics
13.5 Conclusion
References

Chapter 14: Fundamentals of Soundscape Conservation

14.1 Introduction
14.2 Nature Sounds in Science and Education
14.3 The Role of Sound Libraries
14.4 Noise Pollution, the Acoustic Habitat, and the Biology of Disturbance
14.5 Soundscapes, Nature Conservation, and Public Awareness
14.6 Marine Soundscapes
14.7 Conclusion
References

Chapter 15: Urban Acoustics: Heartbeat of Lansing, Michigan, USA

15.1 Introduction
15.2 Objectives
15.3 Methods
15.4 Results
15.5 Discussion and conclusions
References

Chapter 16: Analytical Methods in Ecoacoustics

16.1 Introduction
16.2 Components of an Acoustic Recording
16.3 Visualization of an Acoustic Recording
16.4 Processing Multiple Recordings
16.5 Analyzing Acoustic Time Series
16.6 Time Series of Acoustic Indices
16.7 Searching and Symbolic Methods
16.8 Visualization and Navigation of Long-Duration Recordings
16.9 Spectrogram Pyramids
16.10 New Approaches to Analysis
16.11 Web Platforms for the Visualization of Environmental Audio
References

Chapter 17: Ecoacoustics and its Expression through the Voice of the Arts: An Essay

17.1 Introduction
17.2 Immersive Art as a Science Dissemination Tool
17.3 Examples of Ecoacoustic Works by Bernie Krause
17.4 Examples of Ecoacoustics Works by David Monacchi
17.5 Conclusion
References

Chapter 18: Ecoacoustics Challenges

18.1 Introduction
18.2 Philosophical Issues
18.3 Ecological Issues
18.4 Sensor Technology
18.5 Acoustic Computations and Modeling
18.6 Public Information
18.7 Monetary Issues
References

Index

End User License Agreement

List of Illustrations

Chapter 1: Ecoacoustics: A New Science

Figure 1.1 A spectrogram from a recording made at site LA00 (45.53320, –84.291960 in decimal degrees) on May 4 2009 at 0600h.
Figure 1.2 Ecoacoustics has several competencies in environmental surveys, ranging from population census to quality assessment of landscape for human well-being.

Chapter 2: The Duality of Sounds: Ambient and Communication

Figure 2.1 Need and resources are connected by a chain of semiotic processes in which need activates a function that in turn elicits a cognitive template necessary to locate an eco-field where resources are expected to be.
Figure 2.2 According to the eco-field model, a cognitive template is activated as reference for the location of an adapt (acoustic) eco-field. In this simplified model, a “territory resource” is found when the cognitive template is coincident with the acoustic (territory) eco-field. In this model, a free space (in gray) is the territory resource surrounded by singing territorial individuals (black dots).

Chapter 3: The Role of Sound in Terrestrial Ecosystems: Three Case Examples from Michigan, USA

Figure 3.1 C1. Location of four automated Song Meters in Ted Black Woods, Okemos, Michigan.
Figure 3.2 C1. Mean normalized soundscape power patterns for each of the 48 recordings made per day during May 2016.
Figure 3.3 C1. Contour plots of normalized soundscape power values for six frequency intervals (z), day of year (x) (based on the day count from 1 January) and time of day (y) during May 2016.
Figure 3.4 C1. The patterns of six soundscape indices for each of the 48 recordings made per day during May 2016.
Figure 3.5 C1. Contour plots of six soundscape index values (z), day of year (x) (based on the day count from 1 January) and time of day (y) during May 2016.
Figure 3.6 C1. The distribution of wind speed during May 2016.
Figure 3.7 C1. Distribution of rainfall amount during May 2016.
Figure 3.8 C1. Distribution of rain on day 135 (14 May 2016)
Figure 3.9 C1. Spectrograms from 0330h on day 135 (14 May) (top) and from 0330 on day 136 (15 May) (bottom).
Figure 3.10 C1. A spectrogram from a recording made at TB01 at 0600h on 14 May 2016 (day 135).
Figure 3.11 C2. Mean monthly temperature for March, April, and May for 2009, 2010, 2011, and 2012.
Figure 3.12 C2. First spring peeper call (day of year) versus mean March temperature (F) at site LA00 in 2009–2012.
Figure 3.13 C2. Day of first spring peeper call versus mean March temperature (F) (all sites).
Figure 3.14 C3. Forest stand before (a) and after harvest (b). Ring on pine denotes acoustic monitoring tree to be left for seed production.
Figure 3.15 C3. Normalized Difference Soundscape Index (NDSI) values for each site (a) and combined NDSI for all four sites (b) for the preharvest year (2013) and postharvest years (2014, 2015).
Figure 3.16 C3. NDSI values before (2013) and after harvest (2014–2015) based on recordings made at 30-minute intervals for 60 seconds at four sites.

Chapter 5: The Acoustic Chorus and its Ecological Significance

Figure 5.1 Representation of a chorus and a postchorus period at the time T1, T2, T3 and T4. The small black circles represent singing species (dawn chorus) and the empty circles silent species (post chorus).
Figure 5.2 Spectrogram of a bird chorus (Madonna dei Colli, 25042016 at 04.53, 44°12′30″N,10°03′34″E, 250 m a.s.l.). Turdus merula and Sylvia atricapilla are the major contributors.
Figure 5.3 A comparison between a chorus performed in good weather conditions (Madonna dei Colli, 22042016 at 0543h, 44°12′30″N,10°03′34″E, 250 m a.s.l.).) and a chorus during rain at dawn (Madonna dei Colli, 26042016 at 0543h).
Figure 5.4 The hypothesis presented to explain choruses. Source: Adapted from Staicer et al. (1996).

Chapter 6: The Ecological Effects of Noise on Species and Communities

Figure 6.1 Example of recording of an acoustic community of birds close to a traffic road (State road #63, Fivizzano, 0437-10062016, 44°13'33”N, 10°07'00”E, 264 m a.s.l.). The noise is present for few seconds in the left part of the spectrogram.
Figure 6.2 Different strategies can be adopted by animals to neutralize noise and its effects.

Chapter 7: Biodiversity Assessment in Temperate Biomes using Ecoacoustics

Figure 7.1 Representation of three acoustic events. Event a – dawn chorus (all the species are singing at the same time), time 0. Event b – a mosaic of acoustic communities, and time 1. Event c – a mosaic of acoustic communities, at time 2 at dawn chorus; all the individuals are singing at the same time. In the successive time period the number of individuals acoustically active is variable in space and time.
Figure 7.2 An acoustic event is often the combination of different acoustic contests. In this case, heavy rain and a blackcap song overlap (Agnino, time 06:55, date 03062016, 44°14'12”N, 10°04'16”E, 254 m a.s.l.).
Figure 7.3 EEDI procedure. The numerical analysis selects the potential events according to parameters such as environmental variables and ACI metrics thresholds. The coding process produces the event identification according to a selection of known events from an event's library.
Figure 7.4 Five possible temporal patterns of signals according to a spectrographic representation. I: (a) A low-intensity signal, uniform along time (low ACIf and max ACIfe). (b) A high-intensity signal, uniform along time (high ACIf and max ACIfe). (c) A low-intensity signal, heterogeneous along time (low ACIf and min ACIfe). (d) A high-intensity signal, heterogeneous along time (high ACIf and min ACIfe). (e) An irregular intensity signal, heterogeneous along time (medium ACIf and medium ACIfe). II: Distribution of the five conditions according to a matrix created by ordering ACIf and ACIfe according to four percentiles. Both ACIf and ACIfe are expressed in standard format (from 0 to 1). III: ACIte represents the distribution of intensity along frequencies. This parameter ranges as all the evenness from 0 (one frequency bin represented) to 1 (all frequency bins represented).
Figure 7.5 Annual distribution (September 2015 to July 2016) of acoustic events at Carpaneta (44°13'34”N, 10°07'16”E, 290 m a.s.l., Fivizzano, Italy) based on a model of 250 potential events created by the combination of 10 categories of ACIf, five categories of ACIfe, and five categories of ACIte.
Figure 7.6 Example of four one-minute events. (a) 1055 (Heavy rain), (b) 753 (Dawn chorus), (c) 525 (European robin song), (d) 323 (blackbird isolated alarm call) according to the classification from Table 7.1.

Chapter 8: Biodiversity Assessment in Tropical Biomes using Ecoacoustics: Linking Soundscape to Forest Structure in a Human-dominated Tropical Dry Forest in Southern Madagascar

Figure 8.1 Map of the Beza Mahafaly Special Reserve with study area in gray and reference to location in Madagascar.
Figure 8.2 Map of sampling sites established within the study area at the Beza Mahafaly Special Reserve.
Figure 8.3 Boxplots of Bioacoustic Index (BIO) by month across the year-long sampling period. Black line is median and boxes represent the upper and lower quartiles.
Figure 8.4 Bioacoustic Index (BIO) averaged by month across the year-long sampling period. Solid line is dry deciduous forest and dashed line is gallery forest. Error bars are standard errors.

Chapter 9: Biodiversity Assessment and Environmental Monitoring in Freshwater and Marine Biomes using Ecoacoustics

Figure 9.1 The range of passive acoustic technologies (PAM), including bottom-mounted archival recorders, animal-borne acoustic recording tags, acoustic arrays, autonomous underwater vehicles (a) to survey marine soundscapes consisting of biotic, abiotic, and anthropogenic contributions (b).
Figure 9.2 (a,c) Acoustic Complexity Index (ACI) and spectrogram (FFT: 3509 pt, overlap: 50%) (b,d) for two different reef environments, showing the relationship between diurnal and lunar cycles and acoustic energy in the lower frequency bands over a period of one month.
Figure 9.3 Example spectrogram and sound pressure levels (SPLs) during seismic airgun activity (640 in³ airgun array firing at a rate of 60 s before 14:00:00 on July 30th 2012 and at a rate of 10 s after 14:00:00 on the same day) in polar waters, measured at about 2 km distance from source. Vertical scale bar to the right of the spectrogram represents SPL in dB re 1 μPa²/Hz.

Chapter 10: Integrating Biophony into Biodiversity Measurement and Assessment

Figure 10.1 A tiered representation of three dimensions of biodiversity identified in the Rio Convention. (1) Number of different units, (2) distribution of the differences among the units, and (3) extent of differences between units. Of these, the number of different units is most readily and frequently measured, with species designation used as the differentiation criterion.
Figure 10.2 Hierarchical relationships between the three levels of biodiversity identified in the Rio Convention.
Figure 10.3 Categories of information in the soundscape relevant to the study of biodiversity.
Figure 10.4 A hypothetical model of the evolution of the biophony as an indicator of the transition of a community from dispersal-assembly to niche-assembly rules as the temporal scale increases to reflect evolutionary time. If such a relationship exists, instances where the biophony reflects a transition (i.e. a mixture of overlapping and partitioned signals) may be observable.

Chapter 11: Landscape Patterns and Soundscape Processes

Figure 11.1 Relationship between a landscape and the acoustic objects (sonotopes, soundtopes, sonotones and acoustic communities).
Figure 11.2 Example of a interaction of a blackcap (Sylvia atricapilla) near a busy road (State Road #63) (4°13'33N, 10°07'00E, 264 m a.s.l.), 0655-19062016. Visible in the spectrogram are the frequencies created by passing cars and the blackcap song.
Figure 11.3 Example of variability of the acoustic communities between four recorders (SET: Soundscape Explorer [Terrestrial]) located a few hundreds of meters from each other during two days of sampling (23, 24 June 2016) (1 minute every 5, totaling 240 files a day) along a montane ecotone (prairies and beech forest) (Northern Apennines National Park, 44°16'58”N, 10°13'39”E, 1600 m a.s.l.). Every point in the graphics represents an acoustic event where x = ACIf, Y = ACIfe and Z = ACIte, according to the EEDI methodology (Farina and Salutari 2016).
Figure 11.4 Graphical representation of the relationship between anthrophony, biophony, and landscape metrics in fragmented, human-dominated landscapes.

Chapter 12: Connecting Soundscapes to Landscapes: Modeling the Spatial Distribution of Sound

Figure 12.1 The Salford Predictive Modeler^® produces one-predictor partial dependence plots acquired from the results of running a model in TreeNet. This Figure shows the precise spatial response of (a) biophony, (b) geophony, and (c) technophony soundscape power to the top ranked environmental variable shown in Table 12.1 (Mullet et al. 2016). These Figure provide exceptional information on the exact spatial relationship between landscape variables and soundscape components (Reproduced with permission from Mullet et al. 2016).
Figure 12.2 Once predictions are generated in a model, it is possible to extrapolate the acoustic-environmental relationships of landscape variables and the soundscape from the known locations of recording sites to the rest of the study area. This Figure of the Kenai National Wildlife Refuge, Alaska, US. displays the predicted spatial distribution and patterns of soundscape power attributed to biophony, geophony, and technophony during winter that are in close association with landscape variables determined to be important by the model (see also Table 12.1 and Figure 12.1) (Reproduced with permission from Mullet et al. 2016).

Chapter 13: Soil Acoustics

Figure 13.1 Spectrograms of sounds of nonmicrowaved (live) and microwaved (sterilized) compost with and without water as an activating agent. The x-axis is 30 seconds time and the y-axis represents kHz levels 1–2. The color intensity and brightness indicate loudness. Sounds can be heard at www.nemasoil.com on the compost acoustics page.
Figure 13.2 Power spectral densities (PSD) of live and sterilized compost, without and with water. The error bars represent the 95% confidence interval.
Figure 13.3 Spectrograms of rapid water hydration of soil aggregates from three different soils: (a) Hoytville, Ohio (conventional till), (b) Wooster, Ohio (native forest), (c) KBS, Hickory Corners, Michigan (native soil); (d) background sound with no soil aggregates. The color intensity and brightness indicate sound intensity. Black indicates no sound. Lighter color is higher sound intensity.
Figure 13.4 Power spectral density computed from acoustic samples of rapidly hydrated (immersed in water) soil aggregates and six soil management systems: native succession at KBS (Hickory Corners, Michigan); conventionally tilled and no-till soil from Hoytville (Ohio); and native forest, no-till and conventionally tilled soil from Wooster (Ohio). Error bars indicate 95% confidence intervals. P < 0.0001 based on a one-way ANOVA.
Figure 13.5 Power spectral density computed for 10 frequency intervals (2–11 kHz) and six soil management systems (Hoytville, Ohio, tilled and no-till; KBS, Hickory Corners, Michigan, native soil; and Wooster, Ohio, native, no-till, and tilled soil).

Chapter 14: Fundamentals of Soundscape Conservation

Figure 14.1 Recording in low ambient noise conditions. The visible sound tracks are mainly due to the hum of insects in flight and small noises coming from trees and leaves.
Figure 14.2 Recording with the passage of an airplane and some bird songs between 2 and 10 kHz.
Figure 14.3 In the bands below 80 Hz, the minimum level is close to 0 dB(Z); bird songs are visible in the 2–10 kHz band.
Figure 14.4 Light breeze causes an increase in noise at both low and high frequency due to the rustling of the leaves. Above 10 kHz Orthoptera sounds are present.
Figure 14.5 Recording made in a suburban residential area on the boundaries of Pavia. The noise level is constantly around 60 dB(Z); 1/3 octave bands below 200 Hz reach 70 dB. Bird songs are visible in the 2–10 kHz band.
Figure 14.6 Map of ship traffic density around Italy (www.marinetraffic.com). Reproduced with permission of marinetraffic.com.
Figure 14.7 Spectrogram of fin whale vocalizations in a quiet period (top); the bottom spectrogram shows the noise of a passing ship that completely masks any whale vocalization (x-axis 160 s, y-axis 0–125 Hz).
Figure 14.8 Online map of noise according to a model fed in real time by ships tracked with an AIS - Automatic Identification System (www.oceannoisemap.com).

Chapter 15: Urban Acoustics: Heartbeat of Lansing, Michigan, USA

Figure 15.1 Map of recording sites in the Lansing, Michigan, area.
Figure 15.2 Recording instrumentation (Sangean C.CRANE VersaCorder Dual Speed Cassette Recorder) used to record the sounds of the heartbeat of the city in the Lansing, Michigan area.
Figure 15.3 The mean values (± SE) of the Normalized Difference Soundscape Index (NDSI) for sites in the Lansing, Michigan, area based on recordings made at 0200h, 0600h, 1000h, 1400h, 1800h, and 2200h during February to December, 2006.
Figure 15.4 Mean values (± SE) of the NDSI for habitats in the Lansing, Michigan, area based on recordings made at 0200h, 0600h, 1000h, 1400h, 1800h, and 2200h during February to December, 2006.
Figure 15.5 Mean values (± SE) of the NDSI for rural-urban combinations in the Lansing, Michigan, area based on recordings made at 0200h, 0600h, 1000h, 1400h, 1800h, and 2200h during February to December, 2006.
Figure 15.6 Mean values (± SE) of the NDSI for habitats in the Lansing, Michigan, area based on recordings made at 0200h, 0600h, 1000h, 1400h, 1800h, and 2200h during May, 2006.
Figure 15.7 Mean values (± SE) of the NDSI for habitats in the Lansing, Michigan, area based on recordings made at 0200h, 0600h, 1000h, 1400h, 1800h, and 2200h for rural-urban combinations in May, 2006.
Figure 15.9 Mean values (± SE) of five acoustic indices (ADI, AEI, H, ACI, BIO) within urban-rural combinations in the Lansing, Michigan, area based on recordings made at 0200h, 0600h, 1000h, 1400h, 1800h, and 2200h for rural-urban combinations from February to December, 2006.
Figure 15.8 Mean values (± SE) of the NDSI for rural-urban combinations in the Lansing, Michigan, area based on recordings made at 0200h, 0600h, 1000h, 1400h, 1800h, and 2200h in May, 2006.

Chapter 16: Analytical Methods in Ecoacoustics

Figure 16.1 Panel of acoustic analysis output for each sound recorded at TB01 processed using the MATLAB script (Gage et al. 2010). An oscillogram (a), a spectrogram (b), a plot of nPSD frequencies values (F1–F11) (c) and a bar chart of nPSD values for 10 frequency intervals F2–11 kHz at 1 kHz intervals.
Figure 16.2 A 3D spectrogram based on a sound recorded at site TB01 at 0530 on 15 June 2015 for 60 seconds.
Figure 16.3 Mean normalized soundscape power for frequencies 1–7 kHz during June 2015 from site TB01.
Figure 16.4 Example indices/statistics derived from soundscape power during June 2015 from site TB01.
Figure 16.5 Patterns of six acoustic indices over time of day recorded at 30 m intervals in June 2015 from site TB01.
Figure 16.6 Anomaly score, trigger signal, and ensembles extracted from an acoustic recording.
Figure 16.7 Polar dendrogram illustrating the clustering of vocalizing species when clustered using a SAX symbolic representation of 1 kHz frequency bins.
Figure 16.8 Two 24-hour false-color spectrograms of a terrestrial recording obtained 30 km west of Brisbane, Australia. The top image maps indices BGN, POW, and CVR to RGB respectively. The bottom image maps indices ACI, ENT, and EVN to RGB respectively. See Towsey et al. (2014a) for a description of these indices. The top spectrogram reveals less acoustic structure because the two indices POW and CVR are strongly correlated. The x-axis spans 24 hours. The y-axis spans 11 kHz.
Figure 16.9 Two 12-hour false-color spectrograms of a marine recording obtained off the east coast of the USA. The top image maps indices ACI, ENT, and EVN to RGB respectively. The bottom image maps indices BGN, POW, and CVR to RGB respectively. See Towsey et al. (2014a) for a description of these indices. Shipping activity is plainly visible in the bottom spectrogram in which the red color essentially indicates noise pollution. The left side of the top spectrogram reveals acoustic activity around 100 Hz which is due to the calling activity of both fish and marine mammals. The x-axis spans 12 hours. The y-axis spans 1 kHz.

Chapter 17: Ecoacoustics and its Expression through the Voice of the Arts: An Essay

Figure 17.1 California Academy of Sciences, African waterhole exhibit, 1983.
Figure 17.2 Cleveland MetroParks Zoo, rainforest installation (first nonrepetitive biophonic installation).
Figure 17.3 Fondation Cartier pour l’Art Contemporain retrospective of B. Krause’s soundscape field work, Paris, 2016. A synthesis of both science and the arts. Streaming surround spectrogram concept based on David Monacchi’s Ecoacoustic Theater.
Figure 17.4 First 11 bars of The Great Animal Orchestra Symphony score co-composed with Richard Blackford. Brickwall dynamic filtering concept based on David Monacchi’s Integrated Ecosystem composition.
Figure 17.5 24-hour continuous 3D recording (38 simultaneous hi-definition audio channels) of a circadian cycle in primary lowland equatorial forest habitat at Tiputini River, Yasunì, Ecuador (www.fragmentsofextinction.org).
Figure 17.6 David Monacchi, Fragments of Extinction. Eight-channel surround sound installation with streaming spectrogram projection created for Ear to the Earth, a festival of sound art, music and ecology, New York City, October 6–14, 2006, at 3LD Art Gallery.
Figure 17.7 Integrated Ecosystem, an audio-video spectral soundscape composition based on African primary equatorial forest recordings premiered at Ear to the Earth 2009. The photo is from a replica at the Visitazioni Festival, Rome, 2014. It displays the moment in which the sensor-driven digital performance begins (opening of part III). The projected real-time spectrogram analysis shows insects and bats at around 18–24 kHz, progressively isolated with brickwall filtering, then shifted in frequency (8-octave, logarithmic). The aim of this process of transformation was to bring the inaudible sound gestures of these animals down to an audible area, thus providing the audience with an effective tool to hear the inaudible world. Spectrogram legend, horizontal axis: time (depicting from right to left – about 3 min. window in the photo); vertical axis: frequency (20–22 kHz); color: acoustic energy from silence (black) to about 70 dBA (bright gray).
Figure 17.8 The Ecoacoustic Theater (patented 2013) by David Monacchi. Pictured is a 12-meter diameter option/41.4 loudspeaker system (3D rendering by Pippo Marino). The implementation of the 360° circular streaming spectrogram is here acheived through an array of six projectors connected to a single analysis engine. A 5-meter diameter prototype of the Theater was presented at the ECSITE annual conference in Trento in June 2015.
Figure 17.9 The research and production studio for the project Fragments of Extinction was built in 2013 as a model of the Ecoacoustic Theater and is fully functional at the Conservatory “G.Rossini” in Pesaro, Italy (www.rossinispace.org).

Chapter 18: Ecoacoustics Challenges

Figure 18.1 Ecoacoustics offers a rich collection of opportunities that range from ecological to public issues, creating communication between natural and human sciences.

List of Tables

Chapter 3: The Role of Sound in Terrestrial Ecosystems: Three Case Examples from Michigan, USA

Table 3.1 Initial search criteria and number of recordings of the spring peeper determined by filtering the frequency in which spring peeper calls occur
Table 3.2 Date and time of first call of the spring peeper (FSPC) at Twin Lakes, Cheboygan, MI
Table 3.3 C3 – Site, location, year, start day, end day, and number of recordings
Table 3.4 C3 – Site, location, year, start day, end day, and number of recordings
Table 3.5 C3 – Analysis of variance of NDSI versus year (all data)
Table 3.6 C3 – Tukey pairwise comparisons NDSI versus year (all data) where grouping information is based on 95% confidence. Means that do not share a letter are significantly different
Table 3.7 C3 – Analysis of variance of NDSI versus year (June only)
Table 3.8 C3 – Tukey pairwise comparisons of NDSI versus year (June only) where grouping information is based on 95% confidence. Means that do not share a letter are significantly different

Chapter 7: Biodiversity Assessment in Temperate Biomes using Ecoacoustics

Table 7.1 Annual distribution (September 2015 to July 2016) of acoustic events at Carpaneta (44°13'34”N, 10°07'16”E, 290 m a.s.l., Fivizzano, Italy), only categories >0 where considered and sorted according to the code. #, number of events; code, event code; Tot, total number of events. From this Table four examples are reported in Figure 7.6.

Chapter 8: Biodiversity Assessment in Tropical Biomes using Ecoacoustics: Linking Soundscape to Forest Structure in a Human-dominated Tropical Dry Forest in Southern Madagascar

Table 8.1 Best fit linear mixed models between BIO and forest class during each seasonal period.
Table 8.2 Best fit linear mixed models between BIO and forest structure variable(s) during each seasonal period.

Chapter 10: Integrating Biophony into Biodiversity Measurement and Assessment

Table 10.1 Mathematical tools used to estimate diversity parameters from species surveys. “Importance” refers to the relative dominance or prevalence of a species.
Table 10.2 Possible responses to interference from mechanical sounds and their associated trade-offs.

Chapter 12: Connecting Soundscapes to Landscapes: Modeling the Spatial Distribution of Sound

Table 12.1 Models produce a Table of response variables that have the strongest to weakest relationship to a target variable (e.g. biophony, geophony, technophony). This Table shows the rank of importance of the top 10 environmental variables associated with biophony, technophony, and geophony used to model the acoustic-environmental relationships in the Kenai National Wildlife Refuge, Alaska, over winter 2011–2012. Source: Mullet et al. (2016). Reproduced with permission of Springer.

Chapter 15: Urban Acoustics: Heartbeat of Lansing, Michigan, USA

Table 15.1 Classification of acoustic recording sites according to class, habitat, and class-habitat combination.
Table 15.2 Minimum and maximum mean values for five acoustic indices for each of the urban-rural combinations

Chapter 16: Analytical Methods in Ecoacoustics

Table 16.1 A MATLAB script outputs the variables in csv file format for each sound recording.
Table 16.2 The acoustic indices in this R script include computations for multiple acoustic indices. As there are several indices of the same name but computed slightly differently, the three letters following the indices indicate the source of the indices: Stuart Gage (shg), Soundecology (sou), Seewave (see).
Table 16.3 Species codes and names for species included in Figure 16.7.

Ecoacoustics

The Ecological Role of Sounds

Edited by

Almo Farina

Urbino University, Italy

Stuart H. Gage

Michigan State University, East Lansing, Michigan, USA

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

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Title: Ecoacoustics : the ecological role of sounds / edited by Almo Farina, Urbino University, IT, Stuart H Gage, Michigan State University, East Lansing, MI, US.

Description: First edition. | Hoboken, NJ : John Wiley & Sons, Inc., 2017. | Includes bibliographical references and index.

Identifiers: LCCN 2017003603 (print) | LCCN 2017005379 (ebook) | ISBN9781119230694 (cloth) | ISBN 9781119230700 (pdf) | ISBN 9781119230717 (epub)

Subjects: LCSH: Landscape ecology. | Nature sounds. | Bioacoustics. | Ecosystem health. | Biodiversity.

Classification: LCC QH541.15.L35 E247 2017 (print) | LCC QH541.15.L35 (ebook) | DDC 577-dc23

List of Contributors

Anne C. Axel
Department of Biological Sciences
Marshall University
Huntington
USA

Giuseppa Buscaino
BioAcousticsLab
National Research Council (IAMC-CNR) - Detached Unit of Capo Granitola (TP)
Italy

Maria Ceraulo
Department of Pure and Applied Sciences
University of Urbino
Urbino
Italy

Almo Farina
Department of Pure and Applied Sciences
University of Urbino
Urbino
Italy

Francesco Filiciotto
BioAcousticsLab
National Research Council (IAMC-CNR) - Detached Unit of Capo Granitola (TP)
Italy

Susan Fuller
Queensland University of Technology
Brisbane
Australia

Stuart H. Gage
Department of Entomology
Michigan State University
East Lansing
USA

Wooyeong Joo
Choongnam
Seocheon-gun
Maseo-Myeon
Geumgang-ro
South Korea

Eric P. Kasten
Michigan State University
East Lansing
USA

Bernie Krause
Wild Sanctuary
Glen Ellen
USA

David Monacchi
Conservatorio Gioachino Rossini
Pesaro
Italy

Timothy C. Mullet
Ecological Services
US Fish and Wildlife Service
Daphne
Alabama
USA

Brian Michael Napoletano
Centro de Investigaciones en Geografía Ambiental
Universidad Nacional Autónoma de México
Morelia
Michoacán
México

Susan E. Parks
107 College Place
Syracuse
USA

Gianni Pavan
CIBRA
University of Pavia
Italy

Nadia Pieretti
Department of Pure and Applied Sciences
University of Urbino
Urbino
Italy

Marisol A. Quintanilla-Tornel
Plant and Environmental Protection Sciences
University of Hawaii
Manoa
USA

Lyndsay Rankin
Northern Illinois University
DeKalb
USA

Denise Risch
Scottish Association for Marine Science (SAMS)
Oban
Scotland
UK

Michael Towsey
Queensland University of Technology
Brisbane
Australia

Preface

Discovering the importance of sound in natural processes is an important legacy of bioacoustics and human acoustics, two disciplines that have developed in the second half of the twentieth century. At that time, Aldo Leopold and Rachel Carson used acoustics to describe relevant phenomena like animal migration or the effect of chemical pollution on reproductive success of breeding birds but acoustics technology methods were rare. Their heritage is an important baseline for a new ecological perspective in the scientific investigation of sound, known as ecoacoustics, a discipline that incorporates and integrates the study of sound in both ecological and human systems.

Sound is an important phenomenon including behavioral functions that range from mate performance to territory defense and social cohesion and has recently been shown to be a key issue in ecological processes. The Earth emits geological, biological, and human sounds within the biosphere, creating a sonic context that characterizes ecosystems at different spatial and temporal scales and has consequences that can affect many ecological processes. Vocal animals have a direct relationship with habitat suitability and the vocal performance of other organisms, further confirming the energy investment required to produce acoustic signals and the trade-off between such performances, other life traits, and the availability of resources needed for their survivorship.

All young disciplines, including ecoacoustics, have difficulty in tracing historical origins so there is no precise date allocated to its foundation. The use of the term “ecoacoustics” was suggested at a meeting in June 2104 at the Museum of Natural History in Paris where “soundscape ecology” was also suggested as an alternative. The assembly decided that ecoacoustics was all-inclusive in studies of ecologically based sound and thus included soundscape ecology.

With this book, we offer examples of studies, theoretical concepts, and methodologies that have evolved over the past decades in an attempt to provide a synthesis of the new discipline of ecoacoustics, although we emphasize that these are only a subset of possible examples. This book is not a celebrative edition of a consolidated ecological discipline but a contribution to transmit the principles and ideas of ecoacoustics to a wider audience. We believe that the examples of these aspects of ecoacoustics will provide an incentive for others interested in ecological sounds, including those in the sciences and the arts, to pursue their research, applying sound to solve ecological problems and to educate the next generation about the importance of ecological sounds to the survivorship of the human race.

The 18 chapters in this book cover important topics to assist others to understand the ecological significance of sounds. This introduction to ecoacoustics is intended for all who are interested in or concerned about the ecosystems in which we live and utilize for the resources that they provide.

Almo Farina and Stuart H. Gage