Sound propagation in forests: A comparison of experimental results and values predicted by the Nord 2000 model

Tarrero, A.I.; Martín, María Luisa Novo; González, Julio; Machimbarrena, María; Jacobsen, Finn

doi:10.1016/j.apacoust.2007.01.007

Cited by 29 publications

(28 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the second problem of correcting for the area sampled and the distance over which birds are counted is more fundamental. Sound travels different distances depending on the vegetation and atmospheric conditions occurring between the signaller and the receiver (Holland 2001, Padgham 2004, Simons et al 2007, Pacifici et al 2008, Tarrero et al 2008. Detectability can also vary between observers depending on factors such as age, sex, and experience (Pearson et al 1995, Helzner et al 2005.…”

Section: Introductionmentioning

confidence: 99%

Experimentally derived detection distances from audio recordings and human observers enable integrated analysis of point count data

Yip¹,

Leston²,

Bayne³

et al. 2017

ACE

105

View full text Add to dashboard Cite

ABSTRACT. Point counts are one of the most commonly used methods for assessing bird abundance. Autonomous recording units (ARUs) are increasingly being used as a replacement for human-based point counts. Previous studies have compared the relative benefits of human versus ARU-based point count methods, primarily with the goal of understanding differences in species richness and the abundance of individuals over an unlimited distance. What has not been done is an evaluation of how to standardize these two types of data so that they can be compared in the same analysis, especially when there are differences in the area sampled. We compared detection distances between human observers in the field and four commercially available recording devices (Wildlife Acoustics SM2, SM3, RiverForks, and Zoom H1) by simulating vocalizations of various avian species at different distances and amplitudes. We also investigated the relationship between sound amplitude and detection to simplify ARU calibration. We used these data to calculate correction factors that can be used to standardize detection distances of ARUs relative to each other and human observers. In general, humans in the field could detect sounds at greater distances than an ARU although detectability varied depending on species song characteristics. We provide correction factors for four commonly used ARUs and propose methods for calibrating ARUs relative to each other and human observers. Dérivation expérimentale de distances de détection d'enregistrements audio et d'observateurs humains permettant l'analyse intégrée de points d'écouteRÉSUMÉ. Les points d'écoute sont une des méthodes les plus courantes pour évaluer l'abondance d'oiseaux. Les unités d'enregistrement autonomes (ARU, pour autonomus recording units) sont de plus en plus utilisées pour remplacer les points d'écoute réalisés par des observateurs. Les études antérieures ont comparé les avantages relatifs des dénombrements par point d'écoute faits par des observateurs comparativement à ceux réalisés au moyen d'ARU, principalement pour évaluer les différences de richesse spécifique et d'abondance sur une distance illimitée. Ce qui n'a pas été testé toutefois est comment standardiser ces deux types de données de façon à ce qu'elles soient comparables dans une même analyse, particulièrement lorsqu'il y a des différences d'aire échantillonnée. Nous avons comparé la distance de détection entre des observateurs sur le terrain et quatre enregistreurs commerciaux (Wildlife Acoustics SM2, SM3, RiverForks et Zoom H1), en simulant les vocalisations de diverses espèces aviaires à des distances et des amplitudes variées. Nous avons aussi exploré la relation entre l'amplitude du son et la détectabilité dans le but de simplifier la calibration d'ARU. Nous avons utilisé ces données afin de calculer des facteurs de correction servant à standardiser les distances de détection des ARU entre eux et avec les observateurs. En général, les observateurs sur le terrain pouvaient détecter des sons à des distances plus grandes que ...

show abstract

Section: Introductionmentioning

confidence: 99%

Experimentally derived detection distances from audio recordings and human observers enable integrated analysis of point count data

Yip¹,

Leston²,

Bayne³

et al. 2017

ACE

105

View full text Add to dashboard Cite

show abstract

“…Thus it was concluded that tree belts and shrubs should be planted together to provide best attenuation performance. 9 Tarrero et al 10 carried out an experimental investigation of the sound attenuation in different types of forests with different tree densities, different trunk diameters, and both deciduous and evergreen leaves. The measured data at several source-receiver distances showed that the trees have a noticeable effect on sound attenuation at longer distances of more than 40 m. However, if the trees are planted densely, then the attenuation effect due to trees can be seen at shorter ranges.…”

Section: Introductionmentioning

confidence: 99%

Sound propagation over soft ground without and with crops and potential for surface transport noise attenuation

Bashir

Taherzadeh

Attenborough

2015

The Journal of the Acoustical Society of America

View full text Add to dashboard Cite

Growing demand on transportation, road, and railway networks has resulted in increased levels of annoyance from road traffic. Optimized use of green surfaces in combination with vegetation may be desirable as a method for reducing the noise impact of road traffic in urban and rural environments. Sound propagation over soft ground and through crops has been studied through outdoor measurements at short and medium ranges and through predictions. At lower frequencies, ground effect is dominant, and there is little or no attenuation due to crops. At higher frequencies above 3-4 kHz, the attenuation in crops is dominant. It was also found that the ground effects and the influence of crops can be treated independently and can be added to obtain the total effect. Sound attenuation by crops is the result of multiple scattering between the stems and leaves, loss of coherence, and viscous and thermal losses due to foliage. The major contribution is associated with viscous and thermal losses. A model for sound attenuation by vegetation is proposed. Insertion losses for a typical road traffic noise source have been calculated that result either by replacing hard ground with different types of acoustically soft ground or by growing crops along the road sides.

show abstract

“…17 Different values of the effective flow resistivity U were used in Ref. 17 at different ranges, while in our predictions, the same ground parameters were used at x ¼ 40 m, 60 m, and 80 m. Second, the poplar forest was a regularly planted forest with possible sonic crystal effects. Third, the experimental data are in one-third octaves, while the theory developed is narrow band.…”

Section: à2mentioning

confidence: 99%

“…7-9, black crosses represent the SPL relative to that in free space in one-third octave bands measured in a poplar forest for three propagation ranges x ¼ 40 m, 60 m, and 80 m ( , the averaged tree radius was b ¼ 0.135 m, and the averaged tree height was h ¼ 9 m. Green crosses correspond to the SPL calculated with the Nord2000 model. 17 The predictions use the Delany-Bazley impedance model of the ground, 35 which is characterized by one parameter, the effective flow resistivity U. The ground impedance was not measured during the experiment, but rather U was used as an adjustable parameter for the best fit between theoretical and experimental data.…”

Section: Comparison With Experimental Datamentioning

confidence: 99%

See 1 more Smart Citation

Correspondence between sound propagation in discrete and continuous random media with application to forest acoustics

Ostashev

Wilson

Muhlestein

et al. 2018

The Journal of the Acoustical Society of America

View full text Add to dashboard Cite

Although sound propagation in a forest is important in several applications, there are currently no rigorous yet computationally tractable prediction methods. Due to the complexity of sound scattering in a forest, it is natural to formulate the problem stochastically. In this paper, it is demonstrated that the equations for the statistical moments of the sound field propagating in a forest have the same form as those for sound propagation in a turbulent atmosphere if the scattering properties of the two media are expressed in terms of the differential scattering and total cross sections. Using the existing theories for sound propagation in a turbulent atmosphere, this analogy enables the derivation of several results for predicting forest acoustics. In particular, the second-moment parabolic equation is formulated for the spatial correlation function of the sound field propagating above an impedance ground in a forest with micrometeorology. Effective numerical techniques for solving this equation have been developed in atmospheric acoustics. In another example, formulas are obtained that describe the effect of a forest on the interference between the direct and ground-reflected waves. The formulated correspondence between wave propagation in discrete and continuous random media can also be used in other fields of physics.

show abstract

Sound propagation in forests: A comparison of experimental results and values predicted by the Nord 2000 model

Cited by 29 publications

References 18 publications

Experimentally derived detection distances from audio recordings and human observers enable integrated analysis of point count data

Experimentally derived detection distances from audio recordings and human observers enable integrated analysis of point count data

Sound propagation over soft ground without and with crops and potential for surface transport noise attenuation

Correspondence between sound propagation in discrete and continuous random media with application to forest acoustics

Contact Info

Product

Resources

About