@article {53580, title = {Contributions of MIR to soundscape ecology. Part 2: Spectral timbral analysis for discriminating soundscape components}, journal = {Ecological Informatics}, year = {2019}, month = {Jan-02-2019}, abstract = {

Soundscape ecology evaluates biodiversity and environmental disturbances by investigating the interaction among soundscape components (biological, geophysical, and human-produced sounds) using data collected with autonomous recording units. Current analyses consider the acoustic properties of frequency and amplitude resulting in varied metrics, but rarely focus on the discrimination of soundscape components. Computational musicologists analyze similar data but consider a third acoustic property, timbre.

Here, we investigated the effectiveness of spectral timbral analysis to distinguish among dominant soundscape components. This process included manually labeling and extracting spectral timbral features for each recording. Then, we tested classification accuracy with linear and quadratic discriminant analyses on combinations of spectral timbral features.

Different spectral timbral feature groups distinguished between biological, geophysical, and manmade sounds in a single field recording. Furthermore, as we tested different combinations of spectral timbral features that resulted in both high and very low accuracy results, we found that they could be ordered to \“sift\” out field recordings by individual dominant soundscape component.

By using timbre as a new acoustic property in soundscape analyses, we could classify dominant soundscape components effectively. We propose further investigation into a sifting scheme that may allow researchers to focus on more specific research questions such as understanding changes in biodiversity, discriminating by taxonomic class, or to inspect weather-related events.

}, issn = {15749541}, doi = {10.1016/j.ecoinf.2019.01.008}, url = {https://linkinghub.elsevier.com/retrieve/pii/S1574954118301900}, author = {VanSchaik, Jack and Zhao, Zhao and Gasc, Amandine and Omrani, Hichem and Bryan C. Pijanowski} } @article {52881, title = {Soundscapes reveal disturbance impacts: biophonic response to wildfire in the Sonoran Desert Sky Islands}, journal = {Landscape Ecology}, year = {2018}, month = {Oct-07-2018}, abstract = {

Context
While remote sensing imagery is effective for quantifying land cover changes across large areas, its utility for directly assessing the response of animals to disturbance is limited. Soundscapes approaches\— the recording and analysis of sounds in a landscape\— could address this shortcoming.

Objectives
In 2011, a massive wildfire named \‘\‘the Horseshoe 2 Burn\’\’ occurred in the Chiricahua National Monument, Arizona, USA. We evaluated the impact of this wildfire on acoustic activity of animal communities.

Methods
In 2013, soundscape recordings were col- lected over 9 months in 12 burned and 12 non-burned sites in four ecological systems. The seasonal and diel biological acoustic activity were described using the \‘\‘Bioacoustic Index\’\’, a detailed aural analysis of sound sources, and a new tool called \‘\‘Sonic Time- lapse Builder\’\’ (STLB).


Results
Seasonal biophony phenology showed a diurnal peak in June and a nocturnal peak in October in all ecological systems. On June mornings, acoustic activity was lower at burned than at non-burned sites in three of four ecological systems, due to a decreased abundance of cicadas directly impacted by the death of trees. Aural analyses revealed that 55\% of recordings from non-burned sites contained insect sounds com- pared to 18\% from burned sites. On October nights, orthopteran activity was more prevalent at some burned sites, possibly due to post-fire emergence of herbaceous.

Conclusions
Soundscape approaches can help address long-term conservation issues involving the responses of animal communities to wildfire. Acoustic methods can serve as a valuable complement to remote sensing for disturbance-based landscape management.

}, keywords = {Conservation biology, disturbance, Remote sensing, Sonic timelapse, Soundscape, Wildfire}, issn = {0921-2973}, doi = {10.1007/s10980-018-0675-3}, url = {http://link.springer.com/10.1007/s10980-018-0675-3}, author = {Gasc, Amandine and Gottesman, Benjamin L. and Francomano, Dante and Jung, Jinha and Durham, Mark and Mateljak, Jason and Bryan C. Pijanowski} }