02274nas a2200169 4500008004100000022001300041245012300054210006900177260001600246520167600262100002001938700001501958700001901973700001901992700002602011856006702037 2019 eng d a1574954100aContributions of MIR to soundscape ecology. Part 2: Spectral timbral analysis for discriminating soundscape components0 aContributions of MIR to soundscape ecology Part 2 Spectral timbr cJan-02-20193 a

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.

1 aVanSchaik, Jack1 aZhao, Zhao1 aGasc, Amandine1 aOmrani, Hichem1 aPijanowski, Bryan, C. uhttps://linkinghub.elsevier.com/retrieve/pii/S157495411830190002183nas a2200133 4500008004100000022001300041245007400054210006900128300001200197490000600209520176400215100002001979856005001999 2017 eng d a2158404400aSpatial Soundscape Ecology: Application in a Paleotropical Rainforest0 aSpatial Soundscape Ecology Application in a Paleotropical Rainfo a65 - 710 v73 a

The world’s biodiversity is declining with much of the decrease attributed to human activity. The paleotropical rainforests of Borneo contribute 10% of the world biodiversity but are at risk of destruction due to logging and other human inter- ests. Soundscape ecology, defi ned as the study of the composition of sounds in an environment, is a new fi eld that offers solutions for assessing bio- diversity and disturbance. Spatial dynamics are an important component of an ecosystem, yet the link between spatial dynamics and soundscapes has not yet been studied. It should be possible to assess disturbance of an ecosystem by analyzing the spatial structure of the soundscape. Partic- ularly, soundscapes in undisturbed ecosystems should exhibit more spatial autocorrelation than soundscapes in disturbed ecosystems. We took automated bihourly 10-minute recordings at a dis- turbed (n = 4,905) and an undisturbed (n = 8,450) transect in Brunei, Borneo, for a month-long peri- od. Sites had identical spatial confi gurations, with 13 recorders at each site. Alpha acoustic indices were computed from recorded sound fi les, and beta acoustic indices were calculated pairwise for each 13 recorder group at each unique record- ing time. Moran’s I statistics were calculated to compare the resultant alpha indices from the two transects. We compared beta indices by Mantel Tests. Spatial statistics on alpha and beta indices reveal more spatial autocorrelation and correla- tion at the undisturbed site. Of all alpha indices, Normalized Difference Soundscape Index (NDSI) detected spatial autocorrelation to the highest extent. Beta acoustic indices detected differences between the two sites more precisely, due to their comparative nature.

1 aVanSchaik, Jack uhttp://docs.lib.purdue.edu/jpur/vol7/iss1/10/