The establishment of a soundscape baseline might allow the rapid detection of significant environmental changes and could potentially be a holistic instrument for biome conservation. Due to the diversity and variability of the sounds produced in an ecosystem, the establishment of a baseline is complex. Thus we evaluated if, in an ever-changing soundscape, it was possible to find dominant acoustic features on a monthly and hourly scale. Dominant power spectrums (PSs) in an area of premontane moist forest were identified by correlating PSs from February to December 2015, calculating the linear correlation between them, and defining a set of PSs that were strongly correlated (Pearson > = 0.95) to most of the obtained PSs. For any two PSs, the Pearson coefficient > = 0.95 accounted for an equivalence relation between the PSs; these relations allowed us to group spectrums into a few sets. In the daytime, 7.3% (eight out of 109 PSs) of the PSs (i.e., the dominant spectrums) were strongly correlated to 80.7% of the obtained PSs; the remaining 19.3% were singular PSs, weakly correlated to other diurnal PSs. During the night, 6.06% (four out of 66 PSs) of the PSs (i.e., the dominant spectrums) were strongly correlated to 53.0% of the obtained PSs; the remaining 47.0% were singular PSs, weakly correlated to other nocturnal PSs. Strong correlations between the PSs on an hourly scale and monthly scale could be used to denote features that prevail over time. The occurrence of strong associations between PSs (i.e., > 0.98) in spectrums from different months suggests that the generation of sound in the studied forest has a well-defined frequency distribution.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Aide TM, Corrada-Bravo C, Campos-Cerqueira M et al (2013) Real-time bioacoustics monitoring and automated species identification. PeerJ 1:e103. https://doi.org/10.7717/peerj.103
Balakrishnan R (2005) Species concepts, species boundaries and species identification: a view from the tropics. Syst Biol 54:689–693. https://doi.org/10.1080/10635150590950308
Conti ME, Cecchetti G (2001) Biological monitoring: lichens as bioindicators of air pollution assessment—a review. Environ Pollut 114:471–492
Deichmann JL, Hernández-Serna A, Delgado CJA et al (2017) Soundscape analysis and acoustic monitoring document impacts of natural gas exploration on biodiversity in a tropical forest. Ecol Indic 74:39–48. https://doi.org/10.1016/j.ecolind.2016.11.002
Farina A, Ceraulo M, Bobryk C et al (2015) Spatial and temporal variation of bird dawn chorus and successive acoustic morning activity in a Mediterranean landscape. Bioacoustics 24(3):269–288
Fuller S, Axel AC, Tucker D, Gage SH (2015) Connecting soundscape to landscape: which acoustic index best describes landscape configuration? Ecol Indic 58:207–215. https://doi.org/10.1016/j.ecolind.2015.05.057
Gasc A, Sueur J, Pavoine S et al (2013) Biodiversity sampling using a global acoustic approach: contrasting sites with microendemics in New Caledonia. PLoS One 8:e65311. https://doi.org/10.1371/journal.pone.0065311
Gasc A, Pavoine S, Lellouch L et al (2015) Acoustic indices for biodiversity assessments: analyses of bias based on simulated bird assemblages and recommendations for field surveys. Biol Conserv 191:306–312. https://doi.org/10.1016/j.biocon.2015.06.018
Gasc A, Anso J, Sueur J et al (2017) Cricket calling communities as an indicator of the invasive ant Wasmannia auropunctata in an insular biodiversity hotspot. Biol Invasions. https://doi.org/10.1007/s10530-017-1612-0
Gaston KJ, O’Neill MA (2004) Automated species identification: why not? Philos Trans R Soc Lond B Biol Sci 359:655–667
Jones G, Jacobs D, Kunz T et al (2009) Carpe noctem: the importance of bats as bioindicators. Endanger Species Res 8:93–115. https://doi.org/10.3354/esr00182
Lengagne T, Slater PJB (2002) The effects of rain on acoustic communication: tawny owls have good reason for calling less in wet weather. Proc R Soc B Biol Sci 269:2121–2125. https://doi.org/10.1098/rspb.2002.2115
Mazaris AD, Kallimanis AS, Chatzigianidis G et al (2009) Spatiotemporal analysis of an acoustic environment: interactions between landscape features and sounds. Landsc Ecol 24:817–831. https://doi.org/10.1007/s10980-009-9360-x
Mullet TC, Gage SH, Morton JM, Huettmann F (2016) Temporal and spatial variation of a winter soundscape in south-central Alaska. Landsc Ecol 31:1117–1137. https://doi.org/10.1007/s10980-015-0323-0
Pijanowski BC, Farina A, Gage SH et al (2011a) What is soundscape ecology? An introduction and overview of an emerging new science. Landsc Ecol 26:1213–1232. https://doi.org/10.1007/s10980-011-9600-8
Pijanowski BC, Villanueva-Rivera LJ, Dumyahn SL et al (2011b) Soundscape ecology: the science of sound in the landscape. Bioscience 61:203–216. https://doi.org/10.1525/bio.2011.61.3.6
Rainio J, Niemelä J (2003) Ground beetles (Coleoptera: carabidae) as bioindicators. Biodivers Conserv 12:487–506
Sueur J, Pavoine S, Hamerlynck O, Duvail S (2008) Rapid acoustic survey for biodiversity appraisal. PLoS One 3:e4065. https://doi.org/10.1371/journal.pone.0004065
Tews J, Brose U, Grimm V et al (2004) Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures. J Biogeogr 31:79–92
Ulloa JS, Gasc A, Gaucher P et al (2016) Screening large audio datasets to determine the time and space distribution of screaming piha birds in a tropical forest. Ecol Inform 31:91–99. https://doi.org/10.1016/j.ecoinf.2015.11.012
We are grateful to Prof. Juan Pablo Gomez for all his valuable insights and advice on the data analysis.
About this article
Cite this article
Almeira, J., Guecha, S. Dominant power spectrums as a tool to establish an ecoacoustic baseline in a premontane moist forest. Landscape Ecol Eng 15, 121–130 (2019). https://doi.org/10.1007/s11355-018-0355-0
- Day-night cycle
- Equivalence relation
- Acoustic diversity