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Estimating ecoacoustic activity in the Amazon rainforest through Information Theory quantifiers

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  • Juan G Colonna
  • José R H Carvalho
  • Osvaldo A Rosso

Abstract

Automatic monitoring of biodiversity by acoustic sensors has become an indispensable tool to assess environmental stress at an early stage. Due to the difficulty in recognizing the Amazon’s high acoustic diversity and the large amounts of raw audio data recorded by the sensors, the labeling and manual inspection of this data is not feasible. Therefore, we propose an ecoacoustic index that allows us to quantify the complexity of an audio segment and correlate this measure with the biodiversity of the soundscape. The approach uses unsupervised methods to avoid the problem of labeling each species individually. The proposed index, named the Ecoacoustic Global Complexity Index (EGCI), makes use of Entropy, Divergence and Statistical Complexity. A distinguishing feature of this index is the mapping of each audio segment, including those of varied lengths, as a single point in a 2D-plane, supporting us in understanding the ecoacoustic dynamics of the rainforest. The main results show a regularity in the ecoacoustic richness of a floodplain, considering different temporal granularities, be it between hours of the day or between consecutive days of the monitoring program. We observed that this regularity does a good job of characterizing the soundscape of the environmental protection area of Mamirauá, in the Amazon, differentiating between species richness and environmental phenomena.

Suggested Citation

  • Juan G Colonna & José R H Carvalho & Osvaldo A Rosso, 2020. "Estimating ecoacoustic activity in the Amazon rainforest through Information Theory quantifiers," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-21, July.
  • Handle: RePEc:plo:pone00:0229425
    DOI: 10.1371/journal.pone.0229425
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    References listed on IDEAS

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    1. Rosso, Osvaldo A. & Carpi, Laura C. & Saco, Patricia M. & Gómez Ravetti, Martín & Plastino, Angelo & Larrondo, Hilda A., 2012. "Causality and the entropy–complexity plane: Robustness and missing ordinal patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 42-55.
    2. Martín Gómez Ravetti & Laura C Carpi & Bruna Amin Gonçalves & Alejandro C Frery & Osvaldo A Rosso, 2014. "Distinguishing Noise from Chaos: Objective versus Subjective Criteria Using Horizontal Visibility Graph," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-15, September.
    3. Passerini, Filippo & Severini, Simone, 2008. "The von Neumann entropy of networks," MPRA Paper 12538, University Library of Munich, Germany.
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