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Abstract

Acoustic monitoring is used to assess biodiversity across large spatial and temporal scales. However, extracting meaningful information from large data sets might be exceedingly time consuming. For this reason, acoustic indices have been proposed as proxies for biodiversity monitoring. Although acoustic indices hold great promise for standardizing acoustic data analysis, the complexity of acoustic conditions requires careful examination of the relationship between an index and the underlying process of interest. We evaluated 11 acoustic indices at two operational levels: (1) acoustic community level (an aggregation of species that produces sound), using birds as an example to assess how well acoustic indices predict bird indices (abundance, richness, evenness and diversity); and (2) soundscape level (the collection of biological, geophysical and anthropogenic sounds from a landscape), using acoustic indices to classify the study sites according to their ecological condition. To study the relationship among these variables, we selected two study sites with different ecological conditions (in terms of vegetation structure and traffic noise) within the Braulio Carrillo National Park (BCNP), Costa Rica. We sampled the soundscape and bird community using 12 sampling points and four visits to each study site from June 2017 to August 2018. We continuously recorded sounds at sunrise and sunset, and for 10 minutes every hour, during two consecutive days per visit. In addition, we performed four bird counts per visit (sunrise and sunset). We performed a correlation analysis between 11 acoustic indices and 4 community bird indices. We analyzed the ability of acoustic indices to predict bird indices. Furthermore, we used acoustic indices to classify the two sites according to their ecological condition. Bird abundance and richness were positively correlated with acoustic evenness indices and negatively correlated with the acoustic diversity index, but the whole set of acoustic indices predicted bird indices weakly. However, the classification of the sites using acoustic indices was conducted with a high average precision of 0.93 (sd = 0.08). Acoustic indices appear to be more promising for evaluating the ecological condition of a site than abundance, richness or diversity of specific animal groups, in this case birds, in tropical rainforests.

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