It is not just about birds: what do acoustic indices reveal about a Costa Rican tropical rainforest?

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.

Acoustic indices as proxies for biodiversity: a meta‐analysis

“…New research on less‐studied taxa and environments will be crucial for a comprehensive understanding of acoustic communities and their link with acoustic indices. Some recent studies are providing the first steps to fill this knowledge gap (Greenhalgh et al ., 2020 ; Retamosa Izaguirre et al ., 2021 ).…”

“…Buxton et al ., 2018 b ; Bradfer‐Lawrence et al ., 2020 ), or the fitting of multiple regression models (e.g. Retamosa Izaguirre et al ., 2021 ). Despite being proposed early on, few studies have applied these methods so far, likely because computation and data analysis are more complex and time‐consuming than the use of indices as single predictors (e.g.…”

Temporal Soundscape Patterns in a Panamanian Tree Diversity Experiment: Polycultures Show an Increase in High Frequency Cover

“…If we understand acoustic indices as an integrative measure of biodiversity that reflects the soundscape composition and particularly the acoustic communities as a whole in response to human activity and ecological gradients (Pijanowski et al, 2011;Farina, 2014;Farina and Gage, 2017) we also have to understand that a single acoustic index will rarely correspond only to a single vocalizing animal group (Retamosa Izaguirre et al, 2021). This is probably especially true in the tropics as different vocalizing animal groups often vocalize at the same time (Eldridge et al, 2018) and could explain why in our study the temporal patterns of the chosen acoustic indices did not match the patterns of a single vocalizing animal group perfectly well.…”

Land-use intensity and landscape structure drive the acoustic composition of grasslands

“…the collection of biological, geophysical and anthropogenic sounds that emanate from a landscape (Pijanowski et al, 2011) are highly specific to each habitat. It depends on the local composition of the vocalizing species community (termed biophony), as well as on abiotic factors such as wind and rain (geophony) and on human activities that produce sounds (anthropophony) (Bradfer-Lawrence et al, 2019;Buxton et al, 2018;Eldridge et al, 2018;Retamosa Izaguirre et al, 2021). Since different vocalizing animal groups are influenced differently by various land-use components and are not always strongly correlated with each other (Manning et al, 2015), it can be expected that the numerous components of the soundscape are each influenced by different drivers.…”