Ecological Indicators (Feb 2024)
The effect of latitude on the efficacy of acoustic indices to predict biodiversity: A meta-analysis
Abstract
The increasing biodiversity loss worldwide has resulted in a growing need for cost-effective, efficient tools to monitor biodiversity over large spatial and temporal scales. The idea of using acoustic indices to monitor soniferous animal communities is becoming increasingly popular. Dozens of indices have been proposed over the last 15 years to measure acoustic complexity as a proxy of biodiversity. However, we still lack sufficient evaluation of the acoustic indices’ power to predict biodiversity, and the factors modulating their efficacy. Here, we extend a recent meta-analysis on the acoustic indices conducted by Alcocer et al. (2022; Biological Reviews) by increasing the dataset of studies 1.5 times and adding an important modulating variable: latitude. Latitude is strongly connected to species diversity, and it has previously been postulated that acoustic indices may be unable to fully reflect the high species diversity of the tropics, due to limitations related to phylogenetic inertia (i.e., closely related species sounding similar) and interference between species, with masking by insects being particularly common. Using a total of 524 effect sizes from 49 studies, we found a moderate positive correlation between acoustic indices and biodiversity (r = 0.32, 95 % CI [0.20, 0.43]), similar to the finding of Alcocer et al. (2022). Of five moderator variables, latitude was the second most important after the type of acoustic index, with higher latitude studies showing acoustic indices to have greater predictive power. When testing the indices separately with latitude as the only moderator, four of the seven acoustic indices (ACI, AR, BIO, NDSI) were found to be significantly influenced by latitude. Future work should investigate the mechanisms by which latitude influences the acoustic indices’ efficacy. For now, we can conclude that whatever mechanisms are driving acoustic indices to underestimate diversity in tropical forests, the influence is evident even when measuring acoustic complexity in different ways using different indices.
