Acoustic Indices as Key Biodiversity Indicators in Agroforestry Systems
SSRN, ISSN: 1556-5068
2024
- 128Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Agroforestry systems are widely recognised for their positive impacts on biodiversity. Despite numerous claims of biodiversity benefits, many agroforestry projects lack scalable and cost-effective monitoring methods. This study investigated the feasibility of using acoustic indices derived from recordings in coffee agroforestry systems in El Salvador as a cost-effective monitoring tool for agroforestry systems (AFS). Our results show that the Acoustic Complexity Index (ACI) and the High-Frequency Cover (HFC) index were most effective in reflecting vocal communities. In particular, the ACI showed a high correlation with bird richness at dawn, the time period of peak bird activity (R2=0.72). The ACI did not show correlations with stand structures, whereas bird richness showed correlations with mean tree diameter and tree richness at the plot level. HFC correlated significantly with mean plot level tree diameter and reflected the presence of insects stridulating in high frequency ranges. These results suggest that selected and validated acoustic indices are a promising and cost-effective proxies to track changes in biodiversity in agroforestry systems.
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