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Dryad

Soundscapes and artificial intelligence provide powerful tools to track biodiversity recovery in tropical forests

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Sep 07, 2023 version files 2.08 GB

Abstract

Tropical forest recovery is fundamental to addressing the intertwined climate and biodiversity loss crises. While regenerating trees sequester carbon relatively quickly, the pace of biodiversity recovery remains contentious. Here, we use bioacoustics and meta-barcoding to measure forest recovery post-agriculture in a global biodiversity hotspot in Ecuador. We show that the community composition, and not species richness, of vocalizing vertebrates identified by experts reflects the restoration gradient. Two automated measures – an acoustic index model and a bird community derived from an independently developed Convolutional Neural Network – correlated well with restoration (adj-R2 = 0.62 and 0.69, respectively). Importantly, both measures reflected composition of non-vocalizing nocturnal insects identified via meta-barcoding. We show that such automated monitoring tools, based on new technologies, can effectively monitor the success of forest recovery, using robust and reproducible data. Crucially, this will help ensure that forest restoration efforts result in resilient, biodiverse tropical forests and not simply ‘carbon farms’.