ArticleNature communications2023
Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- AI-driven technological breakthroughs and practical pathways for biodiversity conservation and ecological management.iScience · 2026Review
- Listening forward: emerging roles of bioacoustics in ecology, evolution, and conservation.Biologia futura · 2026Review
- Twelve quick tips for applying deep learning to animal sounds.PLoS computational biology · 2026Article
- Habitat filtering, not dispersal limitation, drives ant and termite community assembly along a tropical forest regeneration gradient.Oecologia · 2026Article
- Large-Scale Forest Restoration Accompanied by Biodiversity Recovery in Costa Rica's Redistributive Payment for Ecosystem Service Program.Global change biology · 2026Article
- 12 years of assembly patterns in saproxylic beetles suggest early decay wood as ephemeral resource patch.The Journal of animal ecology · 2026Article
- Illustrated Catalogue and Phylogenetic Relationships of 330 Species of Arctiinae Moth Species from the Chocó Rainforest in NW Ecuador: Most Species are Undescribed.Neotropical entomology · 2025Article
- Habitat and land-use intensity shape moth community structure across temperate forest and grassland.The Journal of animal ecology · 2025Article
- Automatic detection and annotation of eastern Caribbean sperm whale codas.Scientific reports · 2025Article
- Towards a toolkit for global insect biodiversity monitoring.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Extensive data engineering to the rescue: building a multi-species katydid detector from unbalanced, atypical training datasets.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Combining environmental DNA and remote sensing for efficient, fine-scale mapping of arthropod biodiversity.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Time and habitat structure shape insect acoustic activity in the Amazon.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Piccadilly full of people and other foul things : On heroism and perversion in the post-pandemic era.EMBO reports · 2024Article
- The Deep Learning-Crop Platform (DL-CRoP): For Species-Level Identification and Nutrient Status of Agricultural Crops.Research (Washington, D.C.) · 2024Article
- How AI can help to save endangered species.Nature · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
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 metabarcoding 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 composition 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 metabarcoding. We show that such automated monitoring tools, based on new technologies, can effectively monitor the success of forest recovery, using robust and reproducible data.
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