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Conservation programs need improved tools to measure the recovery of animal diversity across restoration gradients. We used soundscapes and expert identifications of bird species to calculate niche position (i.e., mean of environmental conditions across all areas a species occupies) and niche breadth (i.e., the standard deviation of the species distribution) along a recovery gradient; from agriculture to early (up to 20 yrs) and late (up to 38 yrs) recovery, to old-growth forests. Our survey included 323 bird species and was conducted in 66 plots in the lowland Chocoan tropical rainforest in Ecuador where less than 11% of the forest remains intact, and large areas are currently undergoing regeneration post-abandonment. First, we validated our niche metrics by contrasting them against independent global categories of forest density dependency. We then explained the niche metrics of the bird species with different ecological traits, gathered from the literature, reflecting species-specific primary diet, morphology and distribution, and accounting for the phylogenetic relatedness of species. Finally, we explored the phylogenetic signal present in bird species’ ecological traits and recovery niche metrics. Niche position and breadth across the recovery gradient closely followed global categories of forest density dependency. However, our approach provided a more fine-scaled sorting of bird species in forest plots categorized as late recovery and old-growth. Granivorous birds occupied niche positions in active cacao and pasture plots and were replaced by frugivorous birds in older regeneration plots. Along the recovery gradient, tail length and handwing index decreased with niche position, supporting previous observations that birds in old-growth forests are less mobile. Birds in old-growth forests had smaller global distribution ranges than birds in agricultural plots. Finally, the latitudinal distribution of birds in the study area averaged south of the equator, with birds in old-growth plots averaging latitudinal centroids in wet forests north of the equator, whereas birds in agriculture plots averaged latitudinal centroids further south of the country, towards the dry and open Tumbesian forest. Frugivores, invertivores and vertivores had broader niche breadths, but these decreased (marginally) with tail length. We suggest these recovery niche metrics as a potentially powerful tool for the rapid assessment of the recovery process, which might support conservation strategies such as biodiversity credits, compensation payments, and strategic land purchases. With the increasing availability of information-intensive models for bird species identification, such as deep learning artificial intelligence, our new niche metrics open the avenue for rapid assessment of tropical biodiversity and new conservation areas at larger scales.

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.