Feeding Ecology and Regurgitation–Reingestion Behavior of the Critically Endangered Indri indri in the Maromizaha Protected Area, Eastern Madagascar

Physiological and genomic characterization of Lactiplantibacillus plantarum isolated from Indri indri in Madagascar

AIMS

Indri indri is a lemur of Madagascar which is critically endangered. The analysis of the microbial ecology of the intestine offers tools to improve conservation efforts. This study aimed to achieve a functional genomic analysis of three Lactiplantibacillus plantarum isolates from indris.

METHODS AND RESULTS

Samples were obtained from 18 indri; 3 isolates of Lp. plantarum were obtained from two individuals. The three isolates were closely related to each other, with <10 single nucleotide polymorphisms, suggesting that the two individuals shared diet-associated microbes. The genomes of the three isolates were compared to 96 reference strains of Lp. plantarum. The three isolates of Lp. plantarum were not phenotypically resistant to antibiotics but shared all 17 genes related to antimicrobial resistance that are part of the core genome of Lp. plantarum. The genomes of the three indri isolates of Lp. plantarum also encoded for the 6 core genome genes coding for enzymes related to metabolism of hydroxybenzoic and hydroxycinnamic acids. The phenotype for metabolism of hydroxycinnamic acids by indri isolates of Lp. plantarum matched the genotype.

CONCLUSIONS

Multiple antimicrobial resistance genes and gene coding for metabolism of phenolic compounds were identified in the genomes of the indri isolates, suggesting that Lp. plantarum maintains antimicrobial resistance in defense of antimicrobial plant secondary pathogens and that their metabolism by intestinal bacteria aids digestion of plant material by primate hosts.

There You Are! Automated Detection of Indris' Songs on Features Extracted from Passive Acoustic Recordings

The growing concern for the ongoing biodiversity loss drives researchers towards practical and large-scale automated systems to monitor wild animal populations. Primates, with most species threatened by extinction, face substantial risks. We focused on the vocal activity of the indri (Indri indri) recorded in Maromizaha Forest (Madagascar) from 2019 to 2021 via passive acoustics, a method increasingly used for monitoring activities in different environments. We first used indris’ songs, loud distinctive vocal sequences, to detect the species’ presence. We processed the raw data (66,443 10-min recordings) and extracted acoustic features based on the third-octave band system. We then analysed the features extracted from three datasets, divided according to sampling year, site, and recorder type, with a convolutional neural network that was able to generalise to recording sites and previously unsampled periods via data augmentation and transfer learning. For the three datasets, our network detected the song presence with high accuracy (>90%) and recall (>80%) values. Once provided the model with the time and day of recording, the high-performance values ensured that the classification process could accurately depict both daily and annual habits of indris‘ singing pattern, critical information to optimise field data collection. Overall, using this easy-to-implement species-specific detection workflow as a preprocessing method allows researchers to reduce the time dedicated to manual classification.