Dendrobium loddigesii is a precious traditional Chinese medicine with high medicinal and ornamental value. However, the characterization of its mitochondrial genome is still pending. Here, we assembled the complete mitochondrial genome of D. loddigesii and discovered that its genome possessed a complex multi-chromosome structure. The mitogenome of D. loddigesii consisted of 17 circular subgenomes, ranging in size from 16,323 bp to 56,781 bp. The total length of the mitogenome was 513,356 bp, with a GC content of 43.41%. The mitogenome contained 70 genes, comprising 36 protein-coding genes (PCGs), 31 tRNA genes, and 3 rRNA genes. Furthermore, we detected 403 repeat sequences as well as identified 482 RNA-editing sites and 8154 codons across all PCGs. Following the sequence similarity analysis, 27 fragments exhibiting homology to both the mitogenome and chloroplast genome were discovered, accounting for 9.86% mitogenome of D. loddigesii. Synteny analysis revealed numerous sequence rearrangements in D. loddigesii and the mitogenomes of related species. Phylogenetic analysis strongly supported that D. loddigesii and D. Amplum formed a single clade with 100% bootstrap support. The outcomes will significantly augment the orchid mitochondrial genome database, offering profound insights into Dendrobium’s intricate mitochondrial genome architecture.

Passive acoustic monitoring (PAM) is an automatic and non-invasive method for long-term monitoring of bird vocal activity. PAM generates a large amount of data, and the automatic recognition of data poses significant challenges. BirdNET is a free-to-use sound algorithm. We evaluated the effectiveness of BirdNET in identifying the vocalizations of Chinese Bamboo Partridge (a Chinese endemic species) and proposed a random forest (RF) method to improve the result based on the detection of BirdNET. The diurnal and seasonal patterns of calling activity were described based on the identification results. The results showed that the recall of BirdNET-Analyzer was 16.6%, the precision of BirdNET-Analyzer-XHS was 50.8%, and the recall and precision of the RF model were 75.2% and 74.4%, respectively. The diurnal vocal activity of the Chinese Bamboo Partridge showed a bimodal pattern, with peaks around sunrise and sunset and low vocal activity during the central hours of the day. The seasonal vocal activity displayed a unimodal pattern, with a peak in vocal activity during April and May. This study used the Chinese Bamboo Partridge as an example and proposes an improved RF model, built on BirdNET recognition results, for species identification, providing a practical approach for recognizing the vocalizations of regional species.