The PAE (Posture-Act-Environment) coding system is a behavior coding system that divides the study of animal behavior into postures, actions, and the corresponding environmental factors, and they are coded correspondingly. It determines the analysis dimension to standardize the study of behavior. To investigate the behavior of A. davidianus during the breeding period, as well as their related postures, actions, and required environmental conditions, this study monitored the behavior of four pairs of A. davidianus in a simulated natural breeding pool using an infrared image monitoring system and recorded the changes in water quality during this process using a water quality monitoring system. The process of reproductive behaviors was observed and recorded with the random sampling method and the focal animal sampling method to classify and code the behaviors, and the ethogram of A. davidianus during the breeding period was constructed based on the PAE coding system. The result showed that 10 postures, 33 actions, 11 environments, and 45 behavioral patterns were differentiated and defined, which were classified into 9 categories of behaviors according to the behavioral function. Among these categories, five were distinguished as behaviors unique to the reproductive period, which include sand pushing, showering, courtship, oviposition, and parental care. The remaining four categories were daily behaviors: exercise, feeding, rest, and miscellaneous behaviors. The quantitative data on water quality and habitat factors that had a significant impact on the behavior of A. davidianus, such as water temperature (WT), pH, and dissolved oxygen (DO), were included in the coding framework, which more accurately expresses the environmental conditions and thresholds required for the breeding behavior.

Optimizing the breeding techniques and increasing the hatching rate of Andrias davidianus offspring necessitates a thorough understanding of its parental care behaviors. However, A. davidianus’ nocturnal and cave-dwelling tendencies pose significant challenges for direct observation. To address this problem, this study constructed a dataset for the parental care behavior of A. davidianus, applied the target detection method to this behavior for the first time, and proposed a detection model for A. davidianus’ parental care behavior based on the YOLOv8s algorithm. Firstly, a multi-scale feature fusion convolution (MSConv) is proposed and combined with a C2f module, which significantly enhances the feature extraction capability of the model. Secondly, the large separable kernel attention is introduced into the spatial pyramid pooling fast (SPPF) layer to effectively reduce the interference factors in the complex environment. Thirdly, to address the problem of low quality of captured images, Wise-IoU (WIoU) is used to replace CIoU in the original YOLOv8 to optimize the loss function and improve the model’s robustness. The experimental results show that the model achieves 85.7% in the mAP50-95, surpassing the YOLOv8s model by 2.1%. Compared with other mainstream models, the overall performance of our model is much better and can effectively detect the parental care behavior of A. davidianus. Our research method not only offers a reference for the behavior recognition of A. davidianus and other amphibians but also provides a new strategy for the smart breeding of A. davidianus.

The circadian rhythm of an animal’s body color change is crucial for its survival and adaptation to the environment, with photoperiod serving as a primary “zeitgeber” that significantly affects the circadian rhythm of color change. To explore the circadian body color change in juvenile Chinese giant salamanders (Andrias davidianus), four distinct photoperiod regimens were established, including the DD group (constant darkness), the LD12:12 group (12 h photophase, 12 h scotophase), the LD16:8 group (16 h photophase, 8 h scotophase), and the LD8:16 group (8 h photophase, 16 h scotophase). Reflectance spectra of dorsal skin were measured every 4 h over a 24 h cycle, with data collected every other day for three consecutive days, totaling 72 h. Reflectance spectra were converted into colorimetric variables to analyze circadian patterns. The results demonstrated that juvenile A. davidianus exhibited highly significant circadian rhythmicity under different photoperiods, with their body color becoming darker during the photophase (mean brightness: 14.650 ± 0.629 to 16.385 ± 1.301) and lighter during the scotophase (mean brightness: 16.473 ± 0.875 to 34.422 ± 2.692). Photoperiod alterations significantly affected the rhythm parameters (mesor, amplitude, and acrophase) of mean brightness variation. Compared with the LD12:12 group, the LD16:8 group (extended photophase) reduced rhythm mesor by 1.415, decreased amplitude by 0.988, and induced a 1.510 h acrophase delay. Conversely, the LD8:16 group (extended scotophase) increased rhythm mesor by 2.141 and amplitude by 2.919. These findings indicate that the circadian rhythm of body color change in juvenile A. davidianus is coordinately regulated by endogenous circadian rhythms and exogenous photoperiodic signals. The findings of this study provide a theoretical foundation for the conservation and management of A. davidianus.

Body colour is an important phenotypic trait of the Chinese giant salamander and may reflect its responses to environmental variation. However, quantitative comparisons of body colour among captive environments remain limited. We examined 56 individuals from six breeding facilities in Zhangjiajie, China. The lightness, red–green coordinate and yellow–blue coordinate of the dorsal surface, ventral surface and body markings were measured, along with water quality variables at each facility. Analysis of variance, principal component analysis, cluster analysis and Pearson correlation analysis were used to compare populations, classify colour types and assess environmental relationships. Body-colour characteristics differed significantly among facilities, although overall colour differences between the body background and markings were not significant. Four colour types were identified, with 87.5% of individuals showing either an orange-brown dorsal surface with greyish-black markings or a grey dorsal surface with black markings. Body colour was significantly associated with water physicochemical variables. Higher pH and dissolved oxygen were mainly related to lower lightness and greater ventral redness, whereas higher total phosphorus and ammonia nitrogen were associated with increased lightness and yellowness. Water temperature mainly affected yellowness. These findings support captive-environment optimisation, body-colour management, conservation breeding and germplasm-resource protection.