Sexual Dimorphism of Acoustic Signals in the Oriental White Stork: Non-invasive Identification of Sex in Birds

Sex identification of ducklings based on acoustic signals

Sex identification of ducklings is a critical step in the poultry farming industry, and accurate sex identification is beneficial for precise breeding and cost savings. In this study, a method for identifying the sex of ducklings based on acoustic signals was proposed. In the first step, duckling vocalizations were collected and an improved spectral subtraction method and high-pass filtering were applied to reduce the influence of noise. Then, duckling vocalizations were automatically detected by using a double-threshold endpoint detection method with 3 parameters: short-time energy (STE), short-time zero-crossing rate (ZCR), and duration (D). Following the extraction of Mel-Spectrogram features from duckling vocalizations, an improved Res2Net deep learning algorithm was used for sex classification. This algorithm was introduced with the Squeeze-and-Excitation (SE) attention mechanism and Ghost module to improve the bottleneck of Res2Net, thereby improving the model accuracy and reducing the number of parameters. The ablative experimental results showed that the introduction of the SE attention mechanism improved the model accuracy by 2.01%, while the Ghost module reduced the number of model parameters by 7.26M and the FLOPs by 0.85G. Moreover, this algorithm was compared with 5 state-of-the-art (SOTA) algorithms, and the results showed that the proposed algorithm has the best cost-effectiveness, with accuracy, recall, specificity, number of parameters, and FLOPs of 94.80, 94.92, 94.69, 18.91M, and 3.46G, respectively. After that, the vocalization detection score and the average confidence strategy were used to predict the sex of individual ducklings, and the accuracy of the proposed model reached 96.67%. In conclusion, the method proposed in this study can effectively detect the sex of ducklings and serve as a reference for automated sex identification of ducklings.

Application of 3D-printed prosthetic lower beak in an Oriental stork (Ciconia boyciana)

To our knowledge, ours is the first case of applying a 3D-printed prosthetic beak to an Oriental stork (Ciconia boyciana). A stork in captivity underwent several surgeries for beak fractures, but the lower-mandible fractures failed to be repaired. Therefore, we applied a patient-specific beak prosthesis of titanium alloy and nylon. Because the prosthetic beak could not be maintained due to mandible and soft-tissue inflammation, the stork was euthanized. Still, we confirmed typical behavior and feeding for ~3 months after surgery. This report highlights some of the challenges we encountered and identifies process improvements required for a more successful surgery.

Hissing of geese: caller identity encoded in a non-vocal acoustic signal

Non-vocal, or unvoiced, signals surprisingly have received very little attention until recently especially when compared to other acoustic signals. Some sounds made by terrestrial vertebrates are produced not only by the larynx but also by the syrinx. Furthermore, some birds are known to produce several types of non-syrinx sounds. Besides mechanical sounds produced by feathers, bills and/or wings, sounds can be also produced by constriction, anywhere along the pathway from the lungs to the lips or nostrils (in mammals), or to the bill (in birds), resulting in turbulent, aerodynamic sounds. These noises often emulate whispering, snorting or hissing. Even though hissing sounds have been studied in mammals and reptiles, only a few studies have analyzed hissing sounds in birds. Presently, only the hissing of small, nesting passerines as a defense against their respective predators have been studied. We studied hissing in domestic goose. This bird represents a ground nesting non-passerine bird which frequently produces hissing out of the nest in comparison to passerines producing hissing during nesting in holes e.g., parids. Compared to vocally produced alarm calls, almost nothing is known about how non-vocal hissing sounds potentially encode information about a caller's identity. Therefore, we aimed to test whether non-vocal air expirations can encode an individual's identity similar to those sounds generated by the syrinx or the larynx. We analyzed 217 hissing sounds from 22 individual geese. We calculated the Potential for Individual Coding (PIC) comparing the coefficient of variation both within and among individuals. In addition, we conducted a series of 15 a stepwise discriminant function analysis (DFA) models. All 16 acoustic variables showed a higher coefficient of variation among individuals. Twelve DFA models revealed 51.2-54.4% classification result (cross-validated output) and all 15 models showed 60.8-68.2% classification output based on conventional DFA in comparison to a 4.5% success rate when classification by chance. This indicates the stability of the DFA results even when using different combinations of variables. Our findings showed that an individual's identity could be encoded with respect to the energy distribution at the beginning of a signal and the lowest frequencies. Body weight did not influence an individual's sound expression. Recognition of hissing mates in dangerous situations could increase the probability of their surviving via a more efficient anti-predator response.

Vocal individuality in drumming in great spotted woodpecker-A biological perspective and implications for conservation

Animals-including conservation biologists-use acoustic signals to recognise and track individuals. The majority of research on this phenomenon has focused on sounds generated by vocal organs (e.g., larynx or syrinx). However, animals also produce sounds using other parts of the body, such as the wings, tail, legs, or bill. In this study we focused on non-syrinx vocalisation of the great spotted woodpecker, called drumming. Drumming consists of strokes of a bill on a tree in short, repeated series, and is performed by both males and females to attract mates and deter rivals. Here, we considered whether the great spotted woodpecker's drumming patterns are sex-specific and whether they enable individual identification. We recorded drumming of 41 great spotted woodpeckers (26 males, 9 females, 6 unsexed). An automatic method was used to measure the intervals between succeeding strokes and to count strokes within a drumming roll. The temporal parameters of drumming that were analysed here had lower within- than between-individual coefficients of variation. Discriminant function analyses correctly assigned 70-88% of rolls to the originating individual, but this depended on whether all individuals were analysed together or split into males and females. We found slight, but significant, differences between males and females in the length of intervals between strokes-males drummed faster than females-but no difference in the number of strokes within a roll. Our study revealed that temporal patterns of drumming in the great spotted woodpecker cannot be used for unambiguous sex determination. Instead, discrimination among individuals may be possible based on the intervals between strokes and the number of strokes within a roll. Therefore, it is possible that differences in the temporal parameters of drumming may be used by birds to identify each other, as well as by researchers to aid in census and monitoring tasks.