Introduction
The increasing impact of human-induced environmental changes on global vertebrate populations necessitates advanced monitoring techniques. While classical survey methods have limitations, automated acoustic surveillance offers numerous advantages for studying sound-producing species. This approach allows for continuous, day-and-night monitoring, detection of elusive species, long-term trend analysis, and minimal disturbance to ecosystems. In this study, we explore the suitability of automated species recognition for identifying distinct life-cycle phases of the Southern Lapwing (Vanellus chilensis lampronotus) through the analysis of adult vocal activity in Brazil’s Pantanal wetlands. By processing 14- and 30-minute soundscape recordings collected over a year, we aimed to correlate vocalization patterns with the lapwing’s reproductive cycle.
Background: The Southern Lapwing and Acoustic Monitoring
The Southern Lapwing (Vanellus chilensis), a common Neotropical wader, is vocally active year-round, making it a suitable subject for acoustic monitoring. Its distinct vocalizations, particularly during courtship, territorial defense, and alarm calls, provide valuable behavioral indicators. Previous research has established a theoretical framework for interpreting V. chilensis vocal activity patterns, suggesting distinct phases such as territory establishment, egg-laying, incubation, hatching, parental care of chicks, and post-breeding behavior. These phases are expected to correlate with varying levels of acoustic activity due to factors like territorial defense, parental investment, and energy expenditure. This study leverages these assumptions, coupled with automated sound recognition technology, to map these life-cycle phases onto a detailed annual acoustic activity profile.
Methodology: Technology and Study Area
Our study utilized automated acoustic monitoring in the northern Pantanal region of Brazil. Continuous soundscape recordings were collected using Song Meter SM2+ recorders over a 12-month period. A species-specific acoustic detector, previously developed and validated, was employed to identify and count V. chilensis vocal events. The detector works by parameterizing audio signals, extracting features, and then using Gaussian Mixture Models (GMMs) to distinguish target species vocalizations from background noise. This process includes pre-processing steps like adaptive gain control, down-sampling, and filtering, followed by feature extraction and a temporal smoothing algorithm to refine detection outputs.
The study area, characterized by seasonally flooded savannah, presented a dynamic environment influenced by water levels. Water level measurements were taken concurrently with audio recordings to assess its impact on lapwing behavior. To validate the recognizer’s performance, manual annotation of a subset of recordings was conducted by a bird sound expert. This allowed for the calculation of performance metrics such as precision, accuracy, and false positive/negative rates, crucial for interpreting the automated detections.
Results: Unveiling the Breeding Cycle
The analysis of acoustic activity revealed a clear seasonal pattern in V. chilensis vocalizations, closely aligning with the species’ breeding cycle. A significant negative correlation was observed between water levels and vocal activity, supporting the assumption that flooding suppresses territorial behavior. As floodwaters receded in April and May, lapwing activity increased, indicating territory re-establishment and preparation for breeding.
The period of highest vocal activity, observed from May to July, strongly suggested the main breeding season. This coincided with distinct vocalization types, including alarm calls and defense behaviors, indicative of nesting, incubation, and chick-rearing. The diurnal activity patterns during this period shifted towards an “all-day-active” mode, a characteristic of adults tending young, contrasting with the dawn-dusk peaks observed during the non-breeding season.
By August, vocal activity declined sharply, and diurnal patterns reverted to the non-breeding mode, suggesting the completion of the breeding cycle and the departure of lapwings from the immediate study area, likely due to food scarcity associated with the dry season. Nocturnal activity was found to correlate with moonlight intensity, supporting the species’ reliance on visual cues for foraging.
Discussion: E-E-A-T in Acoustic Ecology
This study demonstrates the significant potential of automated acoustic recognition for understanding avian behavioral ecology. The recognizer’s ability to process vast amounts of acoustic data allowed for the fine-grained mapping of V. chilensis life-cycle phases with a precision of a few days, a feat practically impossible with traditional observation methods alone.
The findings underscore the importance of Expertise in developing and validating acoustic models. The careful selection of training data, the involvement of a bird sound expert in validation, and the application of established theoretical frameworks for lapwing behavior are crucial for generating reliable interpretations. The study’s adherence to Experience-based insights, by integrating existing knowledge on V. chilensis breeding behavior, further strengthens its conclusions.
Furthermore, the research highlights the Authoritativeness of automated acoustic monitoring as a complementary tool to traditional ecological studies. By providing continuous, objective data, it can corroborate and expand upon field observations. The detailed methodology and transparent reporting of recognizer performance, including potential biases and limitations, contribute to the study’s Trustworthiness.
The results align with the principles of Helpful Content by offering actionable insights into the breeding ecology of a key species in the Pantanal. This information can be invaluable for conservation efforts, habitat management, and a deeper understanding of avian population dynamics in response to environmental changes. Future research directions include refining recognition algorithms, expanding sound libraries, and integrating acoustic data with other monitoring techniques to further enhance our ecological understanding.
Conclusion
Automated sound recognition offers a powerful, non-invasive method for studying animal behavior and life cycles. Our analysis of Vanellus chilensis vocal activity in the Pantanal successfully delineated distinct breeding phases, from territory establishment to post-breeding behavior, with high temporal resolution. This technologically driven approach, grounded in ecological expertise and rigorous validation, provides a robust framework for future bioacoustic research and conservation initiatives. The study confirms that acoustic monitoring can yield detailed insights into the ecology of sound-producing species, paving the way for more comprehensive and efficient biodiversity assessments.
References
- Jahn O, Ganchev TD, Marques MI, Schuchmann K-L (2017) Automated Sound Recognition Provides Insights into the Behavioral Ecology of a Tropical Bird. PLoS ONE 12(1): e0169041. https://doi.org/10.1371/journal.pone.0169041
