Pairing a user-friendly machine-learning animal sound detector with passive acoustic surveys for occupancy modeling of an endangered primate.

Population declines and range contractions due to habitat loss are pervasive among nonhuman primates, with 60% of species threatened with extinction. However, the extensive vocal activity displayed by many primates makes them excellent candidates for passive acoustic surveys. Passive acoustic survey data is increasingly being used to support occupancy models, which have proven to be an efficient means of estimating both population trends and distributions. Passive acoustic surveys can be conducted relatively quickly and at broad scales, but efficient audio data processing has long proven elusive. The machine learning algorithm BirdNET was originally developed for birds but was recently expanded to include nonavian taxa. We demonstrate that BirdNET can accurately and efficiently identify an endangered primate, the Yucatán black howler monkey (Alouatta pigra), by sound in passive acoustic survey data (collected in southeastern Chiapas, Mexico), enabling us to use a single-season occupancy model to inform further survey efforts. Importantly, we also generated data on up to 286 co-occurring bird species, demonstrating the value of integrated animal sound classification tools for biodiversity surveys. BirdNET is freely available, requires no computer science expertise to use, and can readily be expanded to include more species (e.g., its species list recently tripled to >3000), suggesting that passive acoustic surveys, and thus occupancy modeling, for primate conservation could rapidly become much more accessible. Importantly, the long history of bioacoustics in primate research has yielded a wealth of information about their vocal behavior, which can facilitate appropriate survey design and data interpretation.

The machine learning-powered BirdNET App reduces barriers to global bird research by enabling citizen science participation.

The BirdNET App, a free bird sound identification app for Android and iOS that includes over 3,000 bird species, reduces barriers to citizen science while generating tens of millions of bird observations globally that can be used to replicate known patterns in avian ecology.

Using the ecological significance of animal vocalizations to improve inference in acoustic monitoring programs.

Recent bioacoustic advances have facilitated large-scale population monitoring for acoustically active species. Animal sounds, however, can of information that is underutilized in typical approaches to passive acoustic monitoring (PAM) that treat sounds simply as detections. We developed 3 methods of extracting additional ecological detail from acoustic data that are applicable to a broad range of acoustically active species. We conducted landscape-scale passive acoustic surveys of a declining owl species and an invasive congeneric competitor in California. We then used sex-specific vocalization frequency to inform multistate occupancy models; call rates at occupied sites to characterize interactions with interspecific competitors and assess habitat quality; and a flexible multivariate approach to differentiate individuals based on vocal characteristics. The multistate occupancy models yielded novel estimates of breeding status occupancy rates that were more robust to false detections and captured known habitat associations more consistently than single-state occupancy models agnostic to sex. Call rate was related to the presence of a competitor but not habitat quality and thus could constitute a useful behavioral metric for interactions that are challenging to detect in an occupancy framework. Quantifying multivariate distance between groups of vocalizations provided a novel quantitative means of discriminating individuals with ≥20 vocalizations and a flexible tool for balancing type I and II errors. Therefore, it appears possible to estimate site turnover and demographic rates, rather than just occupancy metrics, in PAM programs. Our methods can be applied individually or in concert and are likely generalizable to many acoustically active species. As such, they are opportunities to improve inferences from PAM data and thus benefit conservation.

Uso de la Importancia Ecológica de las Vocalizaciones Animales para Mejorar la Inferencia en los Programas de Monitoreo Acústico Resumen Los avances bioacústicos recientes han facilitado el monitoreo a gran escala de poblaciones de especies acústicamente activas. Sin embargo, los sonidos de animales pueden transmitir cantidades sustanciales de información que queda utilizada insuficientemente en las estrategias comunes de monitoreo acústico pasivo (MAP) que tratan a los sonidos como simples detecciones. Desarrollamos tres métodos de extracción de detalles ecológicos adicionales de los datos acústicos que son aplicables a una gama amplia de especies acústicamente activas. Realizamos censos acústicos pasivos a escala de paisaje para una especie de búho en declinación y para un competidor congenérico invasivo en California. Después utilizamos la frecuencia de vocalizaciones específicas por sexo para orientar los modelos multiestado de ocupación; las tasas de llamados en sitios ocupados para caracterizar las interacciones con los competidores interespecíficos y evaluar la calidad de su hábitat; y una estrategia multivariada flexible para diferenciar a los individuos con base en sus características vocales. Los modelos multiestado de ocupación brindaron estimaciones novedosas para las tasas de ocupación por estado reproductivo que fueron más sólidas ante las detecciones falsas y capturaron el número de asociaciones de hábitat más sistemáticamente que los modelos de estado único agnósticos al sexo. La tasa de llamados estuvo relacionada con la presencia de un competidor pero no con la calidad del hábitat y por lo tanto podría constituir una medida conductual útil para las interacciones que son difíciles de detectar en un marco de trabajo de ocupación. La cuantificación de la distancia multivariada entre los grupos de vocalizaciones proporcionó un medio cuantitativo novedoso para discriminar a los individuos con ≥20 vocalizaciones y una herramienta flexible para balancear los errores del tipo I y del tipo II. Por lo tanto, parecer que hay posibilidad de estimar las tasas demográficas y de rotación, en lugar de sólo las medidas de ocupación, en los programas MAP. Nuestros métodos pueden aplicarse individualmente o de manera conjunta y es probable poder generalizarlas para muchas especies acústicamente activas. Dicho así, son oportunidades para mejorar las inferencias de los datos MAP y por lo tanto, beneficiar a la conservación.

Intraspecific functional diversity of common species enhances community stability.

Common species are fundamental to the structure and function of their communities and may enhance community stability through intraspecific functional diversity (iFD). We measured among-habitat and within-habitat iFD (i.e., among- and within-plant community types) of two common small mammal species using stable isotopes and functional trait dendrograms, determined whether iFD was related to short-term population stability and small mammal community stability, and tested whether spatially explicit trait filters helped explain observed patterns of iFD. Southern red-backed voles (Myodes gapperi) had greater iFD than deer mice (Peromyscus maniculatus), both among habitats, and within the plant community in which they were most abundant (their "primary habitat"). Peromyscus maniculatus populations across habitats differed significantly between years and declined 78% in deciduous forests, their primary habitat, as did the overall deciduous forest small mammal community. Myodes gapperi populations were stable across habitats and within coniferous forest, their primary habitat, as was the coniferous forest small mammal community. Generalized linear models representing internal trait filters (e.g., competition), which increase within-habitat type iFD, best explained variation in M. gapperi diet, while models representing internal filters and external filters (e.g., climate), which suppress within-habitat iFD, best explained P. maniculatus diet. This supports the finding that M. gapperi had higher iFD than P. maniculatus and is consistent with the theory that internal trait filters are associated with higher iFD than external filters. Common species with high iFD can impart a stabilizing influence on their communities, information that can be important for conserving biodiversity under environmental change.