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Abstract Researchers have long examined the structure of animal advertisement signals, but comparatively little is known about how often these signals are repeated and what factors predict variation in signaling rate across species. Here, we focus on acoustic advertisement signals to test the hypothesis that calling males experience a tradeoff between investment in the duration or complexity of individual calls and investment in signaling over long time periods. This hypothesis predicts that the number of signals that a male produces per 24 h will negatively correlate with (1) the duration of sound that is produced in each call (the sum of all pulses) and (2) the number of sound pulses per call. To test this hypothesis, we measured call parameters and the number of calls produced per 24 h in 16 species of sympatric phaneropterine katydids from the Panamanian rainforest. This assemblage also provided us with the opportunity to test a second taxonomically specific hypothesis about signaling rates in taxa such as phaneropterine katydids that transition from advertisement calls to mating duets to facilitate mate localization. To establish duets, male phaneropterine katydids call and females produce a short acoustic reply. These duets facilitate searching by males, females, or both sexes, depending on the species. We test the hypothesis that males invest either in calling or in searching for females. This hypothesis predicts a negative relationship between how often males signal over 24 h and how much males move across the landscape relative to females. For the first hypothesis, there was a strong negative relationship between the number of signals and the duration of sound that is produced in each signal, but we find no relationship between the number of signals produced per 24 h and the number of pulses per signal. This result suggests the presence of cross-taxa tradeoffs that limit signal production and duration, but not the structure of individual signals. These tradeoffs could be driven by energetic limitations, predation pressure, signal efficacy, or other signaling costs. For the second hypothesis, we find a negative relationship between the number of signals produced per day and proportion of the light trap catch that is male, likely reflecting males investing either in calling or in searching. These cross-taxa relationships point to the presence of pervasive trade-offs that fundamentally shape the spatial and temporal dynamics of communication. 

A limitation in bioacoustic studies has been the inability to differentiate individual sonic contributions from group‐level dynamics. We present a novel application of acoustic camera technology to investigate how individual wood frogs’ calls influence chorus properties, and how variation influences mating opportunities. We recorded mating calls and used playback trials to gauge preference for different chorus types in the laboratory. Males and females preferred chorus playbacks with low variance in dominant frequency. Females preferred choruses with low mean peak frequency. Field studies revealed more egg masses laid in ponds where males chorused with low variance in dominant frequency. We also noted a trend towards more egg masses laid in ponds where males called with low mean frequency. Nearest‐neighbour distances influenced call timing (neighbours called in succession) and distances increased with variance in chorus frequency. Results highlight the potential fitness implications of individual‐level contributions to a bioacoustic signal produced by groups.

 

We collected 410 10-minute sound recordings of birds in and near the Hubbard Brook Experimental Forest in New Hampshire. Recordings, which encompassed most of the bird breeding season in each of two years, included 130,776 vocalizations from 46 taxa. In the associated publication, we report species lists, rarefaction curves, and vocalization descriptions. We also provide analyses of habitat associations, phenology, and spatial patterning in vocalization activity. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. 

The interface between field biology and technology is energizing the collection of vast quantities of environmental data. Passive acoustic monitoring, the use of unattended recording devices to capture environmental sound, is an example where technological advances have facilitated an influx of data that routinely exceeds the capacity for analysis. Computational advances, particularly the integration of machine learning approaches, will support data extraction efforts. However, the analysis and interpretation of these data will require parallel growth in conceptual and technical approaches for data analysis. Here, we use a large hand‐annotated dataset to showcase analysis approaches that will become increasingly useful as datasets grow and data extraction can be partially automated.

We propose and demonstrate seven technical approaches for analyzing bioacoustic data. These include the following: (1) generating species lists and descriptions of vocal variation, (2) assessing how abiotic factors (e.g., rain and wind) impact vocalization rates, (3) testing for differences in community vocalization activity across sites and habitat types, (4) quantifying the phenology of vocal activity, (5) testing for spatiotemporal correlations in vocalizations within species, (6) among species, and (7) using rarefaction analysis to quantify diversity and optimize bioacoustic sampling.

To demonstrate these approaches, we sampled in 2016 and 2018 and used hand annotations of 129,866 bird vocalizations from two forests in New Hampshire, USA, including sites in the Hubbard Brook Experiment Forest where bioacoustic data could be integrated with more than 50 years of observer‐based avian studies. Acoustic monitoring revealed differences in community patterns in vocalization activity between forests of different ages, as well as between nearby similar watersheds. Of numerous environmental variables that were evaluated, background noise was most clearly related to vocalization rates. The songbird community included one cluster of species where vocalization rates declined as ambient noise increased and another cluster where vocalization rates declined over the nesting season. In some common species, the number of vocalizations produced per day was correlated at scales of up to 15 km. Rarefaction analyses showed that adding sampling sites increased species detections more than adding sampling days.

Although our analyses used hand‐annotated data, the methods will extend readily to large‐scale automated detection of vocalization events. Such data are likely to become increasingly available as autonomous recording units become more advanced, affordable, and power efficient. Passive acoustic monitoring with human or automated identification at the species level offers growing potential to complement observer‐based studies of avian ecology.