1. Animals produce sounds for diverse biological functions such as defending territories, attracting mates, deterring predators, navigation, finding food and maintaining contact with members of their social group. Biologists can take advantage of these acoustic behaviours to gain valuable insights into the spatial and temporal scales over which individuals and populations interact. Advances in bioacoustic technology, including the development of autonomous cabled and wireless recording arrays, permit data collection at multiple locations over time. These systems are transforming the way we study individuals and populations of animals and are leading to significant advances in our understandings of the complex interactions between animals and their habitats. 2. Here, we review questions that can be addressed using bioacoustic approaches, by providing a primer on technologies and approaches used to study animals at multiple organizational levels by ecologists, behaviourists and conservation biologists. 3. Spatially dispersed groups of microphones (arrays) enable users to study signal directionality on a small scale or to locate animals and track their movements on a larger scale. 4. Advances in algorithm development can allow users to discriminate among species, sexes, age groups and individuals. 5. With such technology, users can remotely and non-invasively survey populations, describe the soundscape, quantify anthropogenic noise, study species interactions, gain new insights into the social dynamics of sound-producing animals and track the effects of factors such as climate change and habitat fragmentation on phenology and biodiversity. 6. There remain many challenges in the use of acoustic monitoring, including the difficulties in performing signal recognition across taxa. The bioacoustics community should focus on developing a common framework for signal recognition that allows for various species’ data to be analysed by any recognition system supporting a set of common standards. 7. Synthesis and applications. Microphone arrays are increasingly used to remotely monitor acoustically active animals. We provide examples from a variety of taxa where acoustic arrays have been used for ecological, behavioural and conservation studies. We discuss the technologies used, the methodologies for automating signal recognition and some of the remaining challenges. We also make recommendations for using this technology to aid in wildlife management.

Summary: 1. Using arrays of microphones, biologists can monitor the position of free‐living animals based on the sounds they produce. Microphone array technology exploits differences in sound arrival times at each microphone to calculate an animal’s position. This technology provides new opportunities for studying animal ecology and behaviour and has many advantages over tracking technologies that require capturing animals and fitting them with external devices, or technologies that focus on one individual in isolation of the activities of nearby animals.2. The efficacy of microphone arrays for triangulating the position of wild animals has been established through previous studies. Yet widespread use of microphone array technology has been limited by many factors: arrays are expensive, custom manufactured, and cumbersome. Consequently, microphone arrays are used infrequently, in spite of their transformative potential for studying animal ecology and behaviour.3. We conducted a field test of a new wireless microphone array system that has multiple advantages over previous systems: it is relatively inexpensive, commercially available, includes an integrated global positioning system (GPS) for time‐synchronizing microphones, and it is small enough to fit in a backpack. We set up an array of four stereo recorders (each with a pair of stereo microphones) at 12 sites and tested the system’s accuracy for estimating the location of loudspeakers broadcasting 25 types of bird, mammal and frog sounds.4. We found that this system produced accurate location estimates based on multi‐channel recordings of many types of acoustic signals. The average location accuracy was 1·87 ± 0·13 m, on par with cable‐based microphone array systems. Location accuracy was significantly higher when the recorders were closer together and when sounds were broadcast inside the area bounded by the microphones. Accuracy tended to be higher in field vs. forest habitats.5. We discuss how this system may be used to enhance studies of animal ecology and behaviour across a wide range of contexts. As with previous arrays, this system will allow researchers to monitor animals that produce distinctive acoustic signals. In contrast to previous microphone arrays, this system is affordable, portable and commercially available. Consequently, this system stands to dramatically enhance research on wild, free‐living animals.

Although offering many benefits over manual recording and survey techniques for avian field studies, automated sound recording systems produce large datasets that must be carefully examined to locate sounds of interest. We compared two methods for locating target sounds in continuous sound recordings: (1) a manual method using computer software to provide a visual representation of the recording as a sound spectrogram and (2) an automated method using sound analysis software preprogrammed to identify specific target sounds. For both methods, we examined the time required to process a 24-h recording, scanning accuracy, and scanning comprehensiveness using four different target sounds of Pileated Woodpeckers (Dryocopus pileatus), Pale-billed Woodpeckers (Campephilus guatemalensis), and putative Ivory-billed Woodpeckers (Campehilus principalis). We collected recordings from the bottomland forests of Florida and the Neotropical dry forests of Costa Rica, and compared manual versus automated cross-correlation scanning techniques. The automated scanning method required less time to process sound recordings, but made more false positive identifications and was less comprehensive than the manual method, identifying significantly fewer target sounds. Although the automated scanning method offers a fast and economic alternative to traditional manual efforts, our results indicate that manual scanning is best for studies requiring an accurate account of temporal patterns in call frequency and for those involving birds with low vocalization rates. © 2009 Association of Field Ornithologists