Autonomous recording units in avian ecological research: current use and future applications

Abstract

ABSTRACT. Acoustic surveys are a widely used sampling tool in ecological research and monitoring. They are used to monitor populations and ecosystems and to study various aspects of animal behavior. Autonomous recording units (ARUs) can record sound in most environments and are increasingly used by researchers to conduct acoustic surveys for birds. In this review, we summarize the use of ARUs in avian ecological research and synthesize current knowledge of the benefits and drawbacks of this technology. ARUs enable researchers to do more repeat visits with less time spent in the field, with the added benefits of a permanent record of the data collected and reduced observer bias. They are useful in remote locations and for targeting rare species. ARUs are mostly comparable to human observers in terms of species richness, but in some cases, they detect fewer species and at shorter distances. Drawbacks of ARUs include the cost of equipment, storage of recordings, loss of data if units fail, and potential sampling trade-offs in spatial vs. temporal coverage. ARUs generate large data sets of audio recordings, but advances in automated species recognition and acoustic processing techniques are contributing to make the processing time manageable. Future applications of ARUs include biodiversity monitoring and studying habitat use, animal movement, and various behavioral ecology questions based on vocalization activity. ARUs have the potential to make significant advances in avian ecological research and to be used in more innovative ways than simply as a substitute for a human observer in the field. Unités d'enregistrement autonomes en écologie aviaire : utilisations actuelles et futuresRÉSUMÉ. Les relevés acoustiques sont largement employés comme outil d'échantillonnage pour la recherche et les suivis écologiques. Ils sont utilisés pour suivre les populations et les écosystèmes et étudier le comportement animal sous divers angles. Les unités d'enregistrement autonomes (ARU, pour autonomus recording units) peuvent enregistrer les sons dans la plupart des environnements et sont utilisés de plus en plus souvent par les chercheurs pour effectuer des relevés acoustiques d'oiseaux. Dans la présente revue, nous résumons l'utilisation d'ARU en écologie aviaire et synthétisons les avantages et désavantages connus de cette technologie. Les ARU permettent aux chercheurs de faire plus de visites répétées tout en passant moins de temps sur le terrain, avec l'avantage d'avoir un enregistrement permanent des données récoltées et de réduire le biais associé à l'observateur. Ils sont utiles en milieu éloigné et dans les cas où on cible des espèces rares. Les ARU sont comparables aux observateurs humains pour ce qui est de la richesse spécifique, mais dans certains cas, ils détectent moins d'espèces et à des distances plus courtes. Les désavantages des ARU comprennent le coût de l'équipement, la sauvegarde des enregistrements, la perte de données en cas de défaillance des unités, et le compromis possible à devoir faire sur le plan de la...

Potential benefits of augmenting road-based breeding bird surveys with autonomous recordings

“…This can result in low detectability and misidentifications. Reinterpretation of ARU-based data provides an opportunity to correct errors, verify unknowns, and reduce inter-and intraobserver errors (Rempel et al 2005, Campbell and Francis 2011, Shonfield and Bayne 2017. Another promising contribution of ARUs to the BBS is the possibility to increase data quantity and quality by sampling at different time periods with no additional added field effort.…”

“…Thus, it is important to assess whether employing ARUs would introduce systematic biases in species richness and speciesspecific abundance indices derived by on-road ARU BBS and forest-edge ARU BBS surveys relative to human BBS surveys, i.e., recordings of the same 3-minute period. Some studies have shown differences in detectability between human-and recording-based surveys, whereas others have not (e.g., Hutto and Stutzman 2009, Campbell and Francis 2011, Venier et al 2012, Shonfield and Bayne 2017. However, documenting the relative importance of survey type (human vs. ARU-based surveys) and sampling location (on-road vs. forest edge) on bird counts is key to understanding and thereby standardizing differences between human and ARUbased roadside monitoring.…”

“…ARUs can be programmed to record sounds at predetermined times and over multiple time periods within and among days without the presence of an observer. As a result, ARUs can be deployed in a variety of vegetation types at any time of year, which can increase access in remote regions, e.g., seasonal or winter roads (see Shonfield and Bayne [2017] for an overview of the pros and cons of ARU technology). This new technology can increase data quality and quantity by increasing detection rates of rare species, i.e., irruptive, crepuscular, nocturnal, and less vocal species (Holmes et al 2014), and facilitate estimation of detection probabilities (e.g., Thompson et al 2017).…”

Using occupancy modeling to monitor dates of peak vocal activity for passerines in California

“…We could have achieved a similar increase in precision through additional point counts at each site, but it would have been challenging for us to access each of our survey sites on 3 consecutive mornings. Others have noted the advantages of automated recorders, including limited availability of expert point count observers, synchronization of survey times among sites, and a verifiable record of bird detections (Hobson et al 2002, Rempel et al 2005, Shonfield and Bayne 2017. In our case, we used both methods, which further increased precision by allowing us to sample over a greater diversity of times of the morning.…”

“…Vocalizations are also the primary means by which observers in the field identify birds using standard point counts (Ralph et al 1995) or automated recorders (Shonfield and Bayne 2017). Both techniques have been applied to efficiently survey birds across large geographic areas (McGrann et al 2014, Furnas andCallas 2015).…”