Effects of ambient noise on detectability and localization of avian songs and tones by observers in grasslands

Abstract

Probability of detection and accuracy of distance estimates in aural avian surveys may be affected by the presence of anthropogenic noise, and this may lead to inaccurate evaluations of the effects of noisy infrastructure on wildlife. We used arrays of speakers broadcasting recordings of grassland bird songs and pure tones to assess the probability of detection, and localization accuracy, by observers at sites with and without noisy oil and gas infrastructure in south‐central Alberta from 2012 to 2014. Probability of detection varied with species and with speaker distance from transect line, but there were few effects of noisy infrastructure. Accuracy of distance estimates for songs and tones decreased as distance to observer increased, and distance estimation error was higher for tones at sites with infrastructure noise. Our results suggest that quiet to moderately loud anthropogenic noise may not mask detection of bird songs; however, errors in distance estimates during aural surveys may lead to inaccurate estimates of avian densities calculated using distance sampling. We recommend caution when applying distance sampling if most birds are unseen, and where ambient noise varies among treatments.

Managing urban and rural rights-of-way as potential habitats for grassland birds

“…This is consistent with several previous studies that found little effect of industrial or road noise on detectability of grassland birds (Koper et al 2015, Lituma andBuehler 2016). The lack of a distance effect may be because our transects were relatively narrow, so that all birds in potential grassland habitat were close enough not to be masked by traffic noise (e.g., see also Koper et al 2015). It is possible that the Clay-colored Sparrow and Savannah Sparrow we analyzed sang at frequencies high enough and amplitudes loud enough not to be masked by traffic (Brumm 2004, Nemeth et al 2013; perhaps this explanation could be tested in future studies using portable acoustic recorders to measure traffic volume and bird song amplitudes and frequencies from recordings (Shonfield and Bayne 2017).…”

“…Nevertheless, hierarchical distance sampling and multiseason occupancy models can be used in combination: urban ROWs are usually narrow, linear habitats within which birds using these habitats are never too far from observers along a transect. Within short distances of observers, the detection probability of grassland birds given their availability may not significantly decline even within noisy environments (Koper et al 2015). If hierarchical distance-sampling methods do not indicate a strong effect of urban noise on the detection of birds within surveys, then multiseason occupancy models can be used to predict the probability of grassland birds using urban ROWs over multiple seasons.…”

Microphone variability and degradation: implications for monitoring programs employing autonomous recording units

“…Past research suggests that wind affects detection of calls in ARU surveys more severely than in-person surveys (Digby et al 2013), and it is possible we did not experience the true effect wind has on recordings because our experimental design did not include wind gusts, which would tend to cause recordings to "clip" (Zakis 2011) and further affect detection. Additionally, white noise may not have been ideal to represent sound produced by wind in open habitats, where greater environmental noise can occur at lower frequencies (Zakis 2011), thereby masking only portions of a call and not affecting detection as severely (Koper et al 2015). However, our use of white noise was likely appropriate to simulate the interference caused by leaf rustle in deciduous forests and likely dense cattail vegetation, which tend to follow a similar sound profile (Turnbull, personal commuication).…”

What you find depends on where you look: responses to proximate habitat vary with landscape context

“…We used this conservative distance to reduce variation in detectability: although detection varies among species and habitat types, especially at distances of 100 m or more (Matsuoka et al 2012), detections do not tend to decline appreciably within 50 m , Koper et al 2016, and previous studies have found that a 50 m distance provides reliable data for a broad range of species in wooded as well as open habitats (Matsuoka et al 2012). Studies of auditoryonly detections have shown that detection distances are subject to error ), especially in windy or noisy conditions (Koper et al 2016). To reduce these risks, we sampled only in weather conditions with little wind and no rain; other noise sources were minimal.…”