Measurement artefacts lead to false positives in the study of birdsong in noise

Abstract

Summary Numerous studies over the past decade have reported correlations between elevated levels of anthropogenic noise and a rise in the minimum frequency of acoustic signals of animals living in noisy habitats. This pattern appears to be occurring globally, and higher pitched signals have been hypothesized to be adaptive changes that reduce masking by low‐frequency traffic noise. However, the sound analysis methods most often used in these studies are prone to measurement errors that can result in false positives. In addition, the commonly used method of measuring frequencies visually from spectrograms might also lead to observer‐expectancy biases that could exacerbate measurement errors. We conducted an experiment to (i) quantify the size and type of errors that result from ‘eye‐balling’ frequency measurements with cursors placed manually on spectrograms of signals recorded in noise and no‐noise conditions, and (ii) to test whether observer expectations lead to significant errors in frequency measurements. We asked 54 volunteers, blind to the true intention of our study, to visually measure the minimum frequency of a variety of natural and synthesized bird sounds, recorded either in noise, or no‐noise conditions. Test subjects were either informed or uninformed about the hypothesized results of the measurements. Our results demonstrate that inappropriate methodology in acoustic analysis can yield false positives with effect sizes as large, or even larger, than those reported in published studies. In addition to these measurement artefacts, psychological observer biases also led to false positives – when observers expected signals to have higher minimum frequencies in noise, they measured significantly higher minimum frequencies than uninformed observers, who had not been primed with any expectation. The use of improper analysis methods in bioacoustics can lead to the publication of spurious results. We discuss alternative methods that yield unbiased frequency measures and we caution that it is imperative for researchers to familiarize themselves both with the functions and limitations of their sound analysis programmes. In addition, observer‐expectancy biases are a potential source of error not only in the field of bioacoustics, but in any situation where measurements can be influenced by human subjectivity.

Aircraft sound exposure leads to song frequency decline and elevated aggression in wild chiffchaffs

“…Recordings were made in between aircraft movements, when ambient sound levels were comparable to those at control sites. It is possible that chiffchaffs do increase the frequency of their songs during aircraft movements, but this was impossible to measure as the aircraft noise precluded spectral measurements in our recordings (Brumm et al, 2017;Verzijden et al, 2010).…”

Weather conditions determine attenuation and speed of sound: Environmental limitations for monitoring and analyzing bat echolocation

“…Beyond academic research, these data are used for risk assessment (e.g., at wind turbines; e.g., Newson et al, 2017), to infer population density, diversity, and vulnerability of bats (Clement, Rodhouse, Ormsbee, Szewczak, & Nichols, 2014;Meyer et al, 2011), and to inform risk mitigation and conservation strategies (Meyer, 2015), often based on automatic call analysis software (Russo & Voigt, 2016;Rydell, Nyman, Eklöf, Jones, & Russo, 2017). While these acoustic methods became increasingly easier, faster and more powerful, many biological, environmental, and technical factors lead to variation, if not errors, in the results (Adams, Jantzen, Hamilton, & Fenton, 2012;Brumm, Zollinger, Niemela, & Sprau, 2017;Rydell et al, 2017;Zollinger, Podos, Nemeth, Goller, & Brumm, 2012). Understanding these factors is therefore paramount for correct bioacoustic measurements.…”

Asymmetrical interspecific communication of predatory threat in mixed‐species colonies of lesser kestrels (Falco naumanni) and jackdaws (Corvus monedula)

“…Note that this differs from what would conventionally be considered the overall bandwidth of a call, which, by definition, would capture the range from the minimum to maximum detectable frequency. Fortunately, selection of just those calls with the highest signal‐to‐noise ratio for analysis rendered the placement of the cursor unambiguous in obtaining spectrographic measures, thus minimizing measurement errors implicit in manual spectrographic coding (Brumm, Zollinger, Niemelä, & Sprau, ). Further, blind coding eliminated any bias in measuring spectrographic properties of the calls (Brumm et al, ), as did the imposition of a threshold relative sound pressure level in measuring the power bandwidth of lesser kestrel calls.…”