The figure at left illustrates the theoretical maximum distance that one song sparrow can detect the song of another bird in this species. The dependent variables represented here are different source intensities, assuming an excess attenuation of 5 dB/100 m. Background noise level is given as overall SPL (C-weighted), spectrum level (per cycle energy distribution over the entire band of noise), and the amount of masking assuming a critical ratio of 26 dB (as measured in the laboratory). We know from laboratory studies that the threshold in the quiet for a 2 kHz pure tone is about 0 dB SPL for song sparrows. Critical ratio data for this species shows that background noise levels must be at least 26 dB below the power in a 2 kHz pure tone in order for the tone to be detected by song sparrows (Okanoya & Dooling 1988, 1990). Thus, for a noise spectrum level (energy per Hertz) of -26 dB, masked threshold is the same as absolute threshold in the quiet, and no masking occurs. If the spectrum level of the background noise is 0 dB SPL, however, the threshold of the signal is raised to 26 dB SPL, causing 26 dB of masking. The spectrum level of the background noise can be calculated from the overall sound pressure level, and depends on the bandwidth and distribution of the noise. For a typical sound level meter reading of noise in the frequency band 0 - 10 kHz, an overall SPL of 40 dB is equivalent to a spectrum level of about 0 dB if the noise is flat.
 
 

These kinds of masking studies are very relevant to the ecology of birds. It is important to understand that intense traffic or aircraft noise probably represents a substantial risk to normal acoustic communication in birds. It is not practical to think of eliminating the detrimental effects on communication completely. It is practical, however, to try and quantify the risks so that intelligent judgments can be made concerning the extent to which noise may interfere with the normal behavior and breeding biology of birds in the wild, and reasonable arguments can be made about how much risk is acceptable. At present, predictions made for detection of vocalizations in the environment only address the simplest case, the ability of a bird to tell whether a sound occurred (i.e. detection). Such a measure does not reflect a bird's ability to communicate effectively in a particular acoustic environment, and may have little bearing on it. Consider the case of human speech communication as an example. It is one thing to hear a voice, and it is quite another to understand what is said. For humans, the ability to discriminate one speech sound from another requires a higher signal-to-noise ratio than simply detecting a speech sound. Identification, or the ability to recognize a specific, biologically relevant signal, may require even higher signal-to-noise ratios. We need equivalent data for birds in order to understand communication in noise.

At the present time, these worthwhile environmental projects are not funded. The ultimate goal of these studies is to generate a predictive model for evaluating the impact of noise on acoustic communication in birds in order save endangered species. Future studies will examine not only whether birds are capable of detecting a signal in noise, but are also whether they are able to discriminate or identify relevant sounds such as vocalizations. To do this, several different kinds of tests must be performed in the laboratory with vocalizations and anthropogenic (human made) noises such as traffic noises of different levels. These data, combined with measurements from the field, will allow us to better apply our predictions to specific cases, and estimate relevant distances on territory maps for individuals of particular species and in specific habitats. If you are interested in supporting this environmental research effort, please contact Dr. Robert Dooling.