Toward a general model for the evolution of the auditory sensitivity under variable ambient noise conditions

Ambient noise constrains the evolution of acoustic signals and hearing. An earlier fitness model showed that the trade-off between sound detection and recognition helps predict the best level of auditory sensitivity for acoustic communication in noise. Here, the early model is improved to investigate the effects of different noise masking conditions and signal-to-noise ratios (SNRs). It is revealed that low sensitivity is expected for acoustic communication over short distances in complex noisy environments provided missed sound recognition is costly. By contrast, high sensitivity is expected for acoustic communication over long distances in quieter habitats or when sounds are received with good SNRs under unfavorable noise conditions. High sensitivity is also expected in noisy environments characterized by one dominant source of noise with a fairly constant spectrum (running-water noise) or when sounds are processed using anti-masking strategies favoring the detection and recognition of sound embedded in noise. These predictions help explain unexpected findings that do not fit with the current view on the effects of environmental selection on signal and sensitivity. Model predictions are compared with those of models of signal detection in noisy conditions and results of empirical studies.