Fig. 1 Acoustic stimuli were generated by random draws from distributions having the experimentally specified nominal call rates and levels of inconsistency. (A) Schematic waveforms showing representative sequences of synthetic calls with the same nominal call rate but different nominal levels of inconsistency (CVw). (B) Distributions illustrating computations of realized call rate and realized inconsistency based on subject response latency. This example illustrates a choice between a standard stimulus [nominal call rate of 11.1 calls per minute (cpm)] and an alternative with a nominal call rate of 2 SDs faster. Each stimulus comprised a sequence of calls created by randomly drawing the instantaneous call rate of the ith call (CRi) from a distribution centered on the nominal call rate and having an SD necessary to produce the nominal level of inconsistency (CVw) for the specified test (here, CVw = 0.500). Also shown are example sequences of calls that a hypothetical subject could have sampled during a two-alternative choice test in the time between being released and making a choice (“response latency”). Only stimulus calls occurring between beginning playback and choice were used to compute realized values for call rate and inconsistency used in analysis and visualization. Equations show how the realized call rate (CRrealized) and inconsistency (CVwrealized) were computed in each test. (C) Realized call rates (cpm) and (D) levels of inconsistency (CVw) in relation to their respective nominal levels across all two-alternative choice tests. Horizontal bars in each distribution depict median values.
Fig. 2 Inconsistent signaling and ambient noise transformed preference functions by degrading preferences for faster call rates. (A) Stochastic differences in realized inconsistency between standard and alternative stimuli had no impact on responses within choice tests. Points depict the probability of choosing the alternative stimulus (0 or 1) in relation to differences in realized inconsistency between the alternative and standard stimuli during trials, which are depicted by the gray probability density function. Positive x values indicate that the alternative was relatively more inconsistent, while negative x values indicate that the standard was relatively more inconsistent. The dashed line shows the probability of choosing at random (0.500), while the dotted line shows the overall probability with which females chose the alternative call across all experiments (0.475). (B to F) Three-dimensional surfaces illustrate how the linear preference for faster call rates measured under optimal conditions (transparent gray surface) became shallower and more curvilinear, indicating degraded female decision-making. The z axes show the probability of choosing the alternative stimulus, whose mean call rate was 0, ±1 SD, or ±2 SD different from the mean call rate of the standard stimulus (11.1 cpm). Preferences measured (B) in quiet as a function of call rate and inconsistency; (C) using perfectly consistent signals in ambient noise as a function of call rate and noise level; (D to F) as a function of call rate and inconsistency in ambient noise presented at sound pressure levels (SPLs) of (D) 60 dB, (E) 70 dB, or (F) 80 dB. Surfaces in (B) to (F) were loess smoothed.
Fig. 3 Increasing response latency improved available information but did not rescue call rate discrimination from degrading with inconsistency. (A) Subjects had longer latencies at higher nominal levels of inconsistency (violin plots: median, black bar; mean, black dot). Mean and median response latencies fell within the 95% confidence intervals around the mean mate assessment time estimated in a previous study (21) (gray shading). Colored points depict the call rate discrepancy (|nominal − realized|) computed as a function of response latency for 935 phonotaxis tests; colored lines and shading show this effect with 95% confidence intervals for each nominal level of inconsistency. Response latency was negatively associated with the discrepancy between nominal and realized call rates, indicating that listening longer before choosing could allow females to gain additional information, leading to better estimates of call rate. (B) Despite improving available information, increasing latency had negative linear (β = −0.002, Wald X2 = 6.67, P = 0.010) and significant quadratic (β = 7.32 × 10−6, Wald X2 = 5.43, P = 0.020) effects on the probability of choosing the faster call rate and thus did not “rescue” preference expression. The colored surface shows the proportion of females choosing the faster call rate as functions of inconsistency and response latency. The gray shaded surface shows the proportion choosing the faster call rate when stimuli were perfectly consistent. The difference between the two surfaces illustrates degraded call rate discrimination that was not rescued by adjusting assessment times. Violin plots reproduced from (A). Surfaces in (B) were loess smoothed.
Fig. 4 Inconsistent signalers produced brief sound bites of high-quality signaling in otherwise low-quality bouts. (A) Inconsistency (CVw) in instantaneous call rate (the inverse of the call period) was inversely related to mean call rate. Points depict mean values measured across 20 calls from each of 50 males (n = 1000 calls). Arrows point to data from three males who called with levels of inconsistency representing the population minimum (blue), maximum (red), and approximate mean (black). The call rates (B) and waveforms of 2 min of continuous signaling (C) for the same three males in (A) illustrate how males with low average call rates (red points, lines) nevertheless produced short call sequences at high rates (sound bites, shaded rectangles), whereas males calling at high average rates (blue points, lines) did so consistently. Vertical dashed lines in (B) depict each male’s mean call rate.
- Table 1 Results from GEE models for the effects of inconsistency (in quiet), ambient noise (with perfectly consistent signals), and the joint effects of inconsistency and ambient noise on the probability of choosing the alternative stimulus.
Modeled effects Parameter Estimate SE Wald X2 P value Inconsistency (in quiet) Intercept −0.763 0.044 301.7 <0.001 Call rate 0.111 0.004 735.4 <0.001 Inconsistency 1.272 0.210 36.9 <0.001 Call rate × inconsistency −0.114 0.019 36.8 <0.001 Ambient noise (with perfectly consistent signals) Intercept −0.711 0.069 106.9 <0.001 Call rate 0.104 0.006 292.2 <0.001 Noise 0.199 0.033 35.7 <0.001 Call rate × noise −0.016 0.003 32.1 <0.001 Inconsistency and ambient noise Intercept −0.864 0.101 73.5 <0.001 Call rate 0.112 0.009 170.5 <0.001 Inconsistency 0.960 0.277 12.0 <0.001 Noise 0.206 0.045 20.8 <0.001 Call rate × inconsistency −0.069 0.020 11.7 <0.001 Call rate × noise −0.017 0.004 22.4 <0.001 Inconsistency × noise −0.004 0.083 0.0 0.963 - Table 2 Results from GEE models for the effects of inconsistency (in quiet) on response latency.
Modeled effect Parameter Estimate SE Wald X2 P value Inconsistency (in quiet) Intercept 86.018 8.106 112.6 <0.001 Call rate 0.022 0.708 0.0 0.975 Inconsistency 125.475 35.434 12.5 <0.001 Call rate × inconsistency −5.915 2.955 4.0 0.045
Supplementary Materials
Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/6/20/eaax3957/DC1
Additional Files
Supplementary Materials
Inconsistent sexual signaling degrades optimal mating decisions in animals
Jessie C. Tanner and Mark A. Bee
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- Figs. S1 and S2
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