The previous blog introduced us to the difficulties penguins face when trying to find their mates amongst their crowded colony. As a reminder:
A bird returning from the ocean [. . .] goes back to the breeding area and then calls its mate using the mutual display call. The partner, incubating the egg or rearing the chick, responds and thus gives its identity and its exact position in the colony. After a few calls, the two individuals are able to find each other. [. . .] Colonial life requires that vocal recognition occurs in the continuous background noise of the colony (Lengagne et al., 1999).
The above research was conducted during dry, calm weather. However, the natural conditions are hardly so. Instead, penguins spend much of their lives trying to survive in windy, arctic conditions and are continuously subjected to the influence of strong polar wind streams. Lengagne, Aubin, Lauga, and Jouventin have continued their research to look at if penguins have adopted some sort of adaptation to account for varying weather conditions, and if so, how they accomplish such a feat.
They propose that penguins take advantage of the mathematical theory of communication as follows. The volume of information (V) contained in a produced signal is equal to the signals frequency (F), times the signal duration (T), times the log of one plus signal to noise ratio (g=log2(1+S/N)) such that V=FTg. Because windy conditions decrease the amount of volume information transmitted by decreasing the signal to noise ratio, the producing signal must be modified to counteract such degradation. It is assumed that penguins are already emitting signals at their maximum amplitude and therefore cannot directly increase their signal to noise ratio. Instead, it is hypothesized that penguins increase their signal duration (T) in two ways, “birds can extend the duration of the mutual display call or enhance the emission rate of the call” (Lengagne et al., 1999).
To conduct such a study, Lengagne et al. observed 30 mating pairs amongst a colony consisting of 40,000 penguin pairs.
First, Lengagne et al. “analyzed the modification of the spectral composition of the ambient noise of the colony versus wind speed” through three frequency bands:
0-350 Hz corresponded to physical noise (such as wind),
350-2000 Hz corresponded to calls of birds,
2000-8000 Hz corresponded to the remaining noise of the colony (Lengagne et al., 1999).
They measured the percentage of the total energy in each category (taken from the middle of the colony) via Welch’s method of 80-second recordings. The independent variable was presence of wind such that analyses were made in conditions with no wind and conditions with a wind speed of 11 meters per second.
Secondly, the entropy of broadcast calls was computed in the following three conditions. Control conditions were taken as trails where wind speeds were 5 meters per second or less. Accelerated wind conditions were taken as trials where wind speeds were 11 meters per second. These high-speed conditions were studied in two ways: with the direction of the wind favorable to the transmittance of calls or with the direction of the wind opposing the transmittance of the calls. In this part of the experiment, Lengagne et al. were interested in the “emergence of the penguin’s signal over the background noise (colony+wind) [. . .] measured by computing the entropy of the distribution of its energy” via a calculation proposed by Beecher in 1988 (Lengagne et al., 1999).
Thirdly, Lengagne et al. measured the number of syllables and call durations in six different categories: 5, 6, 7, 8, 9, and 11 meters per second, all at a direction opposing propagation.
Fourthly, the number of calls emitted by the returning penguins was observed in the same categories discussed in the second part of their experiment.
And lastly, Lengagne et al. used the time duration required for change-over as a means to assess the wind-cost for penguins.
Quantitatively, they found that for windy conditions, 23.8% additional energy corresponded to physical noises such as wind (which intuitively makes sense) and the distribution of energy corresponding to the calls of penguins and noises from the colony decreased.
From the second part of their experiment, Lengagne et al. found that the aforementioned observations had correlations with the amount of entropy of the broadcast calls. Downwind conditions are correlated to wind direction favorable to the signal propagation while upwind conditions are correlated to wind direction against signal propagation. As noted in the caption, “a value near 1 characterize[d] a signal almost lost in the background noise” (Lengagne et al., 1999). It can be seen that in windy situations with the wind going against signal propagation, most of the signal is lost due to the background noise (again, agreeing with intuition).
When looking at the number of syllables and call duration, the “two separate models are in surprisingly good agreement with the values of their respective wind speed threshold, W,” duration of call being 7.70 meters per second and 7.52 meters per second for number of syllables (Lengagne et al., 1999). Above those two thresholds, the data fits a linear graph with positive slopes as follows:
In the fourth part of their research, they found that in the upwind condition, the number of calls emitted by both the returning and the brooding penguins were 11.6 calls, which exceeded that of the downwind condition (7.7 calls) and that of lack of wind (5.3 calls) with statistical significance.
To quantitatively show the cost of windy environments, Lengagne et al. showed that when graphing the duration of change-over versus wind speed, the difference between the slopes of the regression lines were statistically significant “showing that the time necessary for change-over was more important in windy situations than without wind” (Lengagne et al., 1999).
The data found by Lengagne et al. shows that the modality of emission of penguin calls changes as wind speed increases. Wind increases the environmental ambient noise which affects both the amount of information transmitted and the distance over which the information is transmitted such that an increase in background noise leads to a diminution of the signal to noise ratio. Sometimes, the “attenuation becomes so strong, the signal disappears” (Lengagne et al., 1999). In order to account for such attenuation and increase the success of their signals, penguins increase their call duration and enhance the number of syllables within each call. Overall, the total number of calls between the mates increases as well. These results are linked to an increase in the “redundancy process” where, “by repeating the same information many times, the birds may increase the probability of communicating during a short-window during which the wind speed suddenly drops” (Lengagne et al., 1999). In other words, an increased redundancy in penguin signaling increases the probability of receiving the intended message. Such an acoustic adaption supports the finding that the animal adjusts its behavior in response to wind noise, at least in the temporary sense. The penguin “adapts in some manner to wind speed and wind direction or noise generated by the wind or indirectly some other parameters linked to the wind modifying the number of syllables that must be emitted” (Lengagne et al., 1999). It is fascinating to see how communication is not static, but a dynamic process that take into consideration many inputs at the current situation. Communication, therefore, is not just an output system that is straight forward. It’s sensitive to many variables such that the efficiency of communication can be enhanced.
Lengagne, T., Aubin, T., Lauga, J., & Jouventin, P. (1999). How do king penguins (Aptenodytes patagonicus apply the mathematical theory of information to communicate in windy conditions?. Proceedings of the Royal Society of London. Series B: Biological Sciences, 266(1429), 1623-1628.