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Spatio-Temporal Dynamics in Collective Frog Choruses Examined by Mathematical Modeling and Field Observations

View Article: PubMed Central - PubMed

ABSTRACT

This paper reports theoretical and experimental studies on spatio-temporal dynamics in the choruses of male Japanese tree frogs. First, we theoretically model their calling times and positions as a system of coupled mobile oscillators. Numerical simulation of the model as well as calculation of the order parameters show that the spatio-temporal dynamics exhibits bistability between two-cluster antisynchronization and wavy antisynchronization, by assuming that the frogs are attracted to the edge of a simple circular breeding site. Second, we change the shape of the breeding site from the circle to rectangles including a straight line, and evaluate the stability of two-cluster and wavy antisynchronization. Numerical simulation shows that two-cluster antisynchronization is more frequently observed than wavy antisynchronization. Finally, we recorded frog choruses at an actual paddy field using our sound-imaging method. Analysis of the video demonstrated a consistent result with the aforementioned simulation: namely, two-cluster antisynchronization was more frequently realized.

No MeSH data available.


Field research on frog choruses, by using our sound-imaging method14.(A) A photograph of a male Japanese tree frog (Hyla japonica). (B) A photograph of our sound-imaging device Firefly. The Firefly unit consists of a microphone and a light emitting diode (LED) that is illuminated when capturing nearby sounds14. (C) A photograph of a paddy field in Japan. Along one edge of this paddy field, we deployed 85 or 86 sound-imaging devices at intervals of 40 cm. As shown here, an index was attached to each device from one end of the edge, which was closer to the camera, to the other end. The spatio-temporal light pattern of these devices was recorded by a video camera. Note that the lights of some devices were not detected, when those devices were deployed far from the camera and were not illuminated by frog calls. We carefully checked all the data, and confirmed that the lights of at least 40 devices close to the camera were stably captured even when those were not strongly illuminated by frog calls. Hence, we used the light patterns of 40 devices close to the camera for data analysis of all the observations. These photographs were taken by I.A. and H.G.O.
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f6: Field research on frog choruses, by using our sound-imaging method14.(A) A photograph of a male Japanese tree frog (Hyla japonica). (B) A photograph of our sound-imaging device Firefly. The Firefly unit consists of a microphone and a light emitting diode (LED) that is illuminated when capturing nearby sounds14. (C) A photograph of a paddy field in Japan. Along one edge of this paddy field, we deployed 85 or 86 sound-imaging devices at intervals of 40 cm. As shown here, an index was attached to each device from one end of the edge, which was closer to the camera, to the other end. The spatio-temporal light pattern of these devices was recorded by a video camera. Note that the lights of some devices were not detected, when those devices were deployed far from the camera and were not illuminated by frog calls. We carefully checked all the data, and confirmed that the lights of at least 40 devices close to the camera were stably captured even when those were not strongly illuminated by frog calls. Hence, we used the light patterns of 40 devices close to the camera for data analysis of all the observations. These photographs were taken by I.A. and H.G.O.

Mentions: Figure 7A shows the time series data of the light pattern of sound-imaging devices14 deployed at an actual paddy field (see Methods and Fig. 6), capturing the chorus structures of male Japanese tree frogs. The colored plots represent the light intensity of each device, which has been calculated by subtracting the average light intensity of each device that can slightly vary depending on its tuning14; an index is attached to each device from one end of the edge, which is closer to the camera, to the other end (Fig. 6C). The device nearest to each calling frog was estimated every 15 sec, by analyzing the summation of the light intensity of the deployed devices: namely, if the summation at one device exhibited a local peak and exceeded a threshold, the device was determined to be nearest to one calling frog. Through this analysis, the threshold was set as 3 × 29.97 fps (frames per second) × 15 sec. To estimate the calling times of each frog, the light pattern of the device nearest to each calling frog was then analyzed: namely, when the light pattern of the device exceeded a threshold, the corresponding times were detected as the calling times of the frog (see supplemental materials of the reference 6). In this analysis, 50% of the maximum light intensity of respective devices was used as a threshold value.


Spatio-Temporal Dynamics in Collective Frog Choruses Examined by Mathematical Modeling and Field Observations
Field research on frog choruses, by using our sound-imaging method14.(A) A photograph of a male Japanese tree frog (Hyla japonica). (B) A photograph of our sound-imaging device Firefly. The Firefly unit consists of a microphone and a light emitting diode (LED) that is illuminated when capturing nearby sounds14. (C) A photograph of a paddy field in Japan. Along one edge of this paddy field, we deployed 85 or 86 sound-imaging devices at intervals of 40 cm. As shown here, an index was attached to each device from one end of the edge, which was closer to the camera, to the other end. The spatio-temporal light pattern of these devices was recorded by a video camera. Note that the lights of some devices were not detected, when those devices were deployed far from the camera and were not illuminated by frog calls. We carefully checked all the data, and confirmed that the lights of at least 40 devices close to the camera were stably captured even when those were not strongly illuminated by frog calls. Hence, we used the light patterns of 40 devices close to the camera for data analysis of all the observations. These photographs were taken by I.A. and H.G.O.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5384602&req=5

f6: Field research on frog choruses, by using our sound-imaging method14.(A) A photograph of a male Japanese tree frog (Hyla japonica). (B) A photograph of our sound-imaging device Firefly. The Firefly unit consists of a microphone and a light emitting diode (LED) that is illuminated when capturing nearby sounds14. (C) A photograph of a paddy field in Japan. Along one edge of this paddy field, we deployed 85 or 86 sound-imaging devices at intervals of 40 cm. As shown here, an index was attached to each device from one end of the edge, which was closer to the camera, to the other end. The spatio-temporal light pattern of these devices was recorded by a video camera. Note that the lights of some devices were not detected, when those devices were deployed far from the camera and were not illuminated by frog calls. We carefully checked all the data, and confirmed that the lights of at least 40 devices close to the camera were stably captured even when those were not strongly illuminated by frog calls. Hence, we used the light patterns of 40 devices close to the camera for data analysis of all the observations. These photographs were taken by I.A. and H.G.O.
Mentions: Figure 7A shows the time series data of the light pattern of sound-imaging devices14 deployed at an actual paddy field (see Methods and Fig. 6), capturing the chorus structures of male Japanese tree frogs. The colored plots represent the light intensity of each device, which has been calculated by subtracting the average light intensity of each device that can slightly vary depending on its tuning14; an index is attached to each device from one end of the edge, which is closer to the camera, to the other end (Fig. 6C). The device nearest to each calling frog was estimated every 15 sec, by analyzing the summation of the light intensity of the deployed devices: namely, if the summation at one device exhibited a local peak and exceeded a threshold, the device was determined to be nearest to one calling frog. Through this analysis, the threshold was set as 3 × 29.97 fps (frames per second) × 15 sec. To estimate the calling times of each frog, the light pattern of the device nearest to each calling frog was then analyzed: namely, when the light pattern of the device exceeded a threshold, the corresponding times were detected as the calling times of the frog (see supplemental materials of the reference 6). In this analysis, 50% of the maximum light intensity of respective devices was used as a threshold value.

View Article: PubMed Central - PubMed

ABSTRACT

This paper reports theoretical and experimental studies on spatio-temporal dynamics in the choruses of male Japanese tree frogs. First, we theoretically model their calling times and positions as a system of coupled mobile oscillators. Numerical simulation of the model as well as calculation of the order parameters show that the spatio-temporal dynamics exhibits bistability between two-cluster antisynchronization and wavy antisynchronization, by assuming that the frogs are attracted to the edge of a simple circular breeding site. Second, we change the shape of the breeding site from the circle to rectangles including a straight line, and evaluate the stability of two-cluster and wavy antisynchronization. Numerical simulation shows that two-cluster antisynchronization is more frequently observed than wavy antisynchronization. Finally, we recorded frog choruses at an actual paddy field using our sound-imaging method. Analysis of the video demonstrated a consistent result with the aforementioned simulation: namely, two-cluster antisynchronization was more frequently realized.

No MeSH data available.