Supplementary Figure 12: Temporal alignment of backpack records

(a) Drifts of internal clocks on three loggers are shown by blue, green and magenta lines relatively to the fourth logger taken as a reference (turquoise horizontal line). Drift was measured by comparing patterns of IR pulses stored on loggers. A Labview program monitored sound recorded with a wall-attached microphone, every 4 ms it assessed whether a song was present, in which case a 0.8-ms IR pulse was sent to the loggers for synchronization. Temporal drift was always linear except in one logger (shown in green) in which a couple of sudden interruptions were observed for a dozen of milliseconds (black arrows). Logger records were aligned by zeroing the lines: we stretched or compressed the records by adding (linear interpolation) or removing data points. (b) Shown are residuals after linear regression of clock drift curves in a (because of the two interruptions we performed linear regression on 3 segments in logger 3). Most of the time residuals did not exceed 1 ms. Only during the first 0.5 h residuals were relatively large (< 3 ms) because of low density of IR pulses caused by infrequent singing. More frequent emission of randomized IR pulse sequences could eliminate this problem. The root-mean-square deviation was 0.46 ms for the whole record and 0.25 ms after omission of the first 0.5 h. (c) Drifts of internal clocks like in a but measured by temporal matching of sound envelopes recorded with the logger microphones. See Online Methods for details. (d) Residuals of sound-based synchronization similar to b. The root-mean-square deviation was 0.37 ms for the entire record and 0.35 ms after omission of the first 0.5 h. Thus, synchronization based on sound works as well as synchronization based on IR pulses and may be useful outdoors where IR synchronization can be difficult.