Minimizing errors in the analysis of dive recordings from shallow-diving animals

Knowledge of the diving behaviour of aquatic animals expanded considerably with the invention of time–depth recorders (TDRs) in the 1960s. The large volume of data acquired from TDRs can be analyzed using dive analysis software, however, the application of the software has received relatively little attention. We present an empirical procedure to select optimum values that are critical to obtaining reliable results: the zero-offset correction (ZOC) and the dive threshold. We used dive data from shallow-diving coastal dugongs (Dugong dugon) and visual observations from an independent study to develop and test a procedure that minimizes errors in characterizing dives. We initially corrected the surface level using custom software. We then determined the optimum values for each parameter by classifying dives identified by an open-source dive analysis software into Plausible and Implausible dives based on the duration of dives. The Plausible dives were further classified as Unrecognized dives if they were not identified by the software but were of realistic dive duration. The comparison of these dive types indicated that a ZOC of 1 m and a dive threshold of 0.75 m were the optimum values for our dugong data as they gave the largest number of Plausible dives and smaller numbers of other dive types. Frequency distributions of dive durations from TDRs and independent visual observations supported the selection. Our procedure could be applied to other shallow-diving animals such as coastal dolphins and turtles.

Research Highlights
► Raw dive data contain a range of noise.
► Dive data requires empirical-based determination of parameter values for dive identification.
► We established the time threshold and used different parameter values to identify appropriate values.
► We found a 1 m ZOC and a 0.75 m dive threshold appropriate for dugongs.
► The work has application to shallow-diving animals.