Trade-offs in telemetry tag programming for deep-diving cetaceans: data longevity, resolution, and continuity

Abstract

BackgroundAnimal-borne telemetry instruments (tags) have greatly advanced our understanding of species that are challenging to observe. Recently, non-recoverable instruments attached to cetaceans have increased in use, but these devices have limitations in data transmission bandwidth. We analyze trade-offs in the longevity, resolution, and continuity of data records from non-recoverable satellite-linked tags on deep-diving Ziphius cavirostris in the context of a behavioral response study of acute noise exposure. We present a strategic data collection programming scheme that balances resolution and continuity against longevity to address specific questions about the behavioral responses of animals to noise exposure in experimental contexts. We compare accuracy and precision between two programming regimes on a commercially available satellite-linked tag: (1) dive behavior summary defined by conductivity thresholds and (2) depth time-series at various temporal resolutions.ResultsWe found that time-series data could faithfully replicate the more precisely defined dives from a dive summary record data stream to an acceptable error range for our application. We determined a 5-minute time-series data stream collected for 14 days balanced resolution with longevity, achieving complete or nearly complete diving records in 6 out of 8 deployments. We increased our data reception rate several fold by employing a boat based data capture system. Finally, a tag deployed in a group concurrently with a high resolution depth recorder showed high depth concordance.ConclusionsWe present the conceptual framework and iterative process for matching telemetry tag programming to research questions that we used and which should be applicable to a wide range of studies. Although designing new hardware for our specific questions was not feasible at the time, we were able to optimize the sampling regime of a commercially available instrument to meet the needs of our research questions and proposed analyses. Nevertheless, for other study species or designs, the complicated intersection between animal behavior and bandwidth of telemetry systems can often create a severe mismatch among research questions, data collection, and analysis tools. More flexible programming and purpose built instruments will increase the efficacy of these studies and increase the scientific yield relative to the inherently higher risk of invasive studies.

Deep diving by offshore bottlenose dolphins (Tursiops spp.)

“…Transmitted tag data were inspected to assess potential transducer failures or drifts that may have influenced dive depth recordings and for the presence of data gaps in the tag records (i.e, data validation). Specifically, the depth and zero depth offset information reported on the status files of each dolphin's tag was examined for extreme values as these have been reported to be indicative of possible transducer failure in other species (e.g., Cuvier's beaked whales; short‐finned pilot whales, Globicephala macrorhynchus ; Baird et al, 2019; Cioffi et al, 2022). In these files the depth is the last depth reading recorded before the tag transmitted data, while the zero‐depth offset value is the amount of offset that the tag is applying to the depth sensor readings if this feature is enabled on the tag (Wildlife Computers, Redmond, WA).…”

“…In these files the depth is the last depth reading recorded before the tag transmitted data, while the zero‐depth offset value is the amount of offset that the tag is applying to the depth sensor readings if this feature is enabled on the tag (Wildlife Computers, Redmond, WA). We followed definitions outlined by Baird et al (2019), which considered cases where more than one depth value in the status record exceeded ±10 m as indicative of potential transducer failure issue, and Cioffi et al (2022), which defined unacceptably high pressure transducer drift as two or more consecutive absolute value zero depth readings >10 m, when assessing data records for possible failures or drifts. Data gaps were defined as any two consecutive records with more than 0 s missing between the end of dive i and the start of dive i + 1.…”