Bringing data to the surface: recovering data loggers for large sample sizes from marine vertebrates. Issue 1 (December 2016) - Lear, Karissa; Whitney, Nicholas
Abstract Background Despite the utility of data loggers for studying the fine-scale behavior and energetics of marine organisms, most studies using these tools have had relatively low sample sizes due to various factors including the logistical difficulty of physically recovering the loggers. Here, we report a simple methodology for recovering large numbers of data loggers over a broad search area, which has proven successful even for large, itinerant marine species. Techniques described include the use of VHF telemetry, a high-speed search vessel, GPS, and custom maps of the search area in order to record logger float package locations and optimize recovery strategy. Results We have deployed data logger packages on 193 sharks of 8 different species in the Gulf of Mexico, with a recovery rate of 97.4 %, retrieving 188 of the loggers with a total of over 4260 h of fine-scale acceleration data. Lost float packages are likely due to scavenging of sharks that succumbed to post-release mortality and ingestion of the packages by larger sharks. Mean (±SD) deployment time for the packages was 22.9 ± 22.5 h (range 0.7–205 h), and mean overall displacement distance was 31.3 ± 28.2 km (range 0.62–231 km). Animals showed a tendency to swim offshore after tagging, with 75 % of packages recovered at a bearing between 180° and 290° relative to their tagging location. Sharks swam to deeper water after tagging, with maximum depths reaching an average of 11 ± 8 m greater at the end of the track versus the start. Due to the high recovery rate and the reusability of these data loggers, we have successfully documented the post-release outcome of 188 sharks at a cost of approximately 535 per shark, compared to a cost of 4200 per shark to have done the same work with satellite tags. Conclusions Given the high recovery rate and the cost-effectiveness of these tags, our results illustrate clear advantages in cost and data quality of this method compared to studies using conventional satellite tags.