Acoustic accelerometer transmitters and their growing relevance to aquatic science

Swimming through sand: using accelerometers to observe the cryptic, pre-emergence life-stage of sea turtle hatchlings

Animals that hatch within a subterranean nest, such as turtle hatchlings, expend some of their limited energy reserves digging out through sand or soil to reach the surface. In sea turtles, this emergence process can take the hatchlings 3-7 days. However, we have a poor understanding of this process as it is difficult to observe what is occurring underground. Here, we utilize a novel method to characterize digging-out behaviour: affixing an accelerometer directly to newly hatched green turtles (Chelonia mydas) to record movement until nest emergence. Our data revealed that buried hatchlings maintained a head-up orientation but did not move in the expected left and right swaying motion associated with alternating limb crawling. Rather, they moved using dorsal-ventral heaving and pitching as if swimming vertically through the sand to the surface. Movement activity was irregular and brief, interspersed by many short periods of inactivity, mostly lasting less than 10 min. The first 24 h of head-up activity displayed no diel patterns, but the last 24 h prior to emergence involved more intense movement during night-time hours compared with daytime hours. Thus, our results add valuable new insight, and in some cases change previous assumptions, regarding the digging behaviours during the egg-to-emergence life stage in sea turtles.

Calibrating acceleration transmitters to quantify the seasonal energetic costs of activity in lake trout

Bioenergetics models are powerful tools used to address a range of questions in fish biology. However, these models are rarely informed by free-swimming activity data, introducing error. To quantify the costs of activity in free-swimming fish, calibrations produced from standardized laboratory trials can be applied to estimate energy expenditure from sensor data for specific tags and species. Using swim tunnel respirometry, we calibrated acceleration sensor-equipped transmitting tags to estimate the aerobic metabolic rates (ṀO2) of lake trout (Salvelinus namaycush) at three environmentally relevant temperatures. Aerobic and swim performance were also assessed. Like other calibrations, we found strong relationships between ṀO2 and acceleration or swimming speed, and jackknife validations and data simulations suggest that our models accurately predict metabolic costs of activity in adult lake trout (~5% algebraic error and ~20% absolute error). Aerobic and swim performance metrics were similar to those reported in other studies, but their critical swimming speed was lower than expected. Additionally, lake trout exhibited a wide aerobic scope, suggesting that the avoidance of waters ≥15°C may be related to selection for optimal growing temperatures. The ability to quantify the free-swimming energetic costs of activity will advance our understanding of lake trout ecology and may yield improvements to bioenergetics model.

TrackdAT, an acoustic telemetry metadata dataset to support aquatic animal tracking research

Data on the movement and space use of aquatic animals are crucial to understand complex interactions among biotic and abiotic components of ecosystems and facilitate effective conservation and management. Acoustic telemetry (AT) is a leading method for studying the movement ecology of aquatic animals worldwide, yet the ability to efficiently access study information from AT research is currently lacking, limiting advancements in its application. Here, we describe TrackdAT, an open-source metadata dataset where AT research parameters are catalogued to provide scientists, managers, and other stakeholders with the ability to efficiently identify and evaluate existing peer-reviewed research. Extracted metadata encompasses key information about biological and technical aspects of research, providing a comprehensive summary of existing AT research. TrackdAT currently hosts information from 2,412 journal articles published from 1969 to 2022 spanning 614 species and 380,289 tagged animals. TrackdAT has the potential to enable regional and global mobilization of knowledge, increased opportunities for collaboration, greater stakeholder engagement, and optimization of future ecological research.