Design and fabrication of a stereo-video camera equipped unoccupied aerial vehicle for measuring sea turtles, sharks, and other marine fauna.

The recent commercialization of unoccupied aerial vehicles (UAVs) has facilitated their incorporation into a variety of ecological studies. While UAVs are able to provide accurate visual data of marine species from an aerial perspective, these devices have some limitations that make measuring marine animals below the surface challenging. Many marine organisms are often visible from the air, but are deeper in the water column, and current methods cannot measure animals below the surface. Here, we developed and tested a stereo-video camera (SVC) system that was mounted onto a commercially-available UAV. We used the SVC-UAV to conduct remote body-size measurements for two marine species: the green sea turtle (Chelonia mydas) and the nurse shark (Ginglymostoma cirratum). When comparing SVC measurements to those taken by hand, the SVC-UAV had a mean absolute error (MAE) of 4.44 cm (n = 6; mean percent error (MPE) = 10.6%) for green sea turtles and 7.16 cm absolute error (n = 1; PE = 3.6%) for the nurse shark. Using a linear model, we estimated the slope of the SVC versus hand measurements for green sea turtles to be 1.085 (±0.099 SE), and accounting for the standard error, a measurement bias was not apparent. Using model selection, based on a global model predicting MAE from animal distance to the SVC and body size, the top ranked model was the intercept-only model. This indicates that neither animal distance nor body size strongly influenced measurement error. Incorporating SVC systems into UAVs can allow for relatively accurate measurements of near surface-dwelling marine species. To our knowledge, there is no other stand-alone SVC for UAVs available that offers similar accuracy and utility.

Validating the use of stereo-video cameras to conduct remote measurements of sea turtles.

Point 1: Stereo-video camera systems (SVCSs) are a promising tool to remotely measure body size of wild animals without the need for animal handling. Here, we assessed the accuracy of SVCSs for measuring straight carapace length (SCL) of sea turtles. Point 2: To achieve this, we hand captured and measured 63 juvenile, subadult, and adult sea turtles across three species: greens, Chelonia mydas (n = 52); loggerheads, Caretta caretta (n = 8); and Kemp's ridley, Lepidochelys kempii (n = 3) in the waters off Eleuthera, The Bahamas and Crystal River, Florida, USA, between May and November 2019. Upon release, we filmed these individuals with the SVCS. We performed photogrammetric analysis to extract stereo SCL measurements (eSCL), which were then compared to the (manual) capture measurements (mSCL). Point 3: mSCL ranged from 25.9 to 89.2 cm, while eSCL ranged from 24.7 to 91.4 cm. Mean percent bias of eSCL ranged from -0.61% (±0.11 SE) to -4.46% (±0.31 SE) across all species and locations. We statistically analyzed potential drivers of measurement error, including distance of the turtle to the SVCS, turtle angle, image quality, turtle size, capture location, and species. Point 4: Using a linear mixed effects model, we found that the distance between the turtle and the SVCS was the primary factor influencing measurement error. Our research suggests that stereo-video technology enables high-quality measurements of sea turtle body size collected in situ without the need for hand-capturing individuals. This study contributes to the growing knowledge base that SVCS are accurate for body size measurements independent of taxonomic clade.

A computational framework for studying energetics and resource management in sea turtle migration and autonomous systems.

Sea turtles complete migrations across vast distances, covering entire ocean basins. To track these migrations, satellite tracking tags are attached to their shells. The impact of these tags must be considered to ensure that turtles' natural behavior is not artificially and adversely impacted through tag-related drag, and that the data collected by a small sample of sea turtles accurately represents the larger population. Additionally, it can be difficult to study animal energetics in the field over large migration distances. In this work, we modify a computational behavior model to study how satellite tracking tags affect turtle migration behavior. Our agent based model contains synthetic magnetic field environments that are used for navigation cues, an ocean current, resource distributions that represent locations of food, and an agent that attempts to migrate to several different goals. The agent loses energy as it progresses, and searches for the resource distributions to replenish itself. Our novel simulation framework demonstrates the relationship between an agent's available energy capacity, its energy consumption based on mechanical power expended, and its ability to navigate to all migratory goal points. This study can be utilized to (1) probe the impacts of an animal's energy capacity and foraging behavior on its resulting navigation and ecology, (2) guide future satellite tag designs, and (3) develop usage recommendations for a suitable tracking tag based on the type of experiment being conducted. Our model can be expanded beyond sea turtles to study other marine species (e.g., sharks, whales). Additionally, this model could be expanded to other domains within the marine environment. For example, it could be modified to examine design trade-offs in remotely operated vehicles (ROVs), which share many of the same operational constraints as sea turtles and other migratory species.