Uncovering loggerhead (Caretta caretta) navigation strategy in the open ocean through the consideration of their diving behaviour.

While scientists have been monitoring the movements and diving behaviour of sea turtles using Argos platform terminal transmitters for decades, the precise navigational mechanisms used by these animals remain an open question. Until now, active swimming motion has been derived from total motion by subtracting surface or subsurface modelled ocean currents, following the approximation of a quasi-two-dimensional surface layer migration. This study, based on tracking and diving data collected from 25 late-juvenile loggerhead turtles released from Reunion Island during their pre-reproductive migration, demonstrates the importance of considering the subsurface presence of the animals. Using a piecewise constant heading model, we investigate navigation strategy using daily time-at-depth distributions and three-dimensional currents to calculate swimming velocity. Our results are consistent with a map and compass strategy in which swimming movements follow straight courses at a stable swimming speed (approx. 0.5 m s-1), intermittently segmented by course corrections. This strategy, previously hypothesized for post-nesting green and hawksbill turtles, had never been observed in juvenile loggerheads. These results confirm a common open-ocean navigation mechanism across ages and species and highlight the importance of considering diving behaviour in most studies of sea turtle spatial ecology.

Age prediction of green turtles with an epigenetic clock.

Age is a fundamental life history attribute that is used to understand the dynamics of wild animal populations. Unfortunately, most animals do not have a practical or nonlethal method to determine age. This makes it difficult for wildlife managers to carry out population assessments, particularly for elusive and long-lived fauna such as marine turtles. In this study, we present an epigenetic clock that predicts the age of marine turtles from skin biopsies. The model was developed and validated using DNA from known-age green turtles (Chelonia mydas) from two captive populations, and mark-recapture wild turtles with known time intervals between captures. Our method, based on DNA methylation levels at 18 CpG sites, was highly accurate with a median absolute error of 2.1 years (4.7% of maximum age in data set). This is the first epigenetic clock developed for a reptile and illustrates their broad applicability across a broad variety of vertebrate species. It has the potential to transform marine turtle management through a nonlethal and inexpensive method to provide key life history information.

Contrasted habitats and individual plasticity drive the fine scale movements of juvenile green turtles in coastal ecosystems.

BACKGROUND: A strong behavioural plasticity is commonly evidenced in the movements of marine megafauna species, and it might be related to an adaptation to local conditions of the habitat. One way to investigate such behavioural plasticity is to satellite track a large number of individuals from contrasting foraging grounds, but despite recent advances in satellite telemetry techniques, such studies are still very limited in sea turtles. METHODS: From 2010 to 2018, 49 juvenile green turtles were satellite tracked from five contrasting feeding grounds located in the South-West Indian Ocean in order to (1) assess the diel patterns in their movements, (2) investigate the inter-individual and inter-site variability, and (3) explore the drivers of their daily movements using both static (habitat type and bathymetry) and dynamic variables (daily and tidal cycles). RESULTS: Despite similarities observed in four feeding grounds (a diel pattern with a decreased distance to shore and smaller home ranges at night), contrasted habitats (e.g. mangrove, reef flat, fore-reef, terrace) associated with different resources (coral, seagrass, algae) were used in each island. CONCLUSIONS: Juvenile green turtles in the South-West Indian Ocean show different responses to contrasting environmental conditions - both natural (habitat type and tidal cycle) and anthropogenic (urbanised vs. uninhabited island) demonstrating the ability to adapt to modification of habitat.

DNA metabarcoding and microscopic analyses of sea turtles biofilms: Complementary to understand turtle behavior.

Sea turtles are distributed in tropical and subtropical seas worldwide. They play several ecological roles and are considered important indicators of the health of marine ecosystems. Studying epibiotic diatoms living on turtle shells suggestively has great potential in the study of turtle behavior because diatoms are always there. However, diatom identification at the species level is time consuming, requires well-trained specialists, and there is a high probability of finding new taxa growing on turtle shells, which makes identification tricky. An alternative approach based on DNA barcoding and high throughput sequencing (HTS), metabarcoding, has been developed in recent years to identify species at the community level by using a DNA reference library. The suitabilities of morphological and molecular approaches were compared. Diatom assemblages were sampled from seven juvenile green turtles (Chelonia mydas) from Mayotte Island, France. The structures of the epibiotic diatom assemblages differed between both approaches. This resulted in different clustering of the turtles based on their diatom communities. Metabarcoding allowed better discrimination between turtles based on their epibiotic diatom assemblages and put into evidence the presence of a cryptic diatom diversity. Microscopy, for its part, provided more ecological information of sea turtles based on historical bibliographical data and the abundances of ecological guilds of the diatom species present in the samples. This study shows the complementary nature of these two methods for studying turtle behavior.

Energy expenditure of freely swimming adult green turtles (Chelonia mydas) and its link with body acceleration.

Marine turtles are globally threatened. Crucial for the conservation of these large ectotherms is a detailed knowledge of their energy relationships, especially their at-sea metabolic rates, which will ultimately define population structure and size. Measuring metabolic rates in free-ranging aquatic animals, however, remains a challenge. Hence, it is not surprising that for most marine turtle species we know little about the energetic requirements of adults at sea. Recently, accelerometry has emerged as a promising tool for estimating activity-specific metabolic rates of animals in the field. Accelerometry allows quantification of the movement of animals (ODBA/PDBA, overall/partial dynamic body acceleration), which, after calibration, might serve as a proxy for metabolic rate. We measured oxygen consumption rates (V(O(2))) of adult green turtles (Chelonia mydas; 142.1±26.9 kg) at rest and when swimming within a 13 m-long swim channel, using flow-through respirometry. We investigated the effect of water temperature (T(w)) on turtle and tested the hypothesis that turtle body acceleration can be used as a proxy for V(O(2)). Mean mass-specific V(O(2)) (sV(O(2))) of six turtles when resting at a T(w) of 25.8±1.0°C was 0.50±0.09 ml min(-1) kg(-0.83). sV(O(2))increased significantly with T(w) and activity level. Changes in sV(O(2)) were paralleled by changes in respiratory frequency (f(R)). Deploying bi-axial accelerometers in conjunction with respirometry, we found a significant positive relationship between sV(O(2)) and PDBA that was modified by T(w). The resulting predictive equation was highly significant (r(2)=0.83, P<0.0001) and associated error estimates were small (mean algebraic error 3.3%), indicating that body acceleration is a good predictor of V(O(2)) in green turtles. Our results suggest that accelerometry is a suitable method to investigate marine turtle energetics at sea.