Explore the vast range of titles available.

Patterns of animal movement associated with foraging lie at the heart of many ecological studies and often animals face decisions of staying in an environment they know versus relocating to new sites. The lack of knowledge of new foraging sites means there is risk associated with a decision to relocate (e.g. poor foraging) as well as a potential benefit (e.g. improved foraging). Using a unique long‐term satellite tracking dataset for several sea turtle species, combined with capture–mark–recapture data extending over 50 years, we show how, across species, individuals generally maintain tight fidelity to specific foraging sites after extended (up to almost 10,000 km) migration to and from distant breeding sites as well as across many decades. Migrating individuals often travelled through suitable foraging areas en route to their ‘home’ site and so extended their journeys to maintain foraging site fidelity. We explore the likely mechanistic underpinnings of this trait, which is also seen in some migrating birds, and suggest that individuals will forgo areas of suitable forage encountered en route during migration when they have poor knowledge of the long‐term suitability of those sites, making relocation to those sites risky. Using satellite tracking in the western Indian Ocean and northern Australia, the authors show that adult green turtles have fidelity to small foraging areas that may be 1,000s of km from their nesting beach. Individuals often forgo suitable foraging areas encountered during migration, probably because relocation to those sites is risky.

Resolving threats to widely distributed marine megafauna requires definition of the geographic distributions of both the threats as well as the population unit(s) of interest. In turn, because individual threats can operate on varying spatial scales, their impacts can affect different segments of a population of the same species. Therefore, integration of multiple tools and techniques--including site-based monitoring, genetic analyses, mark-recapture studies and telemetry--can facilitate robust definitions of population segments at multiple biological and spatial scales to address different management and research challenges. To address these issues for marine turtles, we collated all available studies on marine turtle biogeography, including nesting sites, population abundances and trends, population genetics, and satellite telemetry. We georeferenced this information to generate separate layers for nesting sites, genetic stocks, and core distributions of population segments of all marine turtle species. We then spatially integrated this information from fine- to coarse-spatial scales to develop nested envelope models, or Regional Management Units (RMUs), for marine turtles globally. The RMU framework is a solution to the challenge of how to organize marine turtles into units of protection above the level of nesting populations, but below the level of species, within regional entities that might be on independent evolutionary trajectories. Among many potential applications, RMUs provide a framework for identifying data gaps, assessing high diversity areas for multiple species and genetic stocks, and evaluating conservation status of marine turtles. Furthermore, RMUs allow for identification of geographic barriers to gene flow, and can provide valuable guidance to marine spatial planning initiatives that integrate spatial distributions of protected species and human activities. In addition, the RMU framework--including maps and supporting metadata--will be an iterative, user-driven tool made publicly available in an online application for comments, improvements, download and analysis.

Late Jurassic deposits across Europe have yielded a rich fauna of extinct turtles. Although many of these turtles are recovered from marine deposits, it is unclear which of these taxa are habitually marine and which may be riverine species washed into nearby basins, as adaptations to open marine conditions are yet to be found. Two new fossils from the Late Jurassic of Germany provide unusually strong evidence for open marine adaptations. The first specimen is a partial shell and articulated hind limb from the Late Jurassic (early Tithonian) platy limestones of Schernfeld near Eichstätt, which preserves the integument of the hind limb as an imprint. The skin is fully covered by flat, polygonal scales, which stiffen the pes into a paddle. Although taxonomic attribution is not possible, similarities are apparent with Thalassemys . The second specimen is a large, articulated skeleton with hypertrophied limbs referable to Thalassemys bruntrutana from the Late Jurassic (early Late Kimmeridgian) platy limestone of Wattendorf, near Bamberg. Even though the skin is preserved as a phosphatic film, the scales are not preserved. This specimen can nevertheless be inferred to have had paddles stiffened by scales based on the pose in which they are preserved, the presence of epibionts between the digits, and by full morphological correspondence to the specimen from Schernfeld. An analysis of scalation in extant turtles demonstrated that elongate flippers stiffed by scales are a marine adaptation, in contrast to the elongate but flexible flippers of riverine turtles. Phylogenetic analysis suggests that Thalassemys bruntrutana is referable to the mostly Late Jurassic turtle clade Thalassochelydia . The marine adapted flippers of this taxon therefore evolved convergently with those of later clades of marine turtles. Although thalassochelydian fossils are restricted to Europe, with one notable exception from Argentina, their open marine adaptations combined with the interconnectivity of Jurassic oceans predict that the clade must have been even more wide-spread during that time.

Drones are being increasingly used in innovative ways to enhance environmental research and conservation. Despite their widespread use for wildlife studies, there are few scientifically justified guidelines that provide minimum distances at which wildlife can be approached to minimize visual and auditory disturbance. These distances are essential to ensure that behavioral and survey data have no observer bias and form the basis of requirements for animal ethics and scientific permit approvals. In the present study, we documented the behaviors of three species of sea turtle (green turtles, Chelonia mydas, flatback turtles, Natator depressus, hawksbill turtles, Eretmochelys imbricata), saltwater crocodiles (Crocodylus porosus), and crested terns (Thalasseus bergii) in response to a small commercially available (1.4 kg) multirotor drone flown in Northern Territory and Western Australia. Sea turtles in nearshore waters off nesting beaches or in foraging habitats exhibited no evasive behaviors (e.g. rapid diving) in response to the drone at or above 20-30 m altitude, and at or above 10 m altitude for juvenile green and hawksbill turtles foraging on shallow, algae-covered reefs. Adult female flatback sea turtles were not deterred by drones flying forward or stationary at 10 m altitude when crawling up the beach to nest or digging a body pit or egg chamber. In contrast, flyovers elicited a range of behaviors from crocodiles, including minor, lateral head movements, fleeing, or complete submergence when a drone was present below 50 m altitude. Similarly, a colony of crested terns resting on a sand-bank displayed disturbance behaviors (e.g. flight response) when a drone was flown below 60 m altitude. The current study demonstrates a variety of behavioral disturbance thresholds for diverse species and should be considered when establishing operating conditions for drones in behavioral and conservation studies.

Aim Understanding the spatial ecology of animal movements is a critical element in conserving long‐lived, highly mobile marine species. Analyzing networks developed from movements of six sea turtle species reveals marine connectivity and can help prioritize conservation efforts. Location Global. Methods We collated telemetry data from 1235 individuals and reviewed the literature to determine our dataset's representativeness. We used the telemetry data to develop spatial networks at different scales to examine areas, connections, and their geographic arrangement. We used graph theory metrics to compare networks across regions and species and to identify the role of important areas and connections. Results Relevant literature and citations for data used in this study had very little overlap. Network analysis showed that sampling effort influenced network structure, and the arrangement of areas and connections for most networks was complex. However, important areas and connections identified by graph theory metrics can be different than areas of high data density. For the global network, marine regions in the Mediterranean had high closeness, while links with high betweenness among marine regions in the South Atlantic were critical for maintaining connectivity. Comparisons among species‐specific networks showed that functional connectivity was related to movement ecology, resulting in networks composed of different areas and links. Main conclusions Network analysis identified the structure and functional connectivity of the sea turtles in our sample at multiple scales. These network characteristics could help guide the coordination of management strategies for wide‐ranging animals throughout their geographic extent. Most networks had complex structures that can contribute to greater robustness but may be more difficult to manage changes when compared to simpler forms. Area‐based conservation measures would benefit sea turtle populations when directed toward areas with high closeness dominating network function. Promoting seascape connectivity of links with high betweenness would decrease network vulnerability.

After emerging from nests, neonate sea turtles entering the water are thought to orientate away from shore using wave cues to guide them out to sea. Artificial light may interfere with this process, but the relative importance of natural and anthropogenic cues to the dispersal of hatchlings is unknown. Here, we used acoustic telemetry to track the movement of flatback turtle Natator depressus hatchlings dispersing through nearshore waters. Turtles dispersed in the presence and absence of artificial light through a receiver array where a range of oceanographic variables were measured. Turtle tracks were analysed using a full subsets generalised additive mixed model approach to identify the most important cues influencing the bearing, variance in bearing (a measure of the ability to orientate directly), rate of travel and time spent in the array. Artificial light reduced their swim speed by up to 30%, increased the amount of time spent in nearshore waters (by 50 to 150%) and increased the variance in bearing (100 to 180% more variable), regardless of oceanographic conditions. Under ambient conditions, ocean currents affected the bearing of hatchlings as they left the shore, but when light was present, this effect was diminished, showing turtles actively swam against currents in their attempts to move towards light. After accounting for the effects of currents on hatchlings dispersing under ambient conditions, turtles swam offshore by moving perpendicular to the coastline and did not appear to orient into incident wave direction. Overall, light disrupted the dispersal of hatchlings, causing them to linger, become disoriented in the nearshore and expend energy swimming against ocean currents.

The impact of a range of different threats has resulted in the listing of six out of seven sea turtle species on the IUCN Red List of endangered species. Disease risk analysis (DRA) tools are designed to provide objective, repeatable and documented assessment of the disease risks for a population and measures to reduce these risks through management options. To the best of our knowledge, DRAs have not previously been published for sea turtles, although disease is reported to contribute to sea turtle population decline. Here, a comprehensive list of health hazards is provided for all seven species of sea turtles. The possible risk these hazards pose to the health of sea turtles were assessed and \"One Health\" aspects of interacting with sea turtles were also investigated. The risk assessment was undertaken in collaboration with more than 30 experts in the field including veterinarians, microbiologists, social scientists, epidemiologists and stakeholders, in the form of two international workshops and one local workshop. The general finding of the DRA was the distinct lack of knowledge regarding a link between the presence of pathogens and diseases manifestation in sea turtles. A higher rate of disease in immunocompromised individuals was repeatedly reported and a possible link between immunosuppression and environmental contaminants as a result of anthropogenic influences was suggested. Society based conservation initiatives and as a result the cultural and social aspect of interacting with sea turtles appeared to need more attention and research. A risk management workshop was carried out to acquire the insights of local policy makers about management options for the risks relevant to Queensland and the options were evaluated considering their feasibility and effectiveness. The sea turtle DRA presented here, is a structured guide for future risk assessments to be used in specific scenarios such as translocation and head-starting programs.

Global warming could threaten over 400 species with temperature‐dependent sex determination (TSD) worldwide, including all species of sea turtle. During embryonic development, rising temperatures might lead to the overproduction of one sex and, in turn, could bias populations’ sex ratios to an extent that threatens their persistence. If climate change predictions are correct, and biased sex ratios reduce population viability, species with TSD may go rapidly extinct unless adaptive mechanisms, whether behavioural, physiological or molecular, exist to buffer these temperature‐driven effects. Here, we summarize the discovery of the TSD phenomenon and its still elusive evolutionary significance. We then review the molecular pathways underpinning TSD in model species, along with the hormonal mechanisms that interact with temperatures to determine an individual's sex. To illustrate evolutionary mechanisms that can affect sex determination, we focus on sea turtle biology, discussing both the adaptive potential of this threatened TSD taxon, and the risks associated with conservation mismanagement.

To address a major knowledge gap for flatback sea turtles ( Natator depressus ), a species endemic to Australia and considered ‘Data Deficient’ for IUCN Red List assessment, we present the first-ever skeletochronology-derived age and growth rate estimates for this species. Using a rare collection of bone samples gathered from across northern Australia, we applied skeletochronology and characterized the length-at-age relationship, established baseline growth rates from the hatchling to adult life stages, and produced empirical estimates of age-at- and size-at-sexual-maturation (ASM, SSM). We analyzed humeri from 74 flatback sea turtles ranging in body size from 6.0–96.0 cm curved carapace length (CCL), and recovered from Western Australia (n = 48), Eastern Australia (n = 13), central Australia (n = 8; Northern Territory n = 3, the Gulf of Carpentaria n = 5), and unknown locations (n = 5). We identified the onset of sexual maturity for 29 turtles, based on rapprochement growth patterns in the bones. Estimates for ASM ranged from 12.0 to 23.0 years (mean: 16.3 ± 0.53 SE), SSM ranged from 76.1 to 94.0 cm CCL (mean: 84.9 ± 0.90 SE), and maximum observed reproductive longevity was 31 years for a 45-year old male flatback. Growth was modeled as a smoothing spline fit to the size-at-age relationship and at the mean SSM (84.9 cm CCL) corresponded with a spline-predicted maturity age of 18 years (95% CI: 16 to 24), while mean nesting sizes reported in the literature (86.4 to 94 cm CCL) corresponded to estimated ages of 24+ years. A bootstrapped von Bertalanffy growth model was also applied and showed consistencies with the spline curve, yielding an estimated upper size limit, L inf , at 89.2 ± 0.04 cm (95% CI: 85.5 to 95.9 cm) with the intrinsic growth rate parameter, k , at 0.185 ± 0.0004 (0.16 to 0.22); at the same mean SSM (84.9 cm CCL) the estimated ASM was 16.3 ± 0.05 years (95% CI: 12.8 to 27.7 years). Lastly, four of the samples analyzed were collected from deceased adult females that had previous sizes known from on-going mark/recapture studies at nesting sites in Western Australia. The paired CCL data (measured at nesting and back-calculated) did not significantly differ (p = 0.875). This first skeletochronology study for flatback sea turtles generates valuable empirical estimates for ongoing conservation and management efforts.

Remotely-operated vehicles (ROVs) are used extensively by the offshore oil and gas and renewables industries for inspection, maintenance, and repair of their infrastructure. With thousands of subsea structures monitored across the world’s oceans from the shallows to depths greater than 1000 m, there is a great and underutilised opportunity for their scientific use. Through slight modifications of ROV operations, and by augmenting industry workclass ROVs with a range of scientific equipment, industry can fuel scientific discoveries, contribute to an understanding of the impact of artificial structures in our oceans, and collect biotic and abiotic data to support our understanding of how oceans and marine life are changing. Here, we identify and describe operationally-feasible methods to alter adjust the way in which industry ROVs are operated to enhance the scientific value of data that they collect, without significantly impacting scheduling or adding to deployment costs. These include: rapid marine life survey protocols, imaging improvements, the addition of a range of scientific sensors, and collection of biological samples. By partnering with qualified and experienced research scientists, industry can improve the quality of their ROV-derived data, allowing the data to be analysed robustly. Small changes by industry now could provide substantial benefits to scientific research in the long-term and improve the quality of scientific data in existence once the structures require decommissioning. Such changes also have the potential to enhance industry’s environmental stewardship by improving their environmental management and facilitating more informed engagement with a range of external stakeholders, including regulators and the public.