Previous studies have found there is a high spatial correlation between Loggerhead presence offshore of Southern California and pelagic sea surface temperature (SST). Additionally, sea turtle bycatch records have found that the occasional presence of Loggerheads in southern California largely occurs during El Niño conditions. As the climate shifts warmer, scientists have suggested sea surface temperature (SST) alone may not be a good proxy for Loggerhead habitat. We integrated three datasets (2003-2023) to predict Loggerhead presence in the California Bight during El Niño conditions; aerial surveys, shipboard marine mammal surveys, and sighting reports from the public. In addition to sea surface temperature, primary productivity, surface elevation mean, and bathymetry coefficients from the GAM model were all statistically significant in predicting Loggerhead occurrence. Loggerhead presence was statistically higher in locations with sea surface temperatures of 17.5 to 22.5 °C. Loggerhead presence was statistically higher in areas of low primary productivity (1000 mg C m-2 day-1), waters with shorter wave heights, and closer to the shore. Additionally, the probability of Loggerhead presence was slightly higher, closer to the edge of frontal eddies. Stakeholders can use these findings to identify new environmental indicators linked with Loggerhead presence and key areas for longline fishing closure to reduce Loggerhead bycatch offshore of Southern California. Our study also provides evidence of the added benefits of public sightings reports and citizen engagement in monitoring endangered species.

[Overview]

Sea turtles are categorized as endangered species, and effective conservation necessitates precise survival estimation. Confidence intervals or Highest Density intervals (HDIs) serve as indicators of this accuracy, emphasizing the need for the development of a new framework to enable narrower-interval survival estimations. In this study, we developed a novel survival estimation framework.

[Details]

Catch-curve analysis, commonly used for survival estimation, encounters limitations due to the existing framework's inability to account for growth curve errors or sea turtle immigration. However, compared to mark-recapture analysis, which relies on tag data, catch-curve analysis does not demand intensive research efforts. Consequently, our research team devised a new estimation framework that incorporates growth curve errors and turtle immigration using the Bayesian estimation method, allowing for adaptable model construction and the integration of prior information in the estimation process. Within this framework, we specify the parameters and their respective ranges as prior information and execute the program to fit the distribution of carapace lengths, subsequently estimating the posterior distribution or 95% Highest Density Intervals (HDIs) from the converging values of each parameter.

Using the developed framework, the survival rate of loggerhead turtles in Muroto, Kochi Prefecture, Japan was estimated as 0.852/year (95% HDI: 0.799-0.903). For this estimation, the straight carapace length (SCL) data were used and obtained from incidentally captured individuals from July 2002 to November 2009, comprising 1391 individuals (mode:740–749 mm class; range:563–960 mm). Our research framework enables estimations even with limited sample sizes; for example, with data on carapace length from over 500 individuals, it becomes possible to estimate survival rates with less than 10% HDIs.

Grenada, a tri-island nation in the southeastern Caribbean Sea, supports aggregates of foraging green turtles (Chelonia mydas) and foraging and nesting hawksbill turtles (Eretmochelys imbricata). Conservation strategies are currently limited by a lack of detailed knowledge of the genetic make-up, life history and migration patterns of the local aggregates of these species. Genetic characterisation provides a means for inferring population diversity and origins for these aggregates and to assess potential impacts from regional and worldwide management strategies. Additionally, chelonid alphaherpesvirus-5 (ChHV5) and ChHV5-associated fibropapillomatosis (FP) have recently been reported within Grenada’s green turtle aggregation, but the epidemiology of the disease in Grenada remains poorly understood. We genetically characterised Grenada’s foraging green (n = 57), nesting hawksbill (n = 18), and foraging hawksbill turtle aggregates (n = 22), and used mixed stock analysis (MSA) to assess the level of genetic connectivity of Grenada’s populations with other populations in the Atlantic region. Furthermore, foraging green turtles were assessed for prior exposure to ChHV5 using a serological assay to examine associations between origins and infection status. Mitochondrial DNA (mtDNA) sequencing data revealed seven haplotypes within Grenada’s foraging green turtle aggregation, including one novel haplotype (CM-A82.1), and a total of seven haplotypes across Grenada’s nesting and foraging hawksbill turtle aggregations, including one (Ei-A68) and two rare haplotypes (Ei-A45, Ei-A72), respectively. We identify Grenada’s Isle de Caille rookery as a nesting population of origin for haplotype Ei-A68, which was an orphan haplotype prior to this study. MSA results indicate that Grenada’s green and hawksbill turtle populations are associated with that of 15 other countries throughout the Atlantic region. Grenada's hawksbill turtle rookery contributes 3.6% to the foraging hawksbill turtle aggregation within Grenada, whilst the foraging aggregation contributes 14.5% to the rookery, according to foraging-ground-centric and rookery-centric MSA results, respectively. ChHV5-specific antibodies were identified in serum samples in 9.38% of green turtles, with no apparent association of ChHV5 serology status and green turtle haplotype. Though a small percentage of Grenada’s hawksbill turtle population appears to be residential, mixed stock analyses strongly indicate that Grenada’s sea turtle populations are regionally shared resources and should be managed as such. Furthermore, the rare and/or unique haplotypes present within Grenada’s sea turtle populations offer valuable genetic diversity to the wider region and further conservation strategies are warranted to protect these at-risk haplotypes.

The green turtle (Chelonia mydas) is a highly migratory endangered species. Several direct threat-related strandings of turtles (i.e. bycatch and marine pollution) are reported yearly in the Southwestern Atlantic Ocean (SWAO), and consequently critical areas for sea turtle conservation have been identified in the region, including the coast of Uruguay. This region is an important foraging ground for juveniles feeding on macroalgae, which is a key component of rocky marine ecosystems and provides food and shelter to many species. To date, several efforts have been made to protect sea turtles and reduce threats, however, little attention has been given to evaluating habitat degradation at feeding grounds in SWAO, mainly due to cost and complex logistics. Long-term monitoring programs represent a valuable tool for decision-makers to prevent and mitigate possible threats to sea turtles, and due to their spatially complex life cycle and biology, research and conservation efforts for these animals have been relying on new technology and more efficient protocols to achieve a better understanding of population trends and threats. Recently, Uncrewed Aerial Systems (UAS, or drones) have been introduced for such studies. However, their implementation has been neglected in the SWAO, due in part to the limited sampling protocols available and low water visibility. This aims to develop a holistic approach to the conservation of juvenile green turtles by using UAS to conduct aerial surveys in Uruguayan feeding areas and to determine if this tool is viable to be implemented in long-term population studies.

We used a UAS to survey juvenile green turtles in Cerro Verde e Islas de la Coronilla Coastal-Marine Protected Area (CMPA), Uruguay. We conducted aerial surveys over the water between December 2021-May 2022. We deployed the UAS from the shore, collecting video of the coastal foraging grounds while flying 200m linear transects at an altitude of 35 - 40 m. We conducted 123 missions in four survey areas over 25 field days. Mission duration depended on the survey area and flight times ranged from 7 to 16 minutes, totaling 20.4 hours of video. Days in the field were limited due to high wind and Beaufort Sea State, with operations only possible at mean wind speeds below 28kph (max gusts of 35kph) and sea state of 3. Depending on the survey area, we counted 0 – 70 turtle sightings with an outlier of 126 individuals. These results are preliminary with 30% of videos still being processed. The next step will be to calculate Observations-per-Unit-Effort and to estimate Relative Density of green turtle in CMPA accounting for individuals not available to being seen (Probability of being visible). This ongoing work demonstrates that UAS are effective tools for performing sea turtle monitoring in a region that was previously understudied due to environmental factors such as water clarity. Furthermore, we show the potential benefit of using UAS in sub-optimal environmental and oceanographic conditions, providing information and opportunities to study habitat use, distribution and density of the juvenile green turtle in the main feeding area in Uruguay.

Projection models are being increasingly used to manage threatened taxa by estimating their responses to climate change. Sea turtles are particularly susceptible to climate change as they have temperature-dependent sex determination and so increased sand temperatures could result in the ‘feminisation’ of hatchling sex ratios. Additionally, the implications of temperature data logger accuracy and precision are rarely considered prior to their application in many ecological studies. We assessed the accuracy and precision of three commonly used temperature data loggers (Hobo®, iButton® and TinyTag®) for ecological studies. Through water bath laboratory studies, we found that the accuracy was highest in TinyTags (±0.23°C) and lowest in HOBOs and iButtons (±0.43°C and ±0.49°C respectively). Our results suggest that these temperature loggers can provide reliable descriptions of sand temperature if they are not over-interpreted. We then wanted to consider the risk of climate-induced feminisation for nesting sites within the Asia-Pacific region, as there has been a significant gap in our knowledge of the sand temperatures and hatchling sex ratios for this important region. We modelled the likely long-term trends in sand temperatures and hatchling sex ratios at a nesting site for endangered green turtles (Chelonia mydas) and critically endangered hawksbill turtles (Eretmochelys imbricata) in eastern Papua New Guinea (PNG). A total of 1078 days of sand temperature data were collected from 28 logger deployments at nest depth between 2018 and 2022 on two islands within the Conflict Island Group, PNG. Long-term trends in sand temperature were generated from a model using air temperature as an environmental proxy. The influence of rainfall and seasonal variation on sand temperature was also investigated. Between 1960 and 2019, we estimated that sand temperature increased by ~0.6°C and the average hatchling sex ratio was relatively balanced (46.2% female, SD = 10.7). Additionally, the sex ratio models were unlikely to be influenced by changing rainfall patterns, as our analyses indicated that there were no trends in historical rainfall anomalies and projections indicated no further changes to rainfall until 2100. A relatively balanced sex ratio such as this is starkly different to the extremely female-skewed hatchling sex ratio (>99% female) reported for another Coral Sea nesting site, Raine Island (~850 km west). This PNG nesting site may be rare in the global context, as it is less threatened by climate-induced feminisation. Although there is no current need for ‘cooling’ interventions, the mean projected sex ratios for 2020–2100 were estimated to be 76%–87% female, so future interventions (such as irrigation) may be required to increase male production. This research is part of the ‘Turtle Cooling’ Project and is a broader collaboration with many independent monitoring groups across seven different countries. These relationships have facilitated our ability to fill a substantial knowledge gap on the likely hatchling sex ratios for these important turtle rookeries in the Asia-Pacific. Through this research, we hope to expand on existing hatchling sex ratios datasets for global sea turtle populations and highlight the variables that drive cool sand temperatures at male-producing sites.