Assessing climate change associated sea-level rise impacts on sea turtle nesting beaches using drones, photogrammetry and a novel GPS system.

Climate change associated sea-level rise (SLR) is expected to have profound impacts on coastal areas, affecting many species, including sea turtles which depend on these habitats for egg incubation. Being able to accurately model beach topography using digital terrain models (DTMs) is therefore crucial to project SLR impacts and develop effective conservation strategies. Traditional survey methods are typically low-cost with low accuracy or high-cost with high accuracy. We present a novel combination of drone-based photogrammetry and a low-cost and portable real-time kinematic (RTK) GPS to create DTMs which are highly accurate (<10 cm error) and visually realistic. This methodology is ideal for surveying coastal sites, can be broadly applied to other species and habitats, and is a relevant tool in supporting the development of Specially Protected Areas. Here, we applied this method as a case-study to project three SLR scenarios (0.48, 0.63 and 1.20 m) and assess the future vulnerability and viability of a key nesting habitat for sympatric loggerhead (Caretta caretta) and green turtle (Chelonia mydas) at a key rookery in the Mediterranean. We combined the DTM with 5 years of nest survey data describing location and clutch depth, to identify (a) regions with highest nest densities, (b) nest elevation by species and beach, and (c) estimated proportion of nests inundated under each SLR scenario. On average, green turtles nested at higher elevations than loggerheads (1.8 m vs. 1.32 m, respectively). However, because green turtles dig deeper nests than loggerheads (0.76 m vs. 0.50 m, respectively), these were at similar risk of inundation. For a SLR of 1.2 m, we estimated a loss of 67.3% for loggerhead turtle nests and 59.1% for green turtle nests. Existing natural and artificial barriers may affect the ability of these nesting habitats to remain suitable for nesting through beach migration.

Climate change resilience of a globally important sea turtle nesting population.

Few studies have looked into climate change resilience of populations of wild animals. We use a model higher vertebrate, the green sea turtle, as its life history is fundamentally affected by climatic conditions, including temperature-dependent sex determination and obligate use of beaches subject to sea level rise (SLR). We use empirical data from a globally important population in West Africa to assess resistance to climate change within a quantitative framework. We project 200 years of primary sex ratios (1900-2100) and create a digital elevation model of the nesting beach to estimate impacts of projected SLR. Primary sex ratio is currently almost balanced, with 52% of hatchlings produced being female. Under IPCC models, we predict: (a) an increase in the proportion of females by 2100 to 76%-93%, but cooler temperatures, both at the end of the nesting season and in shaded areas, will guarantee male hatchling production; (b) IPCC SLR scenarios will lead to 33.4%-43.0% loss of the current nesting area; (c) climate change will contribute to population growth through population feminization, with 32%-64% more nesting females expected by 2120; (d) as incubation temperatures approach lethal levels, however, the population will cease growing and start to decline. Taken together with other factors (degree of foraging plasticity, rookery size and trajectory, and prevailing threats), this nesting population should resist climate change until 2100, and the availability of spatial and temporal microrefugia indicates potential for resilience to predicted impacts, through the evolution of nest site selection or changes in nesting phenology. This represents the most comprehensive assessment to date of climate change resilience of a marine reptile using the most up-to-date IPCC models, appraising the impacts of temperature and SLR, integrated with additional ecological and demographic parameters. We suggest this as a framework for other populations, species and taxa.