Climate change resilience of a globally important sea turtle nesting population

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Abstract

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.

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