Balanced primary sex ratios and resilience to climate change in a major sea turtle population

Abstract

Global climate change is expected to have major impacts on biodiversity. Marine turtles have temperature-dependent sex determination, and many populations produce highly femalebiased offspring sex ratios, a skew likely to increase further with global warming. We looked at one of the world's largest green turtle rookeries, in West Africa, to assess the population's primary sex ratio and resilience to climate change. In 2013 and 2014, we deployed dataloggers recording nest (n=101) and sand (n=30) temperatures, and identified hatchling sex (n=131) by histological examination of gonads. A logistic curve was fitted to the data, to allow predictions of sex ratio across habitats and through the nesting season. The population-specific pivotal temperature was 29.4ºC, and both sexes were produced within incubation temperatures from 27.6ºC to 31.4ºC: transitional range of temperatures (TRT). Primary sex ratio changed from male to female dominated across relatively small temporal and spatial scales, but was overall balanced. We estimated an exceptionally high male hatchling production of 47.7% (95% CI: 36.7-58.3%) and 44.5% (95% CI: 33.8-55.4%) in 2013 and 2014, respectively. Both the temporal and spatial variation in incubation conditions, and the wide range of the TRT, suggest resilience and potential for adaptation to climate change, if the present nesting habitat remains unchanged. These findings underline the importance of assessing site-specific parameters to understand populations' response to climate change, particularly with regard to identifying rookeries with high male hatchling production that may be key for the future conservation of sea turtles, under projected global warming scenarios.

Climate change resilience of a globally important sea turtle nesting population

“…Sand temperature was recorded at mean clutch depth (0.7 m, Patrício, Marques, et al., ) with Tinytag‐TGP‐4017 dataloggers (Gemini Data Loggers, Chichester, UK, ±0.3°C accuracy, 0.1°C resolution), in 2013 ( n = 16), and 2014 ( n = 14). All dataloggers were calibrated before and after each nesting season in a constant temperature room (24 hr at 28°C) and used only if accuracy was ≤0.3°C.…”

“…The sand temperature at Poilão varies in relation to the amount of shading, and we defined three microhabitats: “open sand,” “forest border,” and “forest,” per Patrício, Marques, et al. (). Thus, to account for spatial and temporal variability in sand temperature, the dataloggers were distributed along the nesting beach, which extends for 1,800 m, throughout the nesting season, at the open sand ( n = 6/5 in 2013/2014), forest border ( n = 5/4), and forest ( n = 5/5), with at least one datalogger every 500 m at each microhabitat in both years.…”

“…Thus, to account for spatial and temporal variability in sand temperature, the dataloggers were distributed along the nesting beach, which extends for 1,800 m, throughout the nesting season, at the open sand ( n = 6/5 in 2013/2014), forest border ( n = 5/4), and forest ( n = 5/5), with at least one datalogger every 500 m at each microhabitat in both years. Sand temperatures were highly correlated among habitats (open sand vs. forest border r 2 = 0.96, and forest border vs. forest r 2 = 0.94), with sand temperature at the forest border on average 1.0°C below that of the open sand, and 1.5°C above that at the forest (Patrício, Marques, et al., ). We estimated future sand temperatures using the equation: T sand = 0.94T air +3.04, r 2 = 0.60, p < 0.0001, n = 39, T sand = mean biweekly sand temperature at Poilão in the forest border habitat, T air = mean biweekly air temperature at Bissau, sample period = 1 March 2013 to 15 October 2014 (see Patrício, Marques, et al., ).…”

“…Sand temperatures were highly correlated among habitats (open sand vs. forest border r 2 = 0.96, and forest border vs. forest r 2 = 0.94), with sand temperature at the forest border on average 1.0°C below that of the open sand, and 1.5°C above that at the forest (Patrício, Marques, et al., ). We estimated future sand temperatures using the equation: T sand = 0.94T air +3.04, r 2 = 0.60, p < 0.0001, n = 39, T sand = mean biweekly sand temperature at Poilão in the forest border habitat, T air = mean biweekly air temperature at Bissau, sample period = 1 March 2013 to 15 October 2014 (see Patrício, Marques, et al., ). We added to estimated sand temperatures the mean metabolic heating during the thermosensitive period (TSP; period during middle third of development, when sex is irreversibly defined), to estimate annual mean incubation temperatures during the TSP until 2100 (Godley, Broderick, Glen, & Hays, ).…”

“…We added to estimated sand temperatures the mean metabolic heating during the thermosensitive period (TSP; period during middle third of development, when sex is irreversibly defined), to estimate annual mean incubation temperatures during the TSP until 2100 (Godley, Broderick, Glen, & Hays, ). Metabolic heating during the TSP at Poilão is 0.5 ± 0.4°C SD (Patrício, Marques, et al., ).…”