Investigation of the factors affecting the hatching success of the green turtle (chelonia mydas) hatchlings

The Green Turtle (Chelonia mydas) is classified as "Endangered" on a global scale according to the IUCN Red List, while the Mediterranean subpopulation is listed as "Near Threatened." Understanding nest parameters is of critical importance for the conservation of the species. This study was conducted on the Sugözü Beaches in Ceyhan, Adana, and investigated the relationship between hatching success and various parameters, including nesting date, distance of the nest from vegetation and the sea, nest temperature, nest depth, nest moisture, incubation period, and clutch size. According to Spearman's rho analysis, a negative correlation was found between nesting date and incubation period (rho = -0.57), a positive correlation between distance from vegetation and moisture (rho = 0.46), and a negative correlation between distance from vegetation and distance from the sea (rho = -0.38). Two principal component analysises (PCA1–PCA2) was also performed. In PCA1, nesting date showed a negative relationship with nest depth, distance from vegetation, and incubation period on the same factor, while distance from the sea and clutch size appeared to be independent. In PCA2, nesting date and incubation period were related with the first component; nest depth, distance from the sea and vegetation, and moisture were related with the second component; and distance from vegetation and the sea, nest temperature, and clutch size were found to be negatively related with the third component. Among the three beta regression models developed, the most suitable one was selected based on its AIC value (-13.59) and pseudo-R² (0.324) values. The results indicate that nests laid earlier in the season, deeper, cooler, and with shorter incubation periods exhibited higher hatching success. The mean nest temperature in this study (30.5°C) is within the highest observed hatching success. Beta regression analysis facilitates the interpretation of such multivariate conditions and provides important insights for conservation strategies. Multidimensional data evaluation is recommended for future research.