NESTING ECOLOGY OF THE GREEN TURTLE (LINNAEUS, 1758) IN COASTAL KENYA.

Abstract

During the past several decades there has been a general global decline in sea turtle populations attributed either directly or indirectly to anthropogenic and climate change effects. Relatively little is known regarding the preferences turtles may have for some nesting beaches over others but the information is necessary for conservation of populations. The objective of this study was therefore to determine the nesting ecology of the green turtle, Chelonia mydas, in selected beaches in coastal Kenya. Nesting patterns and hatching success of Chelonia mydas were monitored in the year 2012 on nine beaches on the northern coast of Kenya. The number of nests deposited during the year, hatching success, and spatial nesting patterns were monitored in the beaches for twelve months during 2012. At the nesting beaches, samples of sand were analyzed for grain sizes, moisture content, pH and conductivity and the relationships between nest abundance, hatching success and these variables analyzed through linear regressions, multiple stepwise regression and CART analysis. Peak nesting occurred in March (25 nests) and October (26 nests) with nesting rates varying between beaches. Spatial variation was observed in nest densities with a range of 0.4 to 6.7 nests per km among the beaches. The mean clutch size did not vary significantly among sites (Kruskal-Walis: χ2o.5, 8 = 13.57; p = 0.09), so was the variation in mean clutch size between months pooled for all sites (Kruskal-Wallis: χ20.5, 11 = 13.38; p=0.26). Results of a Kruskal-Wallis test did not show any significant difference in mean monthly hatching success among sites for the in situ clutches (Kruskal-Wallis: χ20.5, 11 = 17.86; p = 0.09). The in situ incubated eggs had higher hatching rate than translocated ones (U = 547, p = <0.0001). The pH, clutch size, distance from high tide line (HTL) and moisture content at sites were identified as important variables in partitioning the variance in hatching success of the green turtle following CART analysis. However, results of stepwise multiple regression identified only clutch size as a significant predictor of hatching success (F = 4.93, p = 0.03). Conductivity and moisture content were identified as important predictors of whether nesting abundance would be low, medium or high at sites following a Classification Tree Analysis. Results of this study should provide useful information on the nesting ecology of the green turtle for modeling spatial variability and for management of this endangered species in the Kenyan coast.