The effect of the El Nino Southern Oscillation on the reproductive frequency of eastern Pacific leatherback turtles

Pacific leatherback turtle Dermochelys coriacea populations have been declining precipitously. It has been suggested that fishery-associated mortality is the leading factor causing the decline; however, the sensitivity of leatherbacks to climate variability relative to their population ecology is unknown. We investigated the effects of interannual climate variability, as governed by the El Nino Southern Oscillation (ENSO), on leatherback nesting ecology. We used equatorial Pacific sea surface temperature (SST) anomaly data over various time scales derived from both moored buoys and remote satellites as signals of ENSO. We then incorporated these data into a remigration probability model for the largest nesting population of eastern Pacific leatherbacks at Parque Nacional Marino Las Baulas (PNMB), Costa Rica. Our results showed that nesting females of PNMB exhibited a strong sensitivity to ENSO, as reflected in their nesting remigration probabilities. Cool La Nina events corresponded with a higher remigration probability and warm El Nino events corresponded with a lower remigration probability. We suggest that productivity transitions at leatherback foraging areas in the eastern equatorial and south-eastern Pacific in response to El Nino/La Nina events result in variable remigration intervals and thus variable annual egg production. This phenomenon may render the eastern Pacific leatherback population more vulnerable to anthropogenic mortality than other populations. Synthesis and applications. Physical indices of environmental variation can be used to estimate the probability of leatherbacks remigrating to nest at PNMB. This type of modelling approach can be extremely useful for understanding the effects of climatic variation on the population dynamics of sea turtles. Our remigration probability model can be applied to any monitored sea turtle nesting population where nesting site fidelity and beach monitoring coverage remains high. This modelling approach can help nesting beach monitoring programmes forecast remigrant numbers based on prior climate data, and can further quantify anthropogenic mortality by validating survival estimates.