El Niño and the related phenomenon Southern Oscillation (ENSO): The largest signal in interannual climate variation

El Niño and the related phenomenon Southern Oscillation (ENSO) is the strongest signal in the interannual variation of ocean-atmosphere system. It is mainly a tropical event but its impact is global. ENSO has been drawing great scientific attention in many international research programs. There has been an observational system for the tropical ocean, and scientists have known the climatologies of the upper ocean, developed some theories about the ENSO cycle, and established coupled ocean-atmosphere models to give encouraging predictions of ENSO for a 1-year lead. However, questions remain about the physical mechanisms for the ENSO cycle and its irregularity, ENSO-monsoon interactions, long-term variation of ENSO, and increasing the predictive skill of ENSO and its related climate variations.

Corticosterone levels predict survival probabilities of Galápagos marine iguanas during El Niño events

Plasma levels of corticosterone are often used as a measure of “stress” in wild animal populations. However, we lack conclusive evidence that different stress levels reflect different survival probabilities between populations. Galápagos marine iguanas offer an ideal test case because island populations are affected differently by recurring El Niño famine events, and population-level survival can be quantified by counting iguanas locally. We surveyed corticosterone levels in six populations during the 1998 El Niño famine and the 1999 La Niña feast period. Iguanas had higher baseline and handling stress-induced corticosterone concentrations during famine than feast conditions. Corticosterone levels differed between islands and predicted survival through an El Niño period. However, among individuals, baseline corticosterone was only elevated when body condition dropped below a critical threshold. Thus, the population-level corticosterone response was variable but nevertheless predicted overall population health. Our results lend support to the use of corticosterone as a rapid quantitative predictor of survival in wild animal populations.