Drought-induced shift of a forest–woodland ecotone: Rapid landscape response to climate variation

In coming decades, global climate changes are expected to produce large shifts in vegetation distributions at unprecedented rates. These shifts are expected to be most rapid and extreme at ecotones, the boundaries between ecosystems, particularly those in semiarid landscapes. However, current models do not adequately provide for such rapid effects—particularly those caused by mortality—largely because of the lack of data from field studies. Here we report the most rapid landscape-scale shift of a woody ecotone ever documented: in northern New Mexico in the 1950s, the ecotone between semiarid ponderosa pine forest and piñon–juniper woodland shifted extensively (2 km or more) and rapidly (<5 years) through mortality of ponderosa pines in response to a severe drought. This shift has persisted for 40 years. Forest patches within the shift zone became much more fragmented, and soil erosion greatly accelerated. The rapidity and the complex dynamics of the persistent shift point to the need to represent more accurately these dynamics, especially the mortality factor, in assessments of the effects of climate change.

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.