Jiaqi Li

Wetland area and quality have continued to decline worldwide due to the combined impacts of global climate change and human activities, so there is a need for a scientific and standardized framework to assess wetland degradation risk and support conservation and restoration efforts. In this study, a wetland degradation risk assessment framework integrating pressure level and degradation level was developed and applied to the western Songnen Plain, one of China’s major marsh wetland regions, using data from 2000, 2010, and 2020. The results showed that: (1) anthropogenic activity intensity and wetland area change were the most influential indicators. The degradation risk index ranged from 0.20 to 0.68, with mean values of 0.52, 0.46, and 0.46 in 2000, 2010, and 2020, respectively, indicating a slight overall decline. (2) The pressure level increased from 0.56 to 0.59 from 2000 to 2020, suggesting a growing influence of external pressures. In the same period, the degradation level decreased from 0.34 to 0.30, reflecting a reduced effect of internal environmental conditions. (3) Spatially, medium-risk areas have expanded from 47.5% to 64.1% and became the dominant area, while high-risk areas remained relatively stable at 14–16%, whereas relatively high-risk areas decreased sharply from 33.87% to 6.29%. These results provide useful guidance for regional land management for sustaining ecological systems, and the proposed framework provides a transferable assessment logic for wetland degradation risk, but its application to other regions require local calibration of indicators, weights, thresholds, and validation datasets.

The ability of a general circulation model (GCM) to capture the variability of El Niño–Southern Oscillation (ENSO) is not only a scientific issue of climate model performance, but also critical for climate change and variability impact studies. Here, we assess 48 CMIP5 GCMs for their skill in simulating ENSO interdecadal variability and its teleconnection with precipitation globally. The results show that (1) only 22 out of 48 GCMs display interdecadal variability that is similar to the observations; (2) the ensemble of the 48 GCMs captures the ENSO–precipitation teleconnection at the global scale; (3) no single GCM can capture the observed ENSO–precipitation teleconnection globally; and (4) a GCM that can realistically simulate ENSO variability does not necessarily capture the ENSO-precipitation teleconnection, and vice versa. The results could also be used by climate change impact studies to select suitable GCMs, especially for regions with a statistically significant teleconnection between ENSO and precipitation, as well as for the comparison of CMIP5 and CMIP6.