Ongoing global warming has triggered extreme climate events of increasing magnitude and frequency. Under this effect, a series of extreme climate events such as drought and increased rainfall during the El Nino Southern Oscillation (ENSO) are expected to be amplified in the coming years. Adequate mapping of regions with climate-sensitive vegetation and its associated time lag is required for appropriate mitigation planning to avoid potential negative ecological impacts towards vegetation. In this study, ENSO and climate indicator time series data, for example, Multivariate ENSO Index (MEI) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) data for rainfall were linked with long-term time series vegetation proxies from remote sensing (RS proxies). ENSO- and rainfall-sensitive areas were identified from each RS proxy using the bivariate Granger test, and the areas identified by multiple RS proxies were taken to identify climate-sensitive regions in Indonesia. Of the biome types in Indonesia, savanna was the most sensitive, with approximately 53% of the total savanna area in Indonesia shown to be sensitive to ENSO and rainfall by two or more RS proxies. Rolling correlation analysis also found that the ENSO effect on the vegetation region after rainfall was positively correlated with the RS proxies with a time lag of +5 months. Therefore, rainfall can be taken as a proxy of the effects of ENSO on the temporal dynamics of sensitive vegetation regions in Indonesia.

The dynamics of aboveground biomass (AGB) are driven by both climate variation and anthropogenic modification, however, few studies have evaluated the relative importance of these two drivers, especially in a heterogeneous landscape. Taking the Mongolian Plateau as a case study and employing the vegetation optical depth retrieval as a proxy of AGB, this study aimed to determine the relative importance of climatic and anthropogenic drivers on the dynamics of AGB in Mongolia (ML) and the Inner Mongolia Autonomous Region (IM), China. Spatial panel data model specific to each agro-ecological zone was employed to fulfill the task. The results revealed that: (1) Since the socio-institutional transition in the early 1990s, AGB declined in most parts of the grazing zone of Mongolia. The reduction of precipitation, the rise of temperature and the intensification of livestock grazing were the major drivers behind it. Ranked by their relative importance, the order in the grazing zone with relatively humid climate was: Precipitation ≈ temperature > livestock grazing; the order in the grazing zone with relatively arid climate was: Precipitation > temperature > livestock grazing; (2) Since the implementation of a series of ecological restoration programs in the early 2000s, AGB increased in most parts of the grazing zone of IM, and the increase of precipitation was the dominant driver behind it; (3) Since the early 2000s, AGB increased in most parts of the grazing-farming zone of IM. The increase of precipitation, the decline of temperature and the intensification of grain production were the major drivers behind it. Ranked by their relative importance, the order was: Precipitation > grain production > temperature; (4) Since the early 2000s, AGB increased in most parts of the farming zone of IM. The increase of precipitation and the intensification of grain production were the major drivers behind it. Ranked by their relative importance, the order was: Grain production > precipitation.