Kristina Toderich

Environmental resilience of rangeland ecosystems: assessment drought indices and vegetation trends on arid and semi-arid zones of Central Asia

The Central Asian (CA) rangelands is a part of the arid and semi-arid ecological zones and spatial extent of drylands in CA (Tajikistan, Kazakhstan, Uzbekistan, Kyrgyzstan, and Turkmenistan) is vast. Projections averaged across a suite of climate models, as measured between 1950-2012 by Standardised Precipitation-Evapotranspiration Index (SPEI) estimated a progressively increasing drought risks across rangelands (Turkmenistan, Tajikistan and Uzbekistan) especially during late summer and autumn periods, another index: Potential Evapotranspiration (PET) indicated drought anomalies for Turkmenistan and partly in Uzbekistan (between 1950-2000). On this study, we have combined a several datasets of drought indices ( SPIE, PET, temperature_T°C and precipitation_P) for better estimation of resilience/non-resilience of the ecosystems after warming the temperature in the following five countries, meanwhile, warming of climate causing of increasing rating of degradations and extension of desertification in the lowland and foothill zones of the landscape and consequently surrounding experienced of a raising balance of evapotranspiration (ET0). The study concluded, increasing drought anomalies which is closely related with raising (ET0) in the lowland and foothill zones of CA indicated on decreasing of NDVI indices with occurred sandy and loamy soils it will resulting a loss of vegetation diversity (endangered species) and raising of wind speeds in lowlands of CA, but on regional level especially towards agricultural intensification (without rotation) it indicated no changes of greenness index. It was investigated to better interpret how vegetation feedback modifies the sensitivity of drought indices associated with raising tendency of air temperature and changes of cold and hot year seasons length in the territory of CA.

Monitoring of vegetation condition using the NDVI/ENSO anomalies in Central Asia and their relationships with ONI (very strong) phases

An investigation of temporal dynamics of El Niño–Southern Oscillation (ENSO) and spatial patterns of dryness/wetness period over arid and semi-arid zones of Central Asia and their relationship with Normalized Difference Vegetation Index (NDVI) values (1982-2011) have explored in this article. For identifying periodical oscillations and their relationship with NDVI values have selected El Nino 3.4 index and thirty years of new generation bi-weekly NDVI 3g acquired by the Advanced Very High Resolution Radiometer (AVHRR) satellites time-series data. Based on identification ONI (Oceanic Nino Index) is a very strong El Nino (warm) anomalies observed during 1982-1983, 1997-1998 and very strong La Nino (cool) period events have observed 1988-1989 years. For correlation these two factors and seeking positive and negative trends it has extracted from NDVI time series data as “low productivity period” following years: 1982-1983, 1997 -1998; and as “high productivity period” following years: 1988 -1989. Linear regression observed warm events as moderate phase period selected between moderate El Nino (ME) and NDVI with following periods:1986-1987; 1987-1988; 1991-1992; 2002-2003; 2009-2010; and moderate La Niña (ML) periods and NDVI (1998-1999; 1999-2000; 2007-2008) which has investigated a spatial patterns of wetness conditions. The results indicated that an inverse relationship between very strong El Nino and NDVI, decreased vegetation response with larger positive ONI value; and direct relationship between very strong La Niña and NDVI, increased vegetation response with smaller negative ONI value. Results assumed that significant impact of these anomalies influenced on vegetation productivity. These results will be a beneficial for efficient rangeland/grassland management and to propose drought periods for assessment and reducing quantity of flocks’ due to a lack of fodder biomass for surviving livestock flocks on upcoming years in rangelands. Also results demonstrate that a non-anthropogenic drivers of variability effected to land surface vegetation signals, understanding of which will be beneficial for efficient rangeland and agriculture management and establish ecosystem services in precipitation-driven drylands of Central Asia.