Advancing land degradation in the irrigated areas of Central Asia hinders sustainable development of this predominantly agricultural region. To support decisions on mitigating cropland degradation, this study combines linear trend analysis and spatial logistic regression modeling to expose a land degradation trend in the Khorezm region, Uzbekistan, and to analyze the causes. Time series of the 250-m MODIS NDVI, summed over the growing seasons of 2000–2010, were used to derive areas with an apparent negative vegetation trend; this was interpreted as an indicator of land degradation. About one third (161,000 ha) of the region’s area experienced negative trends of different magnitude. The vegetation decline was particularly evident on the low-fertility lands bordering on the natural sandy desert, suggesting that these areas should be prioritized in mitigation planning. The results of logistic modeling indicate that the spatial pattern of the observed trend is mainly associated with the level of the groundwater table (odds = 330 %), land-use intensity (odds = 103 %), low soil quality (odds = 49 %), slope (odds = 29 %), and salinity of the groundwater (odds = 26 %). Areas, threatened by land degradation, were mapped by fitting the estimated model parameters to available data. The elaborated approach, combining remote-sensing and GIS, can form the basis for developing a common tool for monitoring land degradation trends in irrigated croplands of Central Asia.

Extensive degradation of irrigated croplands, due to increasing soil salinity and depletion of soil nutrient stocks, is a major problem in Central Asia (CA), one of the largest irrigated areas in the world. To assess the potential for improving the productive capacity of degraded lands by afforestation, we examined N₂ fixation of Elaeagnus angustifolia L. in mixed plantations with non-fixing Populus euphratica Oliv. and Ulmus pumila L. Fixation of N₂ was quantified by the ¹⁵N natural abundance technique based on both foliar and whole-plant sampling during five consecutive growing seasons. Despite elevated root-zone soil salinity (6–10 dS m⁻¹) and deficiency in plant-available P (4–15 mg kg⁻¹), N₂ fixation (%Ndfa) increased from an initial value of 20% to almost 100% over 5 years. Within each growing season, %Ndfa steadily increased and peaked in the fall. Annual N₂ fixation, determined using foliar δ¹⁵N, initially averaged 0.02 Mg ha⁻¹, peaked at 0.5 Mg ha⁻¹ during the next 2 years and thereafter stabilized at 0.3 Mg ha⁻¹. Estimates based on whole-plant δ¹⁵N were <10% lower than those based on foliar δ¹⁵N. The increase in plant-available soil N was significantly higher in E. angustifolia plots than in P. euphratica and U. pumila plots. Increases in the concentrations of organic C (19%), total N (21%) and plant-available P (74%) in the soil were significant irrespective of tree species. This improvement in soil fertility is further evidence that afforestation with mixed-species plantations can be a sustainable land use option for the degraded irrigated croplands in CA.

Understanding the complex diversity of species and their potential uses in traditional agroforestry systems is crucial for enhancing the productivity of tropical systems and ensuring the sustainability of the natural resource base. The aim of this study is the evaluation of the role of home gardens and parklands, which are prominent tropical agroforestry systems, in the conservation and management of biodiversity. Our study quantified and compared the diversity of woody and herbaceous perennial species and their uses in traditional home gardens and parkland agroforestry systems under a sub-humid climate in western Ethiopia. A sociological survey of 130 household respondents revealed 14 different uses of the species, mostly for shade, fuelwood, food, and as traditional medicine. Vegetation inventory showed that the Fisher’s α diversity index and species richness were significantly higher in home gardens (Fisher’s α = 5.28 ± 0.35) than in parklands (Fisher’s α = 1.62 ± 0.18). Both systems were significantly different in species composition (Sørenson’s similarity coefficient = 35%). The differences occurred primarily because of the high intensity of management and the cultivation of exotic tree species in the home gardens, whereas parklands harbored mostly native flora owing to the deliberate retention and assisted regeneration by farmers. In home gardens, Mangifera indica L. was the most important woody species, followed by Cordia africana Lam. and Coffea arabica L. On the other hand, Syzygium guineense Wall. was the most important species in parklands, followed by C. africana and M. indica. The species diversity of agroforestry practices must be further augmented with both indigenous and useful, non-invasive exotic woody and herbaceous species, particularly in parklands that showed lower than expected species diversity compared to home-gardens.

Despite rapid advances and large-scale initiatives in forest mapping, reliable cross-border information about the status of forest resources in Central Asian countries is lacking. We produced consistent Central Asia forest cover (CAFC) maps based on a cost-efficient approach using multi-resolution satellite imagery from Landsat and MODIS during 2009–2011. The spectral-temporal metrics derived from 2009–2011 Landsat imagery (overall accuracy of 0.83) was used to predict sub-pixel forest cover on the MODIS scale for 2010. Accuracy assessment confirmed the validity of MODIS-based forest cover map with a normalized root-mean-square error of 0.63. A general paucity of forest resources in post-Soviet Central Asia was indicated, with 1.24% of the region covered by forest. In comparison to the CAFC map, a regional map derived from MODIS Vegetation Continuous Fields tended to underestimate forest cover, while the Global Forest Change product matched well. The Global Forest Resources Assessments, based on individual country reports, overestimated forest cover by 1.5 to 147 times, particularly in the more arid countries of Turkmenistan and Uzbekistan. Multi-resolution imagery contributes to regionalized assessment of forest cover in the world’s drylands while developed CAFC maps (available at https://data.zef.de/) aim to facilitate decisions on biodiversity conservation and reforestation programs in Central Asia.

Accurate monitoring of land surface dynamics using remote sensing is essential for the synoptic assessment of environmental change. We assessed a Medium Resolution Imaging Spectrometer (MERIS) full resolution dataset for vegetation monitoring as an alternative to the more commonly used Moderate-Resolution Imaging Spectroradiometer (MODIS) data. Time series of vegetation indices calculated from 300 m resolution MERIS and 250 m resolution MODIS datasets were analyzed to monitor vegetation productivity trends in the irrigated lowlands in Northern Uzbekistan for the period 2003–2011. Mann-Kendall trend analysis was conducted using the time series of Normalized Differenced Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and MERIS-based Terrestrial Chlorophyll Index (MTCI) to detect trends and examine the capabilities of each sensor and index. The methodology consisted of (1) preprocessing of the original imagery; (2) processing and statistical analysis of the corresponding time series datasets; and (3) comparison of the resulting trends. Results confirmed the occurrence of widespread vegetation productivity decline, ranging from 5.5% (MERIS-MTCI) to 21% (MODIS-NDVI) of the total irrigated cropland in the study area. All indices identified the same spatial patterns of decreasing vegetation. Average vegetation index values of NDVI and SAVI were slightly higher when measured by MERIS than by MODIS. These differences merit further investigation to allow a fusion of these datasets for consistent monitoring of cropland productivity decline at scales suitable for guiding operational land management practices.