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Climate change (CC) may pose a challenge to agriculture and rural livelihoods in Central Asia, but in-depth studies are lacking. To address the issue, crop growth and yield of 14 wheat varieties grown on 18 sites in key agroecological zones of Kazakhstan, Kyrgyzstan, Uzbekistan and Tajikistan in response to CC were assessed. Three future periods affected by the two projections on CC (SRES A1B and A2) were considered and compared against historic ((1961-1990) figures. The impact on wheat was simulated with the CropSyst model distinguishing three levels of agronomic management. Averaged across the two emission scenarios, three future periods and management scenarios, wheat yields increased by 12% in response to the projected CC on 14 of the 18 sites. However, wheat response to CC varied between sites, soils, varieties, agronomic management and futures, highlighting the need to consider all these factors in CC impact studies. The increase in temperature in response to CC was the most important factor that led to earlier and faster crop growth, and higher biomass accumulation and yield. The moderate projected increase in precipitation had only an insignificant positive effect on crop yields under rainfed conditions, because of the increasing evaporative demand of the crop under future higher temperatures.However, in combination with improved transpiration use efficiency in response to elevated atmospheric CO 2 concentrations, irrigation water requirements of wheat did not increase. Simulations show that in areas under rainfed spring wheat in the north and for some irrigated winter wheat areas in the south of Central Asia, CC will involve hotter temperatures during flowering and thus an increased risk of flower sterility and reduction in grain yield. Shallow groundwater and saline soils already nowadays influence crop production in many irrigated areas of Central Asia, and could offset productivity gains in response to more beneficial winter and spring temperatures under CC.Adaptive changes in sowing dates, cultivar traits and inputs, on the other hand, might lead to further yield increasesi.

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Land use and agricultural practices can result in important contributions to the global source strength of atmospheric nitrous oxide (N 2 O) and methane (CH 4 ). However, knowledge of gas flux from irrigated agriculture is very limited. From April 2005 to October 2006, a study was conducted in the Aral Sea Basin, Uzbekistan, to quantify and compare emissions of N 2 O and CH 4 in various annual and perennial land-use systems: irrigated cotton, winter wheat and rice crops, a poplar plantation and a natural Tugai (floodplain) forest. In the annual systems, average N 2 O emissions ranged from 10 to 150 lg N 2 O-N m À2 h À1 with highest N 2 O emissions in the cotton fields, covering a similar range of previous studies from irrigated cropping systems. Emission factors (uncorrected for background emission), used to determine the fertilizer-induced N 2 O emission as a percentage of N fertilizer applied, ranged from 0.2% to 2.6%. Seasonal variations in N 2 O emissions were principally controlled by fertilization and irrigation management. Pulses of N 2 O emissions occurred after concomitant N-fertilizer application and irrigation. The unfertilized poplar plantation showed high N 2 O emissions over the entire study period (30 lg N 2 O-N m À2 h À1 ), whereas only negligible fluxes of N 2 O (o2 lg N 2 O-N m À2 h À1 ) occurred in the Tugai. Significant CH 4 fluxes only were determined from the flooded rice field: Fluxes were low with mean flux rates of 32 mg CH 4 m À2 day À1 and a low seasonal total of 35.2 kg CH 4 ha À1 . The global warming potential (GWP) of the N 2 O and CH 4 fluxes was highest under rice and cotton, with seasonal changes between 500 and 3000 kg CO 2 eq. ha À1 . The biennial cotton-wheat-rice crop rotation commonly practiced in the region would average a GWP of 2500 kg CO 2 eq. ha À1 yr À1 . The analyses point out opportunities for reducing the GWP of these irrigated agricultural systems by (i) optimization of fertilization and irrigation practices and (ii) conversion of annual cropping systems into perennial forest plantations, especially on less profitable, marginal lands. 20 0 S A J J M S A J J M Fig. 2 CH 4 and N 2 O flux rates of the rice plot from May to September 2005 and 2006. Arrows indicate the events of N (kg N ha À1 ) application to the plots (U, urea; AN, ammonium nitrate; AP, ammonium phosphate). Error bars indicate the standard error.

Increased knowledge about the spatial distribution of cotton (Gossypium hirsutum L.) yield in the Khorezm region in Uzbekistan supports the optimal allocation of resources. This research estimated the spatial distribution of cotton yields in Khorezm by integrating remote sensing, field data, and modeling. The agro‐meteorological model used was based on Monteith's biomass production model with multitemporal MODIS (Moderate Resolution Imaging Spectroradiometer)‐derived parameters from 2002 as primary inputs. The photosynthetically active radiation (PAR) and environmental stress scalars on crop development were estimated with meteorological information. Using high‐spatial‐resolution Landsat 7 ETM+ images, the cotton area was extracted and the cotton fraction determined within the coarse spatial resolution MODIS pixels. The spatial resolution of the MODIS FPAR data was improved by using an empirical relationship to the higher‐resolution MODIS NDVI (Normalized Difference Vegetation Index) data. The estimated raw cotton yield ranged from 1.09 to 3.76 Mg ha−1. The modeling revealed a spatial trend of higher yields in upstream areas and in locations closer to the irrigation channels and lower yields in downstream areas and at sites more distant to the channels. The validated yield estimations showed a 10% deviation from official governmental statistics. The established agro‐meteorological model based on freely available MODIS data and a minimum of field data input is a promising technique for economic and operational late‐season estimation of spatially distributed cotton yield over large regions on which management adjustments could be made.