Agricultural practices are believed to be the major anthropogenic source of enhanced nitrous oxide (N 2 O) gas emissions in New Zealand. Studies conducted in New Zealand generally suggest low N 2 O emission from pasture; however, there is little information for arable farming systems. This paper evaluates tillage and land use effects on N 2 O emissions using a closed chamber technique at an Ohakea silt loam (Gleyic luvisol) where winter oats (Avena sativa L.)/fodder maize (Zea mays L.) was double-cropped for 5 years. The tillage types included conventional tillage (CT) and no-tillage (NT) systems, and a permanent pasture (PP) was used as a control.Spatial variability in all treatments showed large inherent variations in N 2 O fluxes (a mean CV = 119%), which reflected natural soil heterogeneity, and perhaps the measurement technique used rather than the real differences due to the tillage and cropping systems evaluated. On an annualised basis, N 2 O emissions measured from December 1998 to September 1999 from the PP (1.66 kg N 2 O-N/ha per year or 19 g N 2 O-N/(m 2 h)) were significantly lower than the CT and NT fields averaging at 9.20 (or 105) and 12.0 (or 137) kg N 2 O-N/ha per year (or g N 2 O-N/(m 2 h)), respectively. However, there were no differences in N 2 O emission rates between the CT and NT treatments. Seedbed preparation using a power harrow which followed within a few days of first ploughing the CT field reduced N 2 O emissions by 65% within the first hour after power harrowing. However, N 2 O emission rates returned to the pre-power harrowing levels at the next sampling period, which was 1 month later.There was a strong relationship between log-transformed data of soil water content (SWC) and N 2 O emissions in all treatments with r = 0.73, 0.75 and 0.86 for the PP, CT and NT treatments, respectively. Seasonal variations in N 2 O emission from the PP were in the order of winter = autumn > summer. Although fluxes in the CT were higher in winter than in the autumn season, there were no differences between the summer and autumn data. The seasonal variations in N 2 O emission in the NT treatment were in the order of winter > autumn = summer.

Abstract:Cropland abandonment is globally widespread and has strong repercussions for regional food security and the environment. Statistics suggest that one of the hotspots of abandoned cropland is located in the drylands of the Aral Sea Basin (ASB), which covers parts of post-Soviet Central Asia, Afghanistan and Iran. To date, the exact spatial and temporal extents of abandoned cropland remain unclear, which hampers land-use planning. Abandoned land is a potentially valuable resource for alternative land uses. Here, we mapped the abandoned cropland in the drylands of the ASB with a time series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from [2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014][2015][2016]. To overcome the restricted ability of a single classifier to accurately map land-use classes across large areas and agro-environmental gradients, "stratum-specific" classifiers were calibrated and classification results were fused based on a locally weighted decision fusion approach. Next, the agro-ecological suitability of abandoned cropland areas was evaluated. The stratum-specific classification approach yielded an overall accuracy of 0.879, which was significantly more accurate (p < 0.05) than a "global" classification without stratification, which had an accuracy of 0.811. In 2016, the classification results showed that 13% (1.15 Mha) of the observed irrigated cropland in the ASB was idle (abandoned). Cropland abandonment occurred mostly in the Amudarya and Syrdarya downstream regions and was associated with degraded land and areas prone to water stress. Despite the almost twofold population growth and increasing food demand in the ASB area from 1990 to 2016, abandoned cropland was also located in areas with high suitability for farming. The map of abandoned cropland areas provides a novel basis for assessing the causes leading to abandoned cropland in the ASB. This contributes to assessing the suitability of abandoned cropland for food or bioenergy production, carbon storage, or assessing the environmental trade-offs and social constraints of recultivation.

Inefficient irrigation and the excessive use of water on agricultural land in the Aral Sea Basin over several decades have led to saline soils. The main objective of this paper is to identify the environmental predictors to model the spatial distribution of soil salinity in a highly irrigated landscape. Soil salinity at farm scale was measured in the topsoil (Total Dissolved Solids, TDS) and down to a depth of 1.5 m by electromagnetic conductivity meter (CMv) over a regular grid covering an area of approximately 15 km 2 in Khorezm Province, Uzbekistan. Six nested samplings within selected grids were conducted to reveal short-distance variation. Apart from widely-used terrain indices and those acquired from remote sensing, data on distance to drainage channels and long-term average groundwater observations were used to account for local parameters possibly influencing soil salinity. Topsoil salinity (TDS) was seen to be highly variable even at short distances (40 m) compared to average bulk soil salinity (CMv). CMv readings were better correlated with factors obtained from remote sensing and distance to drains than TDS. This might be attributable to the fact that topsoil salts are dynamic in nature, and land management practices (e.g. leaching, cultivation, and irrigation) might have contributed considerably to spatial variation. The CMv shows the average amount of salt within a larger soil volume and to greater depth and is less affected by land management than topsoil salinity, which is reflected in the TDS. Most terrain indices showed a low correlation with topsoil and bulk salinity. There was a strong indication that the effects of water management are dominant and tend to outweigh the effects of environmental factors. The very low R 2 for relationship of TDS with environmental factors is evidence that taking TDS samples close to the soil surface is not a good way to assess salinity trends in irrigated land. These findings have important implications for salinity survey methods on flat irrigated terrain: CMv seems to be a more reliable predictor than environmental proxy factors, even if the latter are easier to determine.

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Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km(2)) results were used to upscale soil salinity to a district area (∼300 km(2)). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m(-1)). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated.