Narrowing the agronomic yield gap with improved nitrogen use efficiency: a modeling approach.

Improving nitrogen use efficiency (NUE) in the major cereals is critical for more sustainable nitrogen use in high-input agriculture, but our understanding of the potential for NUE improvement is limited by a paucity of reliable on-farm measurements. Limited on-farm data suggest that agronomic NUE (AE(N)) is lower and more variable than data from trials conducted at research stations, on which much of our understanding of AE(N) has been built. The purpose of this study was to determine the magnitude and causes of variability in AE(N) across an agricultural region, which we refer to as the achievement distribution of AE(N). The distribution of simulated AE(N) in 80 farmers' fields in an irrigated wheat system in the Yaqui Valley, Mexico, was compared with trials at a local research center (International Wheat and Maize Improvement Center; CIMMYT). An agroecosystem simulation model WNMM was used to understand factors controlling yield, AE(N), gaseous N emissions, and nitrate leaching in the region. Simulated AE(N) in the Yaqui Valley was highly variable, and mean on-farm AE(N) was 44% lower than trials with similar fertilization rates at CIMMYT. Variability in residual N supply was the most important factor determining simulated AE(N). Better split applications of N fertilizer led to almost a doubling of AE(N), increased profit, and reduced N pollution, and even larger improvements were possible with technologies that allow for direct measurement of soil N supply and plant N demand, such as site-specific nitrogen management.

Regional-scale assessment of soil salinity in the Red River Valley using multi-year MODIS EVI and NDVI.

The ability to inventory and map soil salinity at regional scales remains a significant challenge to scientists concerned with the salinization of agricultural soils throughout the world. Previous attempts to use satellite or aerial imagery to assess soil salinity have found limited success in part because of the inability of methods to isolate the effects of soil salinity on vegetative growth from other factors. This study evaluated the use of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery in conjunction with directed soil sampling to assess and map soil salinity at a regional scale (i.e., 10-10(5) km(2)) in a parsimonious manner. Correlations with three soil salinity ground truth datasets differing in scale were made in Kittson County within the Red River Valley (RRV) of North Dakota and Minnesota, an area where soil salinity assessment is a top priority for the Natural Resource Conservation Service (NRCS). Multi-year MODIS imagery was used to mitigate the influence of temporally dynamic factors such as weather, pests, disease, and management influences. The average of the MODIS enhanced vegetation index (EVI) for a 7-yr period exhibited a strong relationship with soil salinity in all three datasets, and outperformed the normalized difference vegetation index (NDVI). One-third to one-half of the spatial variability in soil salinity could be captured by measuring average MODIS EVI and whether the land qualified for the Conservation Reserve Program (a USDA program that sets aside marginally productive land based on conservation principles). The approach has the practical simplicity to allow broad application in areas where limited resources are available for salinity assessment.

Greater transportation energy and GHG offsets from bioelectricity than ethanol.

The quantity of land available to grow biofuel crops without affecting food prices or greenhouse gas (GHG) emissions from land conversion is limited. Therefore, bioenergy should maximize land-use efficiency when addressing transportation and climate change goals. Biomass could power either internal combustion or electric vehicles, but the relative land-use efficiency of these two energy pathways is not well quantified. Here, we show that bioelectricity outperforms ethanol across a range of feedstocks, conversion technologies, and vehicle classes. Bioelectricity produces an average of 81% more transportation kilometers and 108% more emissions offsets per unit area of cropland than does cellulosic ethanol. These results suggest that alternative bioenergy pathways have large differences in how efficiently they use the available land to achieve transportation and climate goals.

Combined climate and carbon-cycle effects of large-scale deforestation.

The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO(2) to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These simulations were performed by using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has a net cooling influence on Earth's climate, because the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. Although these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate.