Quantifying the loss mechanisms of nitrogen.
The increases in N use, with NUE reported to be between 33 to 50%, are contributing to higher worldwide N losses that impact air and water quality (Baligar et al. 2001; Raun and Johnson 1999; Follett et al. 1991; IPCC 1994). Although significant advances in the development of better nutrient management practices and new tools are now available to improve N management, we don't have one "silver bullet" solution. What we have are a series of solutions and tools that can be used for a set of specific climates, soils, and crops to improve NU and reduce losses to the environment (Delgado 2001b; Pate et al. 2001). This improvement in N management needs to be developed within the context of the N cycle, accounting for different flows and pathways, mechanisms for loss, and N cycling.
General Impacts from N Losses
Baligar et al. (2001) reported that the current use of N fertilizer in millions of metric tons is 2.1 (2.3 million t) for Africa; 12.6 (13.9 million t) for North and Central America; 2.4 (2.6million t) for South America; 44.9 (49.5 million t) for Asia; 14.5 (16.0 million t) for Europe; and 0.8 (0.9 million t) for Oceania. Raun and Johnson (1999) reported that total worldwide consumption of cereal is 49.7 million MT (54.8 million t) (which accounts for about 60% of the N use reported by the Food and Agriculture Organization (FAO) during 1996). Worldwide NUE for cereal was approximately 33% and the worldwide economic loss for the unaccounted N fertilizer (67%) was equivalent to 15.9 billion U.S. dollars (Raun and Johnson 1999).
Raun and Johnson (1999) assumed a cost of U.S. $0.48/kg of applied N ($0.22/ib) fertilizer, without accounting for the cost of handling or applying the unaccounted 29.8 million MT (32.8 million t) of N. If we assume that N is a limiting factor for most worldwide agroecosystems, and that only 19.9 million MT (21.9 million t) were taken up by cereals such as wheat (Triticum aestivum L.), corn (Zea mays L.), rice (Oriza sativa L.), barley (Hardeum vulgare L.), sorghum (Sorghum bicolor (L.) Moench), millet (Pennisetum glaucum (L.) R. Br.), oats (Avena sativa L.), and rye (Secale cerale L.), we could expect additional economic losses than the loss of 29.8 million MT (32.8 million t) of N fertilizer. There is great potential to improve NUE and reduce the losses that are not accounted for in cereal systems (Delgado 2001a & b; Pate et al. 2001). Management is becoming a key tool in reducing N loss in the environment (Delgado 2001a & b; Pate et al. 2001).
Table 1 shows an estimate for the economic losses across different regions, assuming an average cost of $0.66/kg ($0.30/lb) of N fertilizer. Worldwide economic losses will be 36.4 and 26.0 billion U.S. dollars, assuming NUE of 30 and 50%, respectively. Baligar et al. (2001) reported that the average use efficiencies for potassium (K) and phosphorous (P) are 40 and 10%, respectively. It is clear from Table 1 and from Baligar et al. (2001) and Raun and Johnson (1999) that improving nutrient use efficiencies even by 1% worldwide will save millions of U.S. dollars, Pate et al. (2001) reported the need to continue research and technical assistance to the land users and to continue the development of new tools and methods needed to provide producers with viable options for adapting voluntary management practices that increase NUE and reduce losses.
Anthropogenic activities that increase emissions of trace gases such as [N.sub.2]0 are contributing to the global warning effect (IPCC 1994). The reactions that control the emissions of N gases from soils are described in detail by Hutchinson (1995). In general, there are bigeochemical reactions taking place, such as mineralization of soil organic matter, and nitrification in the soil compartment. It is during these biogeochemical reactions that these transformations generate emissions of trace gases such as [N.sub.2]O/[NO.sub.x]. Nitrate can also be denitrified and lost as [N.sub.2]O/NO/[N.sub.2] gases to the atmosphere. Ammonia volatilization is another mechanism that contributes to the gaseous losses of N.
Depending on the scales and desired resolution, several techniques ranging from chambers (Hutchinson and Livingston 1993), micrometerological methods (Denmead and Raupach 1993), or aircrafts that can sample large areas (Desjardins et al. 1993) can be used to measure [NH.sub.3] [N.sub.2]O NO, and [NO.sub.2]. Several reviewers have discussed the advantages and disadvantages of these techniques. Chambers can be used to study plot treatments with scales of less than one meter (3.28 ft) (Hutchinson and Livingston 1993). Micrometerological techniques can be used to measure gas exchanges on horizontal scales from meters to kilometers (Denmead and Raupach 1993) and aircraft can measure gas exchange over agricultural regions (Desjardins et al. 1993).
Jamber et al. (1997) in a study in France, found that out of 280 kg N [ha.sup.-1] (250 lb N [ac.sup.-1]) applied to corn, 30 to 110 kg N [ha.sup.-1] (26.8 to 98.2 lb N [ac.sup.-1]) were lost atmospherically. Out of these gaseous losses the [NH.sub.3], NO, [N.sub.2]O, and [N.sub.2] were calculated to be 1,40, 14 and 46%, respectively. At this site there was a low potential for [NH.sub.3] gaseous loss, 0.3 to 1.1 kg of [NH.sub.3]-N [ha.sup-1] (0.3 to 1.0 lb [NH.sub.3]-N [ac.sup.-1]). The losses for the other gaseous pathways were higher, 12 to 44 kg NO-N [ha.sup.-1] (10.7 to 39.3 lb NO-N [ac.sup.-1); 4.2 to 15.4 kg [N.sub.2]0-N [ha.sub.-1] (3.8 to 13.8 lb [N.sub.2]O-N [ac.sub.-1); and 13.8 to 50.6 kg [N.sub.2]-N [ha.sup.-1] (12.3 to 45.2 lb [N.sub.2]-N [ac.sub.-1]') respectively. Although the [NH.sub.3]-N losses (0.3 to 1.1 kg N [ha.sub.-1]) (0.3 to 1.0 lb [NH.sub.3]-N [ac.sub.-1) were not as significant at this site, Peoples et al. (1995) reported that worldwide loss due to [NH.sub.3] volatilization is large, e specially from flooded rice systems in Asia and sugarcane fields in Australia. Management is a key factor in reducing these gaseous losses of N to increase NUE (Peoples et al. 1995; Shoji et al. 2001).
[N.sub.2]O and [N.sub.2]. Mosier et al. (1998) reported that the total [N.sub.2]0 emissions from natural and anthropogenic sources were 16.2 Tg N [y.sup.-1] (17.8 million t N [y.sup.-1]) (7.2 (7.9 million t N [y.sup.-1] anthropogenic vs. 9.0 (9.9 million N [y.sup.-1]) natural sources). From the anthropogenic sources, agricultural soils contributed 3.3 Tg N [y.sup.-1] (3.6 million t N [y.sup.-1]) more than the 2.1 Tg N [y.sup.-1] (2.3 million t N [y.sup.-1]) from cattle and feedlots. Using $0.66 per kg ($0.30 per lb) N, these losses from soils are equivalent to 2.2 billion U.S. dollars, higher than the equivalent 1.4 billion U.S. dollars lost worldwide from cattle and feedlots. The worldwide anthropogenic emissions of [N.sub.2]O are equivalent to a loss of 10.7 billion U.S. dollars. Even these emissions of trace gas N add up to significant economic losses from worldwide agricultural systems and to the global cycling of N.
Peoples et al. (1995) reported that potential denitrification is a function of the surface texture and drainage characteristics of soil. They estimated that poorly drained clay soils had a denitrification potential of 35%, seven times higher than the 5.5% for the well-drained sandy soils. Firestone and Davidson (1989) and Hutchinson (1995) described the reactions that control NO, [N.sub.2]O, and [N.sub.2] emissions from soils. It is difficult to detect emissions of [N.sub.2] from the denitrification process since the background atmospheric concentration is about 78%. Indirect methods based on acetylene or isotope [N.sup.15] techniques can be used to conduct accurate measurements. Mosier and Klemedtsson (1994) reviewed the use of acetylene and [N.sup.15] techniques for in situ flux measurements or intact core measurements in the laboratory. The [N.sub.2]O concentrations from air samples can be measured in a gas chromatograph equipped with a [Ni.sup.63] electron capture detector operated at 300 - 400[degrees]C (572 - 752[degrees]F) (Mosier and Mack 1980).
The acetylene technique is based on the discovery by Federova (1973) that the reduction from [N.sub.2]O to [N.sub.2] in the denitrification process can be inhibited with acetylene. Other scientists have used this discovery as well as the fact that atmospheric background concentrations for [N.sub.2]O are as low as 0.00003% to improve and develop new laboratory and in situ denitrification techniques. These techniques use acetylene to block this biogeochemical reaction and flow of [N.sub.2]O to N2, facilitating the detection of changes in [N.sub.2]O concentrations (Balderston et al. 1976; Yoshinari and Knowles 1976; Mosier and Klemedtsson 1994; Burton and Beauchamp 1984; Lindau et al. 1988; Ryden et al. 1987; Tiedje et al. 1989).
The [N.sup.15] isotope techniques have the advantage that the atom % [N.sup.15] concentration for air is 0.366%, a percentage frequently used as a reference value (Porter and Mosier 1992). Mulvaney and Kurtz (1982) used [N.sup.15] techniques to measure [N.sub.2]O emissions from soils, with a method that was first proposed by Hauck et al. (1958). With the [N.sup.15] isotope technique, total N and the atom % [N.sup.15] concentration can be measured in a mass spectrometer (Mulvaney 1988; Mulvaney and Vanden Heuvel, 1988; Mosier et al. 1986). Mosier and Klemetdsson (1994) describe the procedure of using a mass spectrometer to measure [N.sub.2] and [N.sup.15] atom % with formulas to calculate the losses due to denitrification.
These [N.sup.15] and acetylene techniques have been used extensively for soil cores collected from the field and brought into the laboratory or in field in situ studies (Aulakh et al. 1982; Parkin et al. 1984; Mosier and Klemedtsson 1994). The chamber method of Hutchinson and Mosier (1981) has been used for in situ measurements. The chamber method can be used to collect air from chambers inserted into anchors in the soil. Air samples are then taken to the laboratory for gas chromatograph analyses. When studying denitrification, it is important to consider the system. Mosier et al. (1990) and Buresh et al. (1993) reported that rice plants transport [N.sub.2] and [N.sub.2]O into the atmosphere from denitrification occurring in flooded rice fields.
The nitrification process can produce [NO.sub.x] and [N.sub.2]O gases. Patton et al. (1988a) reported that 60 to 80% of the [N.sub.2]O emitted from the Central Plains Experimental Range was from the nitrification process.
We can apply treatments to plots and quantify their effects on [N.sub.2]O fluxes for short and long term effects. For example, Delgado and Mosier (1996) reported that nitrification inhibitors and controlled release fertilizer reduce [N.sub.2]O emissions from irrigated barley systems of northeastern Colorado. Delgado et al. (1996b) reported that [N.sub.2]O losses from spring-applied [NH.sub.4][NO.sub.3] to an irrigated mountain meadow in Wyoming were about 5%. Mosier et al. (1996) showed that cultivation or a single application of N fertilizer increased [N.sub.2]O emissions compared to those from non disturbed sites and that this effect persisted for years. This effect is probably due to the higher N cycling of the applied N fertilizer in the most active compartments, the microbial biomass and particulate organic fraction (Delgado et al. 1996b).
[NO.sub.x] (NO and [NO.sub.2]). Delmas et al. (1997) reported that the dominant emissions of [NO.sub.x] (NO and [NO.sub.2]) are combustions of fossil fuels (50%), biomass burning (20%), and natural sources (soils and lightning with less than 30%). Davidson and Kingerlee (1997) reported that agricultural systems can contribute significantly to the global emissions of [NO.sub.x] and that the best estimate of NO emissions from soils was 21 Tg [NO.sub.x]-N [y.sup.-1] (23.1 million [NO.sub.x]-N [y.sup.-1]). It was not clear how much of this [NO.sub.x] is absorbed by plant canopies, or what the error term was for this global estimate. Skiba et al. (1997) reported that nitrification or urease inhibitors and use of [NH.sub.4][NO.sub.3] instead of urea could contribute to the reduction of [NO.sub.x] emissions from agricultural systems. If we assume that the [NO.sub.x] losses range from 10 to 21 Tg N [y.sup-1], (11.0 to 23.1 million t [NO.sub.x]-N [y.sup.-1]), the worldwide economic losses from the agricultural sector will be between 6.6 to 13.9 billion U.S. dollars, larger than the estimated [N.sub.2]O losses.
Emissions of [NO.sub.x] from agricultural systems can be measured with the flow-through method from Slemr and Seiler (1984) that uses a Teflon-lined chamber to inhibit the transformation of [NO.sub.x]. As with the Hutchinson and Mosier (1981) [N.sub.2]O method, the chamber used for the [NO.sub.x] measurements can be fixed to a PVC anchor. The atmospheric sample is measured with a portable Scintrex LMA-3 chemiluminescent instrument and LNC converter.
Martin et al. (1998) used this method and found that 1.3 kg [NO.sub.x]-N [ha.sup-1] [y.sup.-1] (1.2 lb [NO.sub.x]-N [ac.sup.-1] [y.sup.-1]) was lost from the Colorado shortgrass steppe, approximately ten times more than the [N.sub.2]O emissions. They concluded that mineralization was the main pathway for these [NO.sub.x] losses and that 3 to 4% of the mineralized N was lost as [NO.sub.x] emissions. These results agree with Hurchinson (1995), who reported that although NO is formed in the denitrification process, it is not considered a major product of denitrification. Hutchinson (1995) reported that the combined effect of high water content restricting NO diffusion to the atmosphere, with the further reduction of the NO into [N.sub.2]O and N2, limits the emissions of NO due to denitrification in the field. Martin et al. (1998) were in agreement with [NO.sub.x] micrometeorological measurements collected for this region.
[NH.sub.3]. Fertilizers and animal waste are a large source of [NH.sub.3] volatilization (Peoples et al. 1995). Peoples et al. (1995) reported large losses of the applied N fertilizer from the flooded rice systems of Australia, China, India, and the Philippines (45 - 78%) and from sugarcane systems in Australia (47 - 61%). The pH of the soils is critical for [NH.sub.3] volatilization, especially under flooded rice systems. Urea application broadcasted to a flooded rice system was reported to have 9% loss by [NH.sub.3] volatilization compare to a 30% [NH.sub.3] loss if the system was under a calcareous flooded soil (Peoples et al. 1995). Small grain systems such as barley, sorghum, and wheat usually receive broadcast applications and incorporation, with reported lower losses of [NH.sub.3] volatilization (< 20%).
Crops can also contribute to the [NH.sub.3] losses to the atmosphere. Several researchers reported [NH.sub.3] losses, especially during the senescence period (Hutchinson et al. 1972; Schjoerring et al. 1993; Parton et al. 1988b; Hooker et al. 1980; Francis et al. 1993a).
Loss of [NH.sub.3] volatilization from urea deposition in feedlots is high. Hutchinson et al. (1982) reported that about 50% of the total urea and 25% of the total N deposition from animal wastes in a feedlot from Northeastern Colorado was lost by [NH.sub.3] volatilization. They estimated that these [NH.sub.3] volatilization losses could contribute up to 50 kg N [ha.sup.-1] [y.sup.-1] (44.7 lb N [ac.sup.-1] [y.sup.-1]) to adjacent fields of a feedlot. If we assume that the [NH.sub.3] losses are in about the same range as the [NO.sub.x] losses (Parashar et al. 1998), the economic worldwide losses could be in the range of 6.6 to 13.9 billion U.S. dollars.
Volatilization of [NH.sub.3] from agricultural systems has been reviewed by several authors (Fox et al. 1996; Freney et al. 1981; Sharpe and Harper 1995; Wood et al. 2000). Ammonia volatilization losses from plants and/or fertilizers can be quantified with micrometeorological, static trap, enclosed chambers, and/or [N.sup.15] methods. The [NH.sub.3] samples collected by these methods can be measured by gas chromatograph or wet chemistry analysis with titration or flow colorimetric [NH.sub.4] analyses, depending on the methods and/or acid trap used. We can then use these methods to study the effect of management on [NH.sub.3] losses. For example, Fox et al. (1996) reported that the average [NH.sub.3] loss from surface-applied non incorporated urea, sprayed urea-[NH.sub.4] [NO.sub.3], and dribbled urea-[NH.sub.4][NO.sub.3] were 40, 22, and 17 kg N [ha.sup.-1], (35.7, 19.6, and 15.2 lb N [ac.sup.-1]), respectively.
One of the main flow pathways that contributes to N losses from agricultural systems is [NO.sub.3]-N leaching. It is almost impossible to eliminate [NO.sub.3]-N leaching due to irrigation and precipitation events (Pratt 1979). Factors such as soils and climate are reported to dominate leaching, but management has the potential to minimize [NO.sub.3]-N leaching losses (Delgado 2001a; Shaffer and Delgado 2002). With good management practices we could keep [NO.sub.3]-N leaching losses to a minimum even in sensitive irrigated sites (Smika et al. 1977; Hergert 1986; Westerman et al. 1988; Schepers et al. 1995; Thompson and Doerge 1996 a & b, Delgado et al. 2001a & b).
Since land use patterns have been correlated with underground water [NO.sub.3]-N concentrations (Hallberg 1989; Fletcher 1991; Juergens-Gschwind 1989), we need to continue the development of viable economic practices that will promote voluntary implementation and minimize [NO.sub.3]-N leaching (Ristau 1999; Pate et al. 2001; Delgado 2001b). Shaffer and Delgado (2002) presented the need to develop a national quantitatively based [NO.sub.3]-N leaching index. This index will utilize soils, climate, and management databases to quickly assess the [NO.sub.3]-N leaching losses. The index will have the capability of using Geographic Information Systems (GIS) for regional practices as well as site-specific leaching losses for different areas of a given field. For a detailed description of the essential components of a [NO.sub.3]-N leaching index, see Shaffer and Delgado (2002).
Nitrate leaching can be quantified by measuring its transport out of the root zone in a given soil profile. Leaching can be measured with weighing and non weighing lysimiters or with zero tension or tension samplers. For a description and comparison of the use of zero tension and tension samplers to study [NO.sub.3]-N leaching, see Magid and Christensen (1993). Since soil solutions are held in the soil in different tensions for the micropores (< 0.5 um); mesopores (< 100 um); and cracks and macropores (< 100 um); the user needs to consider his or her objectives when using zero and tension samplers. Magid and Christensen (1993) reported that if the objective is to measure the leaching of solutes, then zero tension solutes may be more accurate. If the objective is to study soil biogeochemical processes, tension samples may be more useful because they samples the solution from the micropores, where more chemical and biogeochemical transformations are taking place. They also reported that the non suction methods could be susceptible to bias, depending on the coincidence of high leaching events with high concentrations.
Owens et al. (1995), using a weighing lysimiter, reported that losses from a corn/soybean (Glycine max Merr.) rotation were significantly lower than those measured for a corn/corn rotation. Although the water percolation was the same for the corn/corn and soybean/corn rotations, when N fertilizer was applied only to the corn and credit for N cycling from the soybeans was accounted for, the corn/soybean rotation reduced the leaching losses by 24.5% during the corn period. This is another proof that management is a driving factor that can reduce [NO.sub.3]-N leaching losses in irrigated and non irrigated systems.
Another method that has been used to quantify [NO.sub.3]-N leaching losses is modeling. For more detail on how to apply these studies to commercial operations, see Delgado et al. 1998, Delgado et al. 2001a & b, and Shaffer and Delgado 2001. Beckie et al. (1994) used the LEACHM (Wagenet and Hutson 1989) and Nitrate Leaching and Economic Analysis Package, NLEAP (Shaffer et al. 1991) models to conduct simulation of water and [NO.sub.3]-N budgets and leaching. Both models simulated the transport and leaching of [NO.sub.3]-N, and simulated values correlated with observed values (Beckie et al. 1994). This method of using simulated [NO.sub.3]-N and soil water budgets has been used to evaluate the effect of best management practices on [NO.sub.3]-N leaching (Delgado 2001a). Other examples of available models that can be used to simulate [NO.sub.3]-N leaching are the Crop Estimation through Resource and Environmental Synthesis, CERES (Ritchie et al. 1985); Erosion Productivity Impact Calculator, EPIC (Williams et al. 1983); Nitrogen Tillage Residue Management, NTRM (Shaffer and Larson 1987); Root Zone Water Quality Model, RZWQM (Shaffer et al. 2000); and the Great Plains Framework for Agricultural Resource Management, GPFARM (Ascough et al. 2001). For additional information on other national and international models that simulate N dynamics and transport see Shaffer et al. (2001).
Off-site Transport of N by Wind and Water
Two of the main mechanisms for off-site transport of N are wind and water erosion. Although these mechanisms can be observed at all sites, drier regions are dominated by wind erosion while rain erosion predominates in humid regions. Legg and Meisinger (1982) calculated the national wind and water (N) erosion losses to be 0.9 and 3.6 millions of metric tons, (1.0 and 4.0 million t) respectively. This is equivalent to 0.6 and 2.4 billion U.S. dollars, respectively, in the United States alone. Although some of this eroded N will cycle and move to other agricultural fields, it may also impact water bodies and can be transported to the oceans or the Gulf of Mexico.
Wind erosive forces transport N attached to soil particles or tied in the organic matter. Fallow systems or systems that leave a small amount of crop residue after harvest are especially susceptible to significant erosion losses. The potential wind erosion can be estimated with the wind erosion equation (Woodruff and Siddoway 1965; Skidmore et al. 1970). Woodruff and Siddoway (1965) reported that the potential wind erosion is a function of the soil erodiblity index, a climatic factor, soil ridge roughness, a field length factor along the prevailing wind direction, and vegetative cover. Dabney et al. (2001) reported that winter cover crops can reduce wind erosion and conserve soil and water quality.
Wind erosion can affect yields and contribute to losses of N and soil organic matter from arid systems (Larney et al. 1998; Delgado et al. 2001b). Zobeck et al. (1989) reported that it is important to reduce the losses of the smallest and lightest soil fractions containing the largest quantities of nutrients. Studies for alternatives to reduce wind erosion and losses of nutrients and particles can be conducted in the laboratory or in the field with wind tunnels or portable wind tunnels by exposing the field to wind forces and catching the erodible material (Armbrust 1999). There are methods that can also be used with traps to assess the losses due to windstorms (Fryrear et al. 1991). Cihacewk et al. (1993) reported that wind erosion sediments can be a source of [NO.sub.3]-N for surface and groundwater.
Rain or irrigation kinetic forces can detach soil particles, increasing the suspension and transport of important components, soluble nutrients, and suspended soil organic matter out of the fields. The Revised Universal Soil Loss Equation is used to compute soil loss (RUSLE) (Wischmeir et al. 1965; Renard et al. 1997). Flow rates are important and can be measured with different techniques and methods, such as flumes, weirs, flow meters, tipping buckets, grab samples (volumes collected in a set of time), and collection of proportional flow (Barfield and Hirschi 1986; Bjorneberg and Kanwar 1993; Gast et al. 1978; Johnson 1942; Khan and Ong 1997; Zobisch et al. 1996; Zhao et al. 2001a & b; Truman 2001).
Rainfall simulators can be used to study the transport of soil and nutrients (N) by surface waters (Foster et al. 1982; Truman et al. 2001). Erosion studies can be conducted in the laboratory, on small plots, or in watersheds. Rochester et al. (1994) used the Coshocron-type runoff samplers and reported that although not significantly different, the average total runoff and total discharge of N and [NO.sub.3]-N was higher in compacted plots. Holt (1979) reported that residue management is important to reduce nutrient (N & P) losses due to wind or water erosion. Seta et al. (1993) reported that even though the concentration of [NO.sub.3]-N and [NH.sub.4] was higher in the non tillage treatment, the total losses were greater in the conventional tillage treatment, followed by chisel-plow tillage, then no tillage. The reason was that the mean runoff rate, total runoff volume, mean sediment concentration, and total soil losses were lower for the non tillage treatment than those measured for the chisel plow and conv entional tillage treatments.
The collected sediment and solution samples can be submitted to different measurements depending on the objectives. There are several ways to measure [NO.sub.3]-N and [NH.sub.4], ranging from different extractions to different methods of detection. The methods of detection range from ion electrode analyses, colorimetric techniques, microdifusion, steam distillation, and flow injection analyses (Keeney and Nelson 1982). For routine analyses the automated flow injection colorimetric method is very sensitive and preferred. Total N analyses in the samples can be quantified with wet-oxidation methods (Kjeldahl 1883) or dry-combustion methods (Dumas 1831). These methods, including five different variations of the Kjeldahl method, were described by Bremner and Mulvaney (1982). Stevenson (1982) described how to fractionate the organic N by different methods to determine the different forms of organic N (eg., amino sugar N, amino acid N). Several authors have described the methods to trace enriched [N.sup.15] and depl eted [N.sup.15] in the environment (Hauck and Bremner 1976; Hauck 1982; Porter and Mosier 1992).
Use of N Budgets and Isotopic [N.sup.15] Techniques
Legg and Meisinger (1982) reviewed the factors that affect soil N budgets and reported that shifts in land use and/or management will affect N dynamics. Changes such as cultivation of a native site, incorporation of manures as an input, and/or other management practices will shift the N dynamics, taking many years to achieve a steady state. These shifts in N dynamics and cycling have long term effects in trace gas emissions of [NO.sub.x] and [N.sub.2]O (Martin et al. 1998; Mosier et al. 1996) that are due to the higher N cycling and mineralization (Parton et al. 1988a; Delgado et al. 1996a). Even if N budgets are not in a steady state, we could use experimental designs with control or zero N fertilizer plots to assess the NUE and potential N losses for a management system. The NUE = [(nutrient uptake in N fertilized plots - nutrient uptake by control)/nutrient applied] * 100.
Nitrogen use efficiency will be an indication of the N recovered by the crop and the potential N losses. This method of calculating the NUE has some advantages and disadvantages. The N uptake by the control plots accounts for all N inputs from the system other than the N applied. One of the disadvantages was described as the Jenkinson effect (Jenkinson 1985), which states that the root system of the plants growing in the control plots is not as extensive as the root system of the fertilized plants. Additionally, the resulting NUE value will not necessarily mean that all the N that was not recovered was lost, especially when the crop rotation has shallower and more deeply rooted crops (Delgado et al. 1999; Delgado 2001a). To estimate the N losses from the system, we could account for the crop rotation and assume that the system is in a steady state. Leguminous crops can contribute to increase N cycling and NUE of the system. Winter cover crops that can scavenge residual soil [NO.sub.3]-N can also contribute to increase the system NUE. We need to use breeding programs to develop varieties with higher yield potential and higher NUE.
A precise method of tracing the fate and compartmentalization of N is the use of [N.sup.15] isotope techniques. Follett (2001) made a detailed analysis of [N.sup.15] techniques and methods measuring NUE. These [N.sup.15] techniques are very accurate and can be used to trace the fate, transport, compartmentalization, and loss of N from a system. Long term [N.sup.15] studies can be conducted to trace the fate of N over time (Delgado et al. 1996a).These techniques can be applied to cropping systems (Sanchez and Blackmer 1987; Sanchez et al. 1987; Westerman et al. 1972) or irrigated mountain meadows (Delgado et al. 1996b). The [N.sup.15] techniques can be used to study the effect of controlled release fertilizers or nitrification inhibitors (Delgado and Mosier 1996). They can also be used to trace emissions of trace gases or leaching of [NO.sub.3] (Chichester and Smith 1978).
Modeling of N Budgets, Dynamics, Transformation, and Losses to the Biosphere
Another method that can be used to investigate N dynamics and transformations and calculate N losses is modeling. There are several models that can be used to simulate N transformations and dynamics and N losses. Some of these models are NLEAP, LEACHM, CERES, EPIC, NTRM, RZWQM, and GPFARM. For additional information on these and/or other national and international models that simulate N dynamics, transport, and N losses, see Shaffer et al. (2001). For more details on how to design studies to evaluate N use efficiencies of commercial agricultural operations, see (Delgado et' al. 1998; Delgado et al. 2001a; Shaffer and Delgado 2001).
Computer models can potentially evaluate the effect of best management practices on NUE and losses (Delgado 2001a) and to calculate N budgets and losses in management zones (Delgado 1999; Delgado and Duke 2000; Delgado et al. 2001a). Nitrogen models that are easily accessible via the Internet will facilitate the development of a national [NO.sub.3]-N leaching index based on strong quantitative databases (Shaffer and Delgado 2002). Shaffer and Delgado (2002) recommended the framework for the development of a national [NO.sub.3]-N index. The index should be able to use databases to quickly calculate the potential for [NO.sub.3]-N losses, and if needed, to use detailed simulation steps based in GIS software handling local site-specific information. Models accessible through the Internet will assess and quantify N losses and potential management scenarios.
New Technology for Identifying Site-specific N Budgets and Losses
New technologies such as Geographic Information Systems, Differential Global Positioning System, Yield Monitors, new computer software, and remote sensing techniques can be used to identify site-specific N budgets and losses from the field. It is well documented that the N cycle in soils is spatially and temporally variable (Legg & Meisinger 1982; Jokela and Randall 1989; Francis et al. 1993b; Cahn et al. 1994; Cambardella et al. 1994). Landscape positions (e.g., catena, swale vs. backslope) are correlated with fertility and N cycling for the grain and grasslands of northeastern Colorado (Schimel et al. 1985, 1986; Delgado et al. 1996a; Ortega et al. 1997). It is important to consider the degree of variability observed in the field, since some researchers have reported that there is the potential to use precision farming for improvements in NUE (Redulla et al. 1996; Gorway et al. 1996; Hergert et al. 1996; Delgado 1999; Ferguson et al. 1996) while others found no advantages in using sitespecific N management practices (Everett and Pierce 1996).
To account for this variability, Fleming et al. (1999) recommended the use of management zones that consider yield history, soil color, topography, and past management experiences in developing N budgets and N application rates by zone, Delgado and Duke (2000) reported that soil texture is important in delineating management zones and that the areas with higher finer textured particle content had higher nutrient concentrations, higher residual soil [NO.sub.3]-N, higher soil organic matter, and higher potato tuber yields, compared with sandier areas. New technology can potentially be used to develop N budgets by zone for preplant and sidedressing applications (Fleming et al. 1999, Khosla et al. 2002) and fertigation during the growing season (King et al. 1996).
It has been reported that crops respond to this spatial variation, as reflected by the correlation between crop N status, sap [NO.sub.3]-N concentrations, and soil properties (Franzen et al. 1999; King et al. 1999; Delgado and Duke 2000; Khosla et al. 2002). This spatial correlation between soil properties, productivity, and NUE is one of the reasons why it will be difficult to maximize NUE by using a single mean N-soil test, single N-source budget, and single N-sink uptake (Delgado et al. 2001a; Khosla et al. 2002). Several researchers have demonstrated the potential of using management zones and new technologies to manage this variability and improve NUE (Fleming et al. 1999; Baush and Dikker 2001; Scharfet al. 2002; Khosla et al. 2002). If the variability is known, there is the potential to account for it when developing management zones to increase yields and improve NUE (Fleming et al. 1999; Khosla et al. 2002). Delgado and Duke (2000) reported that management zones will be dynamic; as soil properties ar e improved (e.g., correct acid pH) productivity may change, requiring changes in the delineation of the management zone due to increased yields in the initially lower yielding areas.
Remote sensing technology can be used to evaluate N status and fine tune N applications (Bausch and Dikker 2001; Scharfet al. 2002). With this new technology, we can evaluate N dynamics in systems using N management zones, increase the agrophysiological response of the crop, reduce N applications, and maintain higher yields. Remote sensing has been successful in identifying low N areas or areas with N deficiencies. Using reference strips and a series of algorithms, we can get close to quantifying the N needs (Bausch and Dikker 2001; Scharf et al. 2002).
Summary and Conclusions
To implement N management practices that maximize NUE, we need to understand the biogeochemistry of the N cycle across different agroecosystems. Soil N is the most dynamic of the essential nutrients undergoing chemical and biogeochemical transformations from organic N compounds (such as proteins in crop residues) to [NO.sub.3]-N, to gaseous [N.sub.2] in a relatively short amount of time. An understanding of the dynamics of N and how it is leaked and lost in systems will be vital to the development of effective nutrient management plans. [N.sup.15] isotope techniques can be used to trace the fate of N in these different flows and pathways. A less expensive alternative to [N.sup.15] is to use control treatments and quantify how the N flows are changed by best management practices when compared with background flows of N.
Increasing N use efficiency is difficult for several reasons. Irrigation and precipitation are two of the main causes of leaching and denitrification of [NO.sub.3]-N. Traditionally, best management practices are based on a uniform rate, assuming that N sources, N sinks, and the mechanisms for losses across the field are uniform. Even the dominant mechanism for N losses could change from higher leaching areas at the coarser gravelly areas of the fields to higher denitrification in areas with higher clay content and lower drainage that may be ponded or flooded. Crops may respond to this site-specific spatial variability of soil physical and chemical properties; yields (the N sink) may be correlated to these changes across these zones (Fleming et al. 1999; Delgado 1999; Khosla et al. 2002)
It is important to consider N budgets and account for site-specific credits, at least at a field level, when improving NUE. A more intensive N budget is to account for management zones within a field (Khosla et al. 2002). These credits can vary by region--Middle Atlantic (Bandel and Fox 1984), South Atlantic (Gilliam and Boswell 1984), East North Central (Welch 1984), West North Central (Peterson and Voss 1984), South Central (Tucker and Murdock 1984), Mountain (Westfall 1984), and Pacific (Rauschkolb et al. 1984)--or even within a region (eg. Mountain; Westfall 1984) or within a field (Khosla et al. 2002).
We need to continue improving N management practices that reduce the loss and maximize the uptake of applied N. This can be accomplished with a better synchronization of the available N to crop needs, minimizing the susceptibility of [NO.sub.3]-N to leaching and denitrification. We also need to better coordinate immobilization and N cycling in phase with N sinks to maximize the system NUE and N cycling sources. The variability of the N sources and sinks by zones needs to be managed to reduce N loss.
We need better and faster methods of determining when and how much N to apply during the growing season to reduce N availability and susceptibility to losses. Nitrogen should be applied in split applications, matched with the time of higher N demands by the crop. We need to develop varieties with higher N use efficiency. Sprinkler systems and drip irrigation systems can be used advantageously to apply N. The advantage of the drip irrigation system is higher since the N can be delivered at the zone of maximum uptake, the active root zone. Control release fertilizers have been reported to have high N recoveries when the release from the fertilizer is matched with the N sink by the crop (Shoji et al. 2001). New in situ N monitoring status and real time techniques such as remote sensing are promising in their potential use for determining N status and needs. We need to understand the mechanisms of N losses to continue developing best management practices, providing producers with viable options for increasing NUE (Pate et al. 2001).
Table 1 Nutrient use ([10.sup.6] metric tons) for different regions and estimated economic losses in billions of U.S. dollars. N Use (1) Level of NUE (2) 30% 50% 70% [10.sup.6] tons billions of U.S. dollars Africa 2.1 1.0 0.7 0.4 North/Central America 12.6 5.8 4.2 2.5 South America 2.4 1.1 0.8 0.5 Asia 44.9 20.7 14.8 8.9 Europe 14.5 6.7 4.8 2.9 Oceania 0.8 0.4 0.3 0.2 World 78.7 36.4 26.0 15.6 (1) Data from Baligar et al. (2001) (N fertilizer use) (2) Economic losses for farmers, assuming a cost of $ 0.66 per kg of applied N. In some situations the N losses may reduce yields, if N is one of the limiting factors. This cost does not include the cost of application or the economic loss due to lower yields, assuming a similar level of efficiency across regions.
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Jorge A. Delgado is a soil scientist at the U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS) Soil Plant Nutrient Research Unit, Fort Collins, Colorado.
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|Publication:||Journal of Soil and Water Conservation|
|Date:||Nov 1, 2002|
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