Corn stover harvest N and energy budgets in central Iowa.

Harvesting corn stover removes N from the fields, but its effect on subsurface drainage and other N losses is uncertain. We used the Root Zone Water Quality Model (RZWQM) to examine N losses with 0 (NRR) or 50% (RR) corn residue removal within a corn and soybean rotation over a 10-yr period. In general, all simulations used the same pre-plant or post-emergence N fertilizer rate (200 kg ha-1 yr-1). Simulated annual corn yields averaged 10.7 Mg ha-1 for the post emergence applications (NRRpost and RRpost), and 9.5 and 9.4 Mg ha-1 yr-1 for NRRpre and RRpre. Average total N input during corn years was 19.3 kg N ha-1 greater for NRRpre compared to RRpre due to additional N in surface residues, but drainage N loss was only 1.1 kg N ha-1 yr-1 greater for NRRpre. Post-emergence N application with no residue removal (NRRpost) reduced average drainage N loss by 16.5 kg ha-1 yr-1 compared to pre-plant N fertilization (NRRpre). The farm-gate net energy ratio was greatest for RRpost and lowest for NRRpre (14.1 and 10.4 MJ output per MJ input) while greenhouse gas intensity was lowest for RRpost and highest for NRRpre (11.7 and 17.3 g CO2-eq. MJ-1 output). Similar to published studies, the simulations showed little difference in N2O emissions between scenarios, decreased microbial immobilization for RR compared to NRR, and small soil carbon changes over the 10-yr simulation. In contrast to several previous modeling studies, the crop yield and N lost to drain flow were nearly the same between NRR and RR without supplemental N applied to replace N removed with corn stover. These results are important to optimizing the energy and nitrogen budgets associated with corn stover harvest and for developing a sustainable bioenergy industry.

N loss to drain flow and N2O emissions from a corn-soybean rotation with winter rye.

Anthropogenic perturbation of the global nitrogen cycle and its effects on the environment such as hypoxia in coastal regions and increased N2O emissions is of increasing, multi-disciplinary, worldwide concern, and agricultural production is a major contributor. Only limited studies, however, have simultaneously investigated NO3- losses to subsurface drain flow and N2O emissions under corn-soybean production. We used the Root Zone Water Quality Model (RZWQM) to evaluate NO3- losses to drain flow and N2O emissions in a corn-soybean system with a winter rye cover crop (CC) in central Iowa over a nine year period. The observed and simulated average drain flow N concentration reductions from CC were 60% and 54% compared to the no cover crop system (NCC). Average annual April through October cumulative observed and simulated N2O emissions (2004-2010) were 6.7 and 6.0kgN2O-Nha-1yr-1 for NCC, and 6.2 and 7.2kgNha-1 for CC. In contrast to previous research, monthly N2O emissions were generally greatest when N loss to leaching were greatest, mostly because relatively high rainfall occurred during the months fertilizer was applied. N2O emission factors of 0.032 and 0.041 were estimated for NCC and CC using the tested model, which are similar to field results in the region. A local sensitivity analysis suggests that lower soil field capacity affects RZWQM simulations, which includes increased drain flow nitrate concentrations, increased N mineralization, and reduced soil water content. The results suggest that 1) RZWQM is a promising tool to estimate N2O emissions from subsurface drained corn-soybean rotations and to estimate the relative effects of a winter rye cover crop over a nine year period on nitrate loss to drain flow and 2) soil field capacity is an important parameter to model N mineralization and N loss to drain flow.

Calculating the detection limits of chamber-based soil greenhouse gas flux measurements.

Renewed interest in quantifying greenhouse gas emissions from soil has led to an increase in the application of chamber-based flux measurement techniques. Despite the apparent conceptual simplicity of chamber-based methods, nuances in chamber design, deployment, and data analyses can have marked effects on the quality of the flux data derived. In many cases, fluxes are calculated from chamber headspace vs. time series consisting of three or four data points. Several mathematical techniques have been used to calculate a soil gas flux from time course data. This paper explores the influences of sampling and analytical variability associated with trace gas concentration quantification on the flux estimated by linear and nonlinear models. We used Monte Carlo simulation to calculate the minimum detectable fluxes (α = 0.05) of linear regression (LR), the Hutchinson/Mosier (H/M) method, the quadratic method (Quad), the revised H/M (HMR) model, and restricted versions of the Quad and H/M methods over a range of analytical precisions and chamber deployment times (DT) for data sets consisting of three or four time points. We found that LR had the smallest detection limit thresholds and was the least sensitive to analytical precision and chamber deployment time. The HMR model had the highest detection limits and was most sensitive to analytical precision and chamber deployment time. Equations were developed that enable the calculation of flux detection limits of any gas species if analytical precision, chamber deployment time, and ambient concentration of the gas species are known.

Rye cover crop and gamagrass strip effects on NO3 concentration and load in tile drainage.

A significant portion of the NO3 from agricultural fields that contaminates surface waters in the Midwest Corn Belt is transported to streams or rivers by subsurface drainage systems or "tiles." Previous research has shown that N fertilizer management alone is not sufficient for reducing NO3 concentrations in subsurface drainage to acceptable levels; therefore, additional approaches need to be devised. We compared two cropping system modifications for NO3 concentration and load in subsurface drainage water for a no-till corn (Zea mays L.)-soybean (Glycine max [L.] Merr.) management system. In one treatment, eastern gamagrass (Tripsacum dactyloides L.) was grown in permanent 3.05-m-wide strips above the tiles. For the second treatment, a rye (Secale cereale L.) winter cover crop was seeded over the entire plot area each year near harvest and chemically killed before planting the following spring. Twelve 30.5x42.7-m subsurface-drained field plots were established in 1999 with an automated system for measuring tile flow and collecting flow-weighted samples. Both treatments and a control were initiated in 2000 and replicated four times. Full establishment of both treatments did not occur until fall 2001 because of dry conditions. Treatment comparisons were conducted from 2002 through 2005. The rye cover crop treatment significantly reduced subsurface drainage water flow-weighted NO3 concentrations and NO3 loads in all 4 yr. The rye cover crop treatment did not significantly reduce cumulative annual drainage. Averaged over 4 yr, the rye cover crop reduced flow-weighted NO3 concentrations by 59% and loads by 61%. The gamagrass strips did not significantly reduce cumulative drainage, the average annual flow-weighted NO3 concentrations, or cumulative NO3 loads averaged over the 4 yr. Rye winter cover crops grown after corn and soybean have the potential to reduce the NO3 concentrations and loads delivered to surface waters by subsurface drainage systems.

Manure composition of swine as affected by dietary protein and cellulose concentrations.

An experiment was conducted to investigate the effects of reducing dietary CP and increasing dietary cellulose concentrations on manure DM, C, N, S, VFA, indole, and phenol concentrations. Twenty-two pigs (105 kg initial BW) were fed diets containing either 14.5 or 12.0% CP, in combination with either 2.5 or 8.7% cellulose. Pigs were fed twice daily over the 56-d study, with feed intake averaging 2.74 kg/d. Feces and urine were collected after each feeding and added to the manure storage containers. Manure storage containers were designed to provide a similar unit area per animal as found in industry (7,393 cm2). Before sampling on d 56, the manure was gently stirred to obtain a representative sample for subsequent analyses. An interaction of dietary CP and cellulose was observed for manure acetic acid concentration, in that decreasing CP lowered acetic acid in pigs fed standard levels of cellulose but increased acetic acid in pigs fed greater levels of cellulose (P = 0.03). No other interactions were noted. Decreasing dietary CP reduced manure pH (P = 0.01), NH4 (P = 0.01), isovaleric acid (P = 0.06), phenol (P = 0.05), and 4-ethyl phenol (P = 0.02) concentrations. Increasing dietary cellulose decreased pH (P = 0.01) and NH4 (P = 0.07) concentration but increased manure C (P = 0.03), propionic acid (P = 0.01), butyric acid (P = 0.03), and cresol (P = 0.09) concentrations in the manure. Increasing dietary cellulose also increased manure DM (P = 0.11), N (P = 0.11), and C (P = 0.02) contents as a percentage of nutrient intake. Neither cellulose nor CP level of the diet affected manure S composition or output as a percentage of S intake. Headspace N2O concentration was increased by decreasing dietary CP (P = 0.03) or by increasing dietary cellulose (P = 0.05). Neither dietary CP nor cellulose affected headspace concentration of CH4. This study demonstrates that diets differing in CP and cellulose content can significantly impact manure composition and concentrations of VFA, phenol, and indole, and headspace concentrations of N(2)O, which may thereby affect the environmental impact of livestock production on soil, air, and water.

Effect of land use on methane flux from soil.

The precise effects of natural and disturbed terrestrial systems on the atmospheric CH4 pool are uncertain. This study was conducted to quantify and compare CH4 fluxes from a variety of ecosystems in central Iowa. We investigated agricultural systems under different management practices, a hardwood forest site, native and restored prairies, and a municipal landfill. Flux measurements were obtained using a closed-chamber method, and measurements were compiled by sampling over the 1993 and 1994 growing seasons. In 1993, most of the agricultural sites were net CH4 producers with cumulative CH4 fluxes ranging from -0.02 to 3.19 g m(-2) over the 258-d sampling season, while the natural ecosystems were net CH4 consumers, with cumulative seasonal fluxes ranging from -0.27 to -0.07 g m-2 258 d(-1). In 1994, only the landfill and the agricultural site treated with broadcast liquid swine manure (LSM) were net CH4 producers, while the remainder of the natural and agricultural ecosystems were net CH4 consumers, with mean seasonal flux rates ranging from -0.43 to -0.008 g m(-2) 271 d(-1). We hypothesize that the differences in CH4 fluxes between the two years are due to differences in rainfall. To illustrate the integration between land use and CH4 flux, we computed an area-weighted soil CH4 flux for the state of Iowa. Our calculations yielded a net average soil CH4 flux of 139,000 Mg CH4 for 1993 and 1994.

Methane oxidation and production activity in soils from natural and agricultural ecosystems.

Methane (CH4) flux from soil to the atmosphere is the result of two microbial processes, methanogenesis and CH4 oxidation. Land use may have a profound impact on the relative activities of these groups of organisms. In this study, the CH4 production and consumption potentials of soils from agricultural and nonagricultural ecosystems were assessed in laboratory incubations. Methane production potentials of most soils were low and in the range of 0.02 to 0.35 nmol CH4 g soil(-1) h(-1); however, soils from two of the agricultural sites that experience periodic water saturation had CH4 production potentials from 100 to 300 nmol CH4 g soil(-1) h(-1). The high methanogenic potential suggests that CH4 consumers may not be wholly dependent on atmospheric CH4 for their survival and maintenance. The prairie soils exhibited the highest CH4 oxidation under ambient atmospheric CH4 concentrations, and CH4 oxidation activity was markedly enhanced in incubations with an atmosphere enriched in CH4. This stimulated CH4 oxidation activity was generally greater in the agricultural soils as compared with the forest and prairie soils. Methane oxidation appeared to be related to soil nitrogen status. Under ambient atmospheric CH4 concentrations, CH4 oxidation was negatively related to soil mineral N (NO2- + NO3- + NH4+) concentration. However, a positive relationship between soil mineral N status and CH4 oxidation activity was observed in incubations with atmospheres enriched in CH4. This pattern suggests that the agricultural lands contain different populations of CH4 oxidizers than the natural systems.

Stochastic models of soil denitrification.

Soil denitrification is a highly variable process that appears to be lognormally distributed. This variability is manifested by large sample coefficients of variation for replicate estimates of soil core denitrification rates. Deterministic models for soil denitrification have been proposed in the past, but none of these models predicts the approximate lognormality exhibited by natural denitrification rate estimates. In this study, probabilistic (stochastic) models were developed to understand how positively skewed distributions for field denitrification rate estimates result from the combined influences of variables known to affect denitrification. Three stochastic models were developed to describe the distribution of measured soil core denitrification rates. The driving variables used for all the models were denitrification enzyme activity and CO(2) production rates. The three models were distinguished by the functional relationships combining these driving variables. The functional relationships used were (i) a second-order model (model 1), (ii) a second-order model with a threshold (model 2), and (iii) a second-order saturation model (model 3). The parameters of the models were estimated by using 12 separate data sets (24 replicates per set), and their abilities to predict denitrification rate distributions were evaluated by using three additional independent data sets of 180 replicates each. Model 2 was the best because it produced distributions of denitrification rate which were not significantly different (P > 0.1) from distributions of measured denitrification rates. The generality of this model is unknown, but it accurately predicted the mean denitrification rates and accounted for the stochastic nature of this variable at the site studied. The approach used in this study may be applicable to other areas of ecological research in which accounting for the high spatial variability of microbiological processes is of interest.

Adaptation of Denitrifying Populations to Low Soil pH.

Natural denitrification rates and activities of denitrifying enzymes were measured in an agricultural soil which had a 20-year past history of low pH (pH ca. 4) due to fertilization with acid-generating ammonium salts. The soil adjacent to this site had been limed and had a pH of ca. 6.0. Natural denitrification rates of these areas were of similar magnitude: 158 ng of N g of soil day for the acid soil and 390 ng of N g of soil day at the neutral site. Estimates of in situ denitrifying enzyme activity were higher in the neutral soil, but substantial enzyme activity was also detected in the acid soil. Rates of nitrous oxide reduction were very low, even when NO(3) and NO(2) were undetectable, and were ca. 400 times lower than the rates of N(2)O production from NO(3). Denitrification rates measured in slurries of the acid and neutral soil showed distinctly different pH optima (pH 3.9 and pH 6.3) which were near the pH values of the two soils. This suggests that an acid-tolerant denitrifying population had been selected during the 20-year period of low pH.