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The PhenoCam network is collecting color and near infrared images year-round using cameras in fixed positions on agricultural lands including a site located on the Swan Lake Research Farm. The network effort was initiated in 2015 at this long-term, plot-scale research site. The camera at the research farm on focused a plot-scale, replicated research study that was established in 1997 to assess the long-term impacts of various tillage management options on soil organic carbon. Initially the study included eight tillage treatments: no-tillage, moldboard + disk tillage, chisel tillage, and fall and spring residue management, with or without strip-tillage and strip-tillage + sub-soiling. In 2004, the number of treatments were reduced to no-tillage, moldboard tillage, and fall and spring residue management without strip-tillage. All tillage treatments also had an early or late planting date. In 2008, the strip-tillage plots were modified to explore alternative strategies for supporting cellulosic bioenergy feedstock production, including planting of cellulosic feedstock. The modification included adding perennials grasses into an extended 6-year rotation, winter cereal rye cover crops in a corn-soybean rotation, and an alternative Sorghum-Sudan grass hybrid forage system. Detailed soil and crop properties data have been collected from this site. This site is designated to be continued as part of the LTAR "common experiment" comparing agricultural and environmental results from "business as usual" and "aspirational best practices.
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ASRU Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Sidney, Montana Information is needed to mitigate dryland soil greenhouse gas (GHG) emissions by using novel management practices. We evaluated the effects of cropping sequence and N fertilization on dryland soil temperature and water content at the 0- to 15-cm depth and surface CO2, N2O, and CH4 fl uxes in a Williams loam (fi ne-loamy, mixed, superactive, frigid, Typic Argiustolls) in eastern Montana. Treatments were no-tilled continuous malt barley (Hordeum vulgaris L.) (NTCB), no-tilled malt barley–pea (Pisum sativum L.) (NTB–P), and conventional-tilled malt barley–fallow (CTB–F) (control), each with 0 and 80 kg N ha–1. Gas fl uxes were measured at 3 to 14 d intervals using static, vented chambers from March to November 2008 to 2011. Soil temperature varied but water content was greater in CTB–F than in other treatments. The GHG fl uxes varied with date of sampling, peaking immediately after substantial precipitation (>15 mm) and N fertilization during increased soil temperature. Total CO2 fl ux from March to November was greater in NTCB and NTB–P with 80 kg N ha–1 than in other treatments from 2008 to 2010. Total N2O fl ux was greater in NTCB with 0 kg N ha–1 and in NTB–P with 80 kg N ha–1 than in other treatments in 2008 and 2011. Total CH4 uptake was greater with 80 than with 0 kg N ha–1 in NTCB in 2009 and 2011. Because of intermediate level of CO2 equivalent of GHG emissions and known favorable effect on malt barley yield, NTB–P with 0 kg N ha–1 might mitigate GHG emissions and sustain crop yields compared to other treatments in eastern Montana. For accounting global warming potential of management practices, however, additional information on soil C dynamics and CO2 associated with production inputs and machinery use are needed. 2008, greater in cropping than in fallow phases, and greater in NTCB than in NTB-F. Tillage did not infl uence crop biomass and CO2 fl ux but N fertilization had a variable eff ect on the fl ux in 2008. Similarly, soil total C content was not infl uenced by treatments. Annual cropping increased CO2 fl ux compared with crop–fallow probably by increasing crop residue returns to soils and root and rhizosphere respiration. Inclusion of peas in the rotation with malt barley in the no-till system, which have been known to reduce N fertilization rates and sustain malt barley yields, resulted in a CO2 fl ux similar to that in the CTB-F sequence.
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Bioenergy Cropping Systems Study for Resilient Economic Agricultural Practices in Mandan, North Dakota Rigorous economic analyses are crucial for the successful launch of lignocellulosic bioenergy facilities in 2014 and beyond. Our objectives are to (1) introduce readers to a query tool developed to use data downloaded from the Agricultural Research Service (ARS) REAPnet for constructing enterprise budgets and (2) demonstrate the use of the query tool with REAPnet data from two field research sites (Ames, IA, and Mandan, ND) for evaluating short-term economic performance of various biofuel feedstock production strategies. Our results for both sites showed that short-term (<3 years) impacts on grain profitability were lower at lower average annual crop residue removal rates. However, it will be important to monitor longer term changes to see if grain profitability declines over time and if biomass harvest degrades soil resources. Analyses for Iowa showed short-term breakeven field-edge biomass prices of $26–$42 Mg−1 among the most efficient strategies, while results for North Dakota showed breakeven prices of $54–$73 Mg−1. We suggest that development of the data query tool is important because it helps illustrate several different soil and crop management strategies that could be used to provide sustainable feedstock supplies.
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The LTAR network maintains stations for standard meteorological measurements including, generally, air temperature and humidity, shortwave (solar) irradiance, longwave (thermal) radiation, wind speed and direction, barometric pressure, and precipitation. Many sites also have extensive comparable legacy datasets. The LTAR scientific community decided that these needed to be made available to the public using a single web source in a consistent manner. To that purpose, each site sends data on a regular schedule, as frequently as hourly, to the National Agricultural Library, which has developed a web service to provide the data to the public in tabular or graphical form.
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On-Farm Residue Removal Study for Resilient Economic Agricultural Practices in Morris, Minnesota Interest in harvesting crop residues for energy has waxed and waned since the oil embargo of 1973. Since the at least the late 1990’s interest has been renewed due to concern of peak oil, highly volatile natural gas prices, replacing fossil fuel with renewable sources and a push for energy independence. The studies conducted on harvesting crop residues during the 1970’s and1980’s focused primarily on erosion risk and nutrient removal as a result early estimates of residue availability focused on erosion control (Perlack et al., 2005). More recently, the focus has expanded to also address harvest impacts on soil organic matter and other constraints (Wilhelm et al., 2007; Wilhelm et al., 2010). In West Central Minnesota, crop residues have been proposed a replacement for natural gas (Archer and Johnson, 2012) while nationally residues are also be considered for cellulosic ethanol production (US DOE, 2011). The objective of the on-farm study was to assess the impact of residue harvest on working farms with different management systems and soils. Indicators of erosion risk, soil organic matter, and crop productivity is response to grain plus cob, or grain plus stover compared to grain only harvest.
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Corn Residue Removal Plots Study for Resilient Economic Agricultural Practices in Florence, South Carolina None
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MaLi Fallow Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Mandan, North Dakota The ‘Management Strategies for Soil Quality’ study was established in 1993 by Dr. Don Tanaka (USDA-ARS-NGPRL) to evaluate long-term impacts of minimum and no-till cropping systems on crop yield, precipitation use, and soil properties. The study was designed with six crop sequences (whole plot) each split by tillage type (split plot). All phases of each crop sequence are present every year, and treatments are replicated three times. From: Liebig, T.M., J.R.Gross, S.L. Kronberg, R.L. Phillips, J.D. Hanson. 2010. Grazing management contributions to net global warming potential: A long-term evaluation in the northern great plains. J Env Q. 39 (3):799-809. Materials and Methods Site description Experimental sites were located within the Temperate Steppe Ecoregion of the USA (Bailey, 1995). This ecoregion possesses a semiarid continental climate, with evaporation typically exceeding precipitation in any given year. Specifically, sites were within the Missouri Plateau approximately 6 km south of Mandan, North Dakota, USA (46º 46’ 12” N, 100º 55’ 59” W). Average annual precipitation at the sites from 1913 to 2003 was 410 mm and long-term growing season precipitation (Apr. – Sept.) was 330 mm. Average annual temperature was 4°C, though daily averages ranged from 21°C in the summer to -11°C in the winter. The average frost-free period at the sites was 131 days. The sites were on gently rolling uplands (0-3% slope) with a silty loess mantle overlying Wisconsin age till. Predominant soils were Temvik-Wilton silt loams (FAO: Calcic Siltic Chernozems; USDA: Fine-silty, mixed, superactive, frigid Typic and Pachic Haplustolls) (Soil Survey Staff, 2009). A survey of select soil properties conducted prior to initiating the study has been reviewed elsewhere (Liebig et al., 2006). Description of grazing treatments.Grazing treatments included two native vegetation pastures and one seeded forage pasture. The two native vegetation pastures included a moderately grazed pasture (MGP) and heavily grazed pasture (HGP), both of which were established in 1916. Vegetation composition within the MGP upon initiation of this study included a mixture of blue grama [Bouteloua gracilis (H.B.K.) Lag. Ex Griffiths], needle-and-thread (Stipa comata Trin. and Rupr.), western wheatgrass [Pascopyrum smithii (Rybd) Löve], prairie junegrass [Koeleria pyramidata (Lam) Beauv.], Kentucky bluegrass (Poa pratensis L.), and sedge (Carex filifolia Nutt. and Carex heliophila Mack.). Within HGP, blue grama and sedge were the dominant plant species. A crested wheatgrass [Agropyron desertorum (Fisch. ex. Link) Schult.] pasture (CWP) represented the seeded forage, which was planted in 1932 into plowed native range. In addition to crested wheatgrass, a small amount of blue grama was present in the CWP. The grazing treatments varied in size, with MGP, HGP, and CWP occupying 15.4, 2.8, and 2.6 ha, respectively. Per standard protocol for the establishment of experimental treatments prior to widespread use of statistics, none of the grazing treatments were replicated (Sarvis, 1923). The grazing season for all three pastures extended from about mid-May to early-October using yearling steers. Stocking rates for MGP and HGP were 2.6 and 0.9 ha steer-1 (0.39 and 1.1 animals ha-1), respectively. Stocking rates within CWP were 0.4 ha steer-1 (2.3 animals ha-1) in late-spring/early-summer and 0.9 ha steer-1 (1.2 animals ha-1) for the remainder of the grazing season. Grazing has occurred every year since pasture establishment except during times of severe drought when forage production was inadequate to support livestock grazing. To increase forage production, CWP was fertilized in the fall of each year since 1963 with NH4NO3 at 45 kg N ha-1. Of the three grazing treatments, MGP and HGP are reflective of the predominant forms of grassland management in the northern Great Plains. Experimental setup Preparations for the experiment were initiated on 6 Oct. 2003 with the placement of six polyvinyl chloride (PVC) pipe anchors (19.6-cm i.d.; 15.2-cm height) in each grazing treatment. The anchors served as part of a two-piece chamber system for GHG analyses (described below). Anchors were oriented in a hexagonal pattern around the center of each grazing treatment. Distance between adjacent anchors was approximately 40 m in the MGP, and 10 m in the HGP and CWP. Treatment area covered within the six collars was 1.8 x 10-5 ha. Anchors were inserted into the soil to a depth of approximately 10 cm using a tractor-mounted Giddings hydraulic probe (Giddings Machine Co., Windsor, CO). A carpenter’s level was used during collar insertion to ensure each anchor was level on north-south and east-west axes. Following insertion, headspace within each anchor was determined by lining the space within an anchor with plastic wrap and filling it with a known volume of water until the water level was flush with the upper edge of the anchor. Vegetation within each anchor was not removed during the evaluation unless it was grazed by livestock. Soil sample collection and analysesOn 7 Oct. 2003, soil samples were collected from four locations in each grazing treatment, approximately equidistant between anchors 1 and 2, 1 and 6, 3 and 4, and 4 and 5. Soil samples were collected to 100 cm in depth increments of 0 to 5, 5 to 10, 10 to 20, 20 to 30, 30 to 60, and 60 to 100 cm using a tractor-mounted Giddings hydraulic probe with an inner tip diameter of 3.5 cm. At each location, eight soil cores at 0 to 5 and 5 to 10 cm, four soil cores at 10 to 20 and 20 to 30 cm, and two soil cores at 30 to 60 and 60 to 100 cm were collected and composited by depth. Each sample was saved in a double-lined plastic bag and placed in cold storage at 5ºC until processing. Soil samples were dried at 35ºC for 3 to 4 d and ground by hand to pass a 2.0 mm sieve. Identifiable plant material (> 2.0 mm) was removed during sieving. Air-dry water content was determined for each sample using a 12 to 15 g subsample by measuring the difference in mass before and after drying at 105ºC for 24 hr. Samples were analyzed for total soil C and N by dry combustion on soil ground to pass a 0.106 mm sieve (Nelson and Sommers, 1996). Using the same fine-ground soil, inorganic C was measured on soils with a pH = 7.2 by quantifying the amount of CO2 produced using a volumetric calcimeter after application of dilute HCl stabilized with FeCl2 (Loeppert and Suarez, 1996). Soil organic C (SOC) was calculated as the difference between total C and inorganic C. Gravimetric data were converted to a volumetric basis for each sampling depth using field measured soil bulk density (Blake and Hartge, 1986). All data were expressed on an oven-dry basis. To assess grazing management effects on SOC over time, archived soil from a 1959 sampling of the grazing treatments (reviewed by Liebig et al., 2008b) was subsampled and analyzed as outlined above. While information on protocol from the 1959 sampling is limited, inspection of the sample descriptions indicated multiple locations in each of the grazing treatments were sampled to a depth of 60.9 cm in increments of 0 to 15.2, 15.2 to 30.5, and 30.5 to 60.9 cm. Specifically, nine locations were sampled in MGP and HGP (resulting in 27 total samples each), while 30 locations were sampled in CWP (resulting in 90 total samples). Given discrepancies in depth increments between the 1959 and 2003 samplings and lack of soil bulk density data from 1959, volumetric expression of SOC for the archive samples utilized soil bulk density values weighted by depth from the 2003 sampling for the respective grazing treatments (Table 1). Similarly, calculated values of SOC in 2003 were weighted to conform to depth increments used in 1959. To eliminate effects of sampling depth and soil bulk density on SOC stocks, data from the 1959 and 2003 samplings were recalculated on an equivalent mass basis assuming a soil profile mass of 7500 Mg ha-1 for each grazing treatment (Ellert and Bettany, 1995). The soil profile mass was selected based on the approximate soil mass in the upper 60.9 cm soil depth assuming a mean soil bulk density across grazing treatments of 1.22 Mg m-3. GHG analyses Fluxes of N2O and CH4 were measured in the grazing treatments from 21 Oct. 2003 to 24 Oct. 2006 employing static chamber methodology as outlined by Hutchinson and Mosier (1981). Within each treatment, gas samples were collected from two-part chambers consisting of six anchors (outlined above) each with a PVC cap (19.6-cm i.d.; 10.0-cm height), vent tube, and sampling port. Gas samples from inside the chambers were collected with a 20 mL syringe at 0, 15, and 30 min after installation (approximately 10:00 a.m. each sampling day). After collection, gas samples were injected into 12 mL evacuated Exetainer glass vials sealed with butyl rubber septa (Labco Limited, Buckinghamshire, UK). Concentration of N2O and CH4 inside each vial was measured by gas chromatography 1-3 d after collection using a Shimadzu GC-17A gas chromatograph (Shimadzu Scientific Instruments, Kyoto, Japan) attached to an ISCO Retriever IV autosampler (Teledyne Isco, Inc., Lincoln, NE). Using this system, each sample was auto-injected and split into two sample loops, with 1 mL directed to a thermal conductivity detector (TCD) in series with a flame ionization detector (FID) using ultra-pure He carrier gas. Ultra-pure He and hydrocarbon-free air were used for combustion in the FID. The second sample loop directed 0.5 mL to a 63Ni electron capture detector (ECD) with ultra-pure N2 as carrier gas. Prior to reaching each detector, samples passed through a 4-m HayeSep D column (Hayes Separations, Inc., Bandera, TX) for the TCD and FID, and 2-m Porapak Q (Waters Corp., Milford, MA) and 4-m HayeSep D columns for the ECD. The gas chromatograph was calibrated with a commercial blend of N2O (0.100, 0.401, 1.99 µL L-1) and CH4 (1.00, 2.09, 10.1 µL L-1) balanced in N2 from Scott Specialty Gases (Scott Specialty Gases, Plumsteadville, PA). Precision analysis expressed as coefficient of variation for 18 replicate injections of 0.401 µL N2O L-1 and 2.09 µL CH4 L-1 standards was 1.8 and 2.0%, respectively. Standard error associated with the precision analysis for each gas was ± 0.002 µL N2O L-1 and ± 0.008 µL CH4 L-1. Gas flux was calculated from the change in concentration in the chamber headspace over time (Hutchinson and Mosier, 1981). Measurements of gas fluxes were made one to two times per week when near-surface soil depths were not frozen or during mid-winter thawing periods. Otherwise, fluxes were measured every other week. Over the course of the evaluation gas fluxes were measured 128 times. Due to recurring problems with the FID, CH4 flux measurements were used only from 19 Jan. 2005 to 27 Sep. 2005 and 29 Nov. 2005 to 24 Oct. 2006, for a total of 73 measurements. Supplementary analyses Precipitation, air temperature, and solar radiation were monitored daily at a North Dakota Agricultural Weather Network (NDAWN) station within 1 km of the grazing treatments. Relevant data were downloaded following each gas sampling event from the NDAWN website (NDAWN, 2009). Near-surface soil water content and temperature were measured concurrently with gas flux when the soil was not frozen. Volumetric water content was measured in the surface 12 cm of soil using a time-domain reflectometry technique with a Campbell CS620 HydroSense System (Campbell Scientific, Inc., Logan, UT). Soil temperature was measured at a 6 cm depth with an Omega HH81A handheld digital thermometer attached to a heavy-duty T type thermocouple probe (Omega, Inc., Stamford, CT). Three measurements of soil water content and one measurement of soil temperature were made within 30 cm of each anchor during the 15 min gas sampling period. Values for volumetric water content were converted to water-filled pore space (WFPS) using field-measured soil bulk density for the surface 10 cm (Linn and Doran, 1984). Data analyses Given the lack of replication of the grazing treatments, anchors and sampling locations served as pseudo-replicates for measurements of gas flux, soil properties, and aboveground biomass (Gomez, 1984). While not ideal, justification for using this approach hinges upon the long-term value of the grazing treatments, the age of which makes them rare within North America. All collected data were analyzed using PROC MIXED in SAS (Littell et al., 1996) with grazing treatments and pseudo-replicates considered fixed and random effects, respectively. A significance criterion of P=0.05 was used to document differences among means. Variation of arithmetic means was expressed using standard error (Steel and Torrie, 1980). Where appropriate, associations between measured parameters were identified using Pearson correlation analysis. Gas flux data were tested for normality using skewness, kurtosis, and Kolmogorov-Smirnov coefficients before and after data were log-transformed. Data transformation did not improve normality of the data, so original gas flux data were used for statistical analyses. A mixed repeated measures model was used to analyze the effects of year, quarterly period (1 Dec. – 28/29 Feb., 1 Mar. – 31 May, 1 June – 31 Aug., and 1 Sep. – 30 Nov.), and grazing treatment on N2O and CH4 flux. Effects of soil temperature and WFPS on CH4 and N2O flux were also evaluated using a repeated measures model, but with a parsed data set including only sampling times when soil temperature and WFPS were measured. For both analyses, a time series covariance structure was used in the repeated measures model, where correlations decline over time (Phillips et al., 2009). Cumulative fluxes of N2O and CH4 were calculated by linearly interpolating data points and integrating the underlying area (Gilbert, 1987). Net GWP was calculated for each grazing treatment as the sum of emitted CO2 equivalents from five factors: Net GWP = NPA + EF + ?SOC + CH4F + N2OF where NPA was N fertilizer production and application; EF was CH4 emission from enteric fermentation; ?SOC was SOC change; CH4F was soil-atmosphere CH4 flux; and N2OF was soil-atmosphere N2O flux. The GWP for N fertilizer production was based on the applied N rate and an emission factor of 3.14 kg CO2 kg-1 N (West and Marland, 2002). Emission of CO2 associated with fertilizer N application (via a granular spreader and small tractor) was assumed to be 45.5 kg CO2 ha-1 (West and Marland, 2002). Daily CH4 emission via enteric fermentation from each steer was estimated at 179 g CH4 d-1 assuming a diet of ‘good pasture’ (Westberg et al., 2001). Differences in SOC stocks between the 1959 and 2003 samplings were taken to represent net soil-atmosphere CO2 and CH4 exchange for each grazing treatment. Soil organic C stocks determined by the equivalent soil mass approach were used for calculation. Contributions of soil-atmosphere CH4 and N2O flux to GWP were based on annual flux rates. For each factor contributing to GWP, the sum of CO2 equivalents was calculated assuming direct GWP of 1 kg CH4 ha-1 = 25 kg CO2 ha-1 and 1 kg N2O ha-1 = 298 kg CO2 ha-1 (100 year time horizon) (IPCC, 2007). Results for net GWP were expressed as kg CO2equiv. ha-1 yr-1. Global warming potential was related to animal productivity by dividing net GWP by mean annual weight gain ha-1 to estimate greenhouse gas intensity (GHGI) for each grazing treatment. Measurements of gas fluxes were made one to two times per week when near-surface soil depths were not frozen or during mid-winter thawing periods. Otherwise, fluxes were measured every other week. Over the course of the evaluation gas fluxes were measured 128 times. Due to recurring problems with the FID, CH4 flux measurements were used only from 19 Jan. 2005 to 27 Sep. 2005 and 29 Nov. 2005 to 24 Oct. 2006, for a total of 73 measurements. Supplementary analyses Precipitation, air temperature, and solar radiation were monitored daily at a North Dakota Agricultural Weather Network (NDAWN) station within 1 km of the grazing treatments. Relevant data were downloaded following each gas sampling event from the NDAWN website (NDAWN, 2009). Near-surface soil water content and temperature were measured concurrently with gas flux when the soil was not frozen. Volumetric water content was measured in the surface 12 cm of soil using a time-domain reflectometry technique with a Campbell CS620 HydroSense System (Campbell Scientific, Inc., Logan, UT). Soil temperature was measured at a 6 cm depth with an Omega HH81A handheld digital thermometer attached to a heavy-duty T type thermocouple probe (Omega, Inc., Stamford, CT). Three measurements of soil water content and one measurement of soil temperature were made within 30 cm of each anchor during the 15 min gas sampling period. Values for volumetric water content were converted to water-filled pore space (WFPS) using field-measured soil bulk density for the surface 10 cm (Linn and Doran, 1984). Data analyses Given the lack of replication of the grazing treatments, anchors and sampling locations served as pseudo-replicates for measurements of gas flux, soil properties, and aboveground biomass (Gomez, 1984). While not ideal, justification for using this approach hinges upon the long-term value of the grazing treatments, the age of which makes them rare within North America. All collected data were analyzed using PROC MIXED in SAS (Littell et al., 1996) with grazing treatments and pseudo-replicates considered fixed and random effects, respectively. A significance criterion of P=0.05 was used to document differences among means. Variation of arithmetic means was expressed using standard error (Steel and Torrie, 1980). Where appropriate, associations between measured parameters were identified using Pearson correlation analysis. Gas flux data were tested for normality using skewness, kurtosis, and Kolmogorov-Smirnov coefficients before and after data were log-transformed. Data transformation did not improve normality of the data, so original gas flux data were used for statistical analyses. A mixed repeated measures model was used to analyze the effects of year, quarterly period (1 Dec. – 28/29 Feb., 1 Mar. – 31 May, 1 June – 31 Aug., and 1 Sep. – 30 Nov.), and grazing treatment on N2O and CH4 flux. Effects of soil temperature and WFPS on CH4 and N2O flux were also evaluated using a repeated measures model, but with a parsed data set including only sampling times when soil temperature and WFPS were measured. For both analyses, a time series covariance structure was used in the repeated measures model, where correlations decline over time (Phillips et al., 2009). Cumulative fluxes of N2O and CH4 were calculated by linearly interpolating data points and integrating the underlying area (Gilbert, 1987). Net GWP was calculated for each grazing treatment as the sum of emitted CO2 equivalents from five factors:Net GWP = NPA + EF + ?SOC + CH4F + N2OF where NPA was N fertilizer production and application; EF was CH4 emission from enteric fermentation; ?SOC was SOC change; CH4F was soil-atmosphere CH4 flux; and N2OF was soil-atmosphere N2O flux. The GWP for N fertilizer production was based on the applied N rate and an emission factor of 3.14 kg CO2 kg-1 N (West and Marland, 2002). Emission of CO2 associated with fertilizer N application (via a granular spreader and small tractor) was assumed to be 45.5 kg CO2 ha-1 (West and Marland, 2002). Daily CH4 emission via enteric fermentation from each steer was estimated at 179 g CH4 d-1 assuming a diet of ‘good pasture’ (Westberg et al., 2001). Differences in SOC stocks between the 1959 and 2003 samplings were taken to represent net soil-atmosphere CO2 and CH4 exchange for each grazing treatment. Soil organic C stocks determined by the equivalent soil mass approach were used for calculation. Contributions of soil-atmosphere CH4 and N2O flux to GWP were based on annual flux rates. For each factor contributing to GWP, the sum of CO2 equivalents was calculated assuming direct GWP of 1 kg CH4 ha-1 = 25 kg CO2 ha-1 and 1 kg N2O ha-1 = 298 kg CO2 ha-1 (100 year time horizon) (IPCC, 2007). Results for net GWP were expressed as kg CO2equiv. ha-1 yr-1. Global warming potential was related to animal productivity by dividing net GWP by mean annual weight gain ha-1 to estimate greenhouse gas intensity (GHGI) for each grazing treatment.
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H3 Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Mandan, North Dakota Greenhouse gas management and understanding the carbon emissions associated with land management decisions is a growing public concern and an increasingly important component to sustainable agricultural systems. Fertilization with nitrogen is known to influence emissions of greenhouse gases from soils. Less clear is how the timing of fertilization impacts emissions. We performed an experiment to determine if emissions could be reduced by adjustment of fertilization timing alone using a maize field in production. We found fertilization of plots with urea in the early-spring resulted in lower greenhouse gas emissions than fertilization of similar plots with urea in the late-spring. This was primarily due to greater emissions of carbon dioxide at the soil surface when fertilized at temperatures greater than 10°C. The difference between treatments, when integrated over a 5-month growing season, was 548 kg C ha-1. Yields were similar for both treatments. Fertilizing at cooler temperatures resulted in a substantial carbon “savings” without affecting yield. This study indicates fertilization timing may be a management option for reducing soil carbon losses and greenhouse gas emissions. Additional study is needed to determine if this effect is consistent across years.
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Phenocam overlooking a wetland dominated by Juncus effuses and Panicum hemitomon, Archbold's Buck Island Ranch, Florida. Tracking seasonal changes in greenness in the wetland. Takes RGB and IR photographs daily (every half hour between 6am and 8 pm) and sends them to phenocam network server at https://phenocam.sr.unh.edu/webcam/ where images are available to the public for downloads and processing.
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Phenocam overlooking A. virginicus Field, Archbold's Buck Island Ranch, Florida. Tracking seasonal changes in greenness of a semi-native pasture entirely burned once every three years. Takes RGB and IR photographs daily (every half hour between 6am and 8 pm) and sends them to phenocam network server at https://phenocam.sr.unh.edu/webcam/ where images are available to the public for downloads and processing.