• Authors:
    • Rothstein, D. E.
    • Forrester, J. A.
    • Palmer, M. M.
    • Mladenoff, D. J.
  • Source: GCB Bioenergy
  • Volume: 6
  • Issue: 4
  • Year: 2014
  • Summary: Short-rotation woody biomass crops (SRWC) have been proposed as a major feedstock source for bioenergy generation in the Northeastern US. To quantify the environmental effects and greenhouse gas (GHG) balance of crops including SRWC, investigators need spatially explicit data which encompass entire plantation cycles. A knowledge gap exists for the establishment period which makes current GHG calculations incomplete. In this study, we investigated the effects of converting pasture and hayfields to willow ( Salix spp.) and hybrid-poplar ( Populus spp.) SRWC plantations on soil nitrogen (N) cycling, nitrous oxide (N 2O) emissions, and nitrate (NO 3-) leaching at six sites of varying soil and climate conditions across northern Michigan and Wisconsin, following these plantations from pre conversion through their first 2 years. All six sites responded to establishment with increased N 2O emissions, available inorganic N, and, where it was measured, NO 3- leaching; however, the magnitude of these impacts varied dramatically among sites. Soil NO 3- levels varied threefold among sites, with peak extractable NO 3- concentrations ranging from 15 to 49 g N kg -1 soil. Leaching losses were significant and persisted through the second year, with 44-112 kg N ha -1 leached in SRWC plots. N 2O emissions in the first growing season varied 30-fold among sites, from 0.5 to 17.0 Mg-CO 2eq ha -1 (carbon dioxide equivalents). N 2O emissions over 2 years resulted in N 2O emissions due to plantation establishment that ranged from 0.60 to 22.14 Mg-CO 2eq ha -1 above baseline control levels across sites. The large N losses we document herein demonstrate the importance of including direct effects of land conversion in life-cycle analysis (LCA) studies of SRWC GHG balance. Our results also demonstrate the need for better estimation of spatial variability of N cycling processes to quantify the full environmental impacts of SRWC plantations.
  • Authors:
    • Asam, Z.-u.-Z.
    • Zhang, W.
    • Li, D.
    • Xu, X.
    • Luo, Y.
    • Kumar, S.
    • Rafique, R.
  • Source: Global and Planetary Change
  • Volume: 118
  • Issue: July
  • Year: 2014
  • Summary: Greenhouse gas (GHG) emissions play an important role in regulating the Earth surface temperature. GHG emissions from soils are sensitive to climate change and land management practices. According to general circulation model (GCM) predictions, the Earth will experience a combination of increased temperature and altered precipitation regimes which may result in an increase or a decrease of GHG exchange. The effect of climate change on GHG emissions can be examined through both experiments and by applying process-based models, which have become more popular. The performance of those models can be improved significantly by appropriate calibration procedures. The objectives of this study are to: (i) calibrate the DAYCENT model using advance parameter estimation (PEST) software and to (ii) examine simulated GHG dynamics at daily and seasonal time-scales under a climate change scenario of increased temperature (2 degrees C) and a precipitation regime change where 40% of precipitation during the dry season was redistributed to the wet season. The algorithmic calibration improved the model performance by reducing the sum of weighted squared residual differences by up to 223% (decreased from 1635 to 505 g N2O-N ha(-1) d(-1)) for N2O and 22% (decreased from 623 to 507% WFPS) for water filled pore space (WFPS) simulation results. In the altered climate scenario, total N2O and CO2 fluxes decreased by 9% (from 231 to 2.10 kg N2O-N ha(-1) yr(-1)) and 38% (from 1134.08 to 699.56 kg CO2 ha-1 yr-1) respectively, whereas CH4 fluxes increased by 10% (from 1.62 to 1.80 kg CH4 ha-1 yr-1). Our results show a larger impact of altered climate on CO2 as compared to N2O and CH4 emissions. The main difference in all GHG emissions was observed in summer period due to drought conditions created by reduced precipitation and increased temperatures. However, the GHG dynamics can also be attributed to no-till practices which play an important role in changing the soil moisture conditions for aerobic and anaerobic microsites. These results are based on a process-based model, therefore, we suggest performing experimental studies to examine the GHG emissions under increased temperature and especially under altered precipitation regimes. (C) 2014 Elsevier B.V. All rights reserved.
  • Authors:
    • Phillips, R.
    • Savage, K.
    • Davidson, E.
  • Source: Biogeosciences
  • Volume: 11
  • Issue: 10
  • Year: 2014
  • Summary: Carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) are the most important anthropogenic greenhouse gases (GHGs). Variation in soil moisture can be very dynamic, and it is one of the dominant factors controlling the net exchange of these three GHGs. Although technologies for high-frequency, precise measurements of CO2 have been available for years, methods for measuring soil fluxes of CH4 and N2O at high temporal frequency have been hampered by lack of appropriate technology for in situ real-time measurements. A previously developed automated chamber system for measuring CO2 flux from soils was configured to run in line with a new quantum cascade laser (QCLAS) instrument that measures N2O and CH4. Here we present data from a forested wetland in Maine and an agricultural field in North Dakota, which provided examples of both net uptake and production for N2O and CH4. The objective was to provide a range of conditions in which to run the new system and to compare results to a traditional manual static-chamber method. The high-precision and more-than-10-times-lower minimum detectable flux of the QCLAS system, compared to the manual system, provided confidence in measurements of small N2O uptake in the forested wetland. At the agricultural field, the greatest difference between the automated and manual sampling systems came from the effect of the relatively infrequent manual sampling of the high spatial variation, or "hot spots", in GHG fluxes. Hot spots greatly influenced the seasonal estimates, particularly for N2O, over one 74-day alfalfa crop cycle. The high temporal frequency of the automated system clearly characterized the transient response of all three GHGs to precipitation and demonstrated a clear diel pattern related to temperature for GHGs. A combination of high-frequency automated and spatially distributed chambers would be ideal for characterizing hot spots and "hot moments" of GHG fluxes.
  • Authors:
    • Malins, C. J.
    • Searle, S. Y.
  • Source: Biomass and Bioenergy
  • Volume: 65
  • Issue: June
  • Year: 2014
  • Summary: Expectations are high for energy crops. Government policies in the United States and Europe are increasingly supporting biofuel and heat and power from cellulose, and biomass is touted as a partial solution to energy security and greenhouse gas mitigation. Here, we review the literature for yields of 5 major potential energy crops: Miscanthus spp., Panicum virgatum (switch grass), Populus spp. (poplar), Salix spp. (willow), and Eucalyptus spp. Very high yields have been achieved for each of these types of energy crops, up to 40 t ha(-1) y(-1) in small, intensively managed trials. But yields are significantly lower in semi-commercial scale trials, due to biomass losses with drying, harvesting inefficiency under real world conditions, and edge effects in small plots. To avoid competition with food, energy crops should be grown on non-agricultural land, which also lowers yields. While there is potential for yield improvement for each of these crops through further research and breeding programs, for several reasons the rate of yield increase is likely to be slower than historically has been achieved for cereals; these include relatively low investment, long breeding periods, low yield response of perennial grasses to fertilizer, and inapplicability of manipulating the harvest index. Miscanthus x giganteus faces particular challenges as it is a sterile hybrid. Moderate and realistic expectations for the current and future performance of energy crops are vital to understanding the likely cost and the potential of large-scale production. (c) 2014 Elsevier Ltd. All rights reserved.
  • Authors:
    • Reay, D. S.
    • Six, J.
    • Angst, T. E.
    • Sohi, S. P.
  • Source: Agriculture Ecosystems & Enviroment
  • Volume: 191
  • Year: 2014
  • Summary: Manure generated by dairy cattle is a useful soil amendment but contributes to greenhouse gas (GHG) emissions and water pollution from nutrient leaching. In order to assess the impact of pine chip biochar produced at a peak temperature of 550°C when added to a dairy grassland system, a one-year field study was conducted on a sandy loam soil under annual ryegrass ( Lolium multiflorum Lam.) grown for silage in Petaluma, California. Manure was applied to all plots at a rate of ca. 150 m 3 ha -1 (410 kg N ha -1). Control plots received no biochar, high application biochar plots (HB) received biochar (with a 17% ash content) at a rate of 18.8 t ha -1, and low application biochar plots (LB) received the same biochar at 5.7 t ha -1. Although the HB plots demonstrated the lowest cumulative nitrous oxide (N 2O) and methane (CH 4) emissions, there was no significant difference between treatments ( p=0.152 and p=0.496, respectively). Soil pH results from samples collected throughout the year indicated a significant treatment effect ( p=0.046), though Tukey test results indicated that there was no difference between mean values. Soil total carbon was significantly higher in HB plots at the end of the experiment ( p=0.025) and nitrate (NO 3-) intensity throughout the year (which expresses potential exposure of NO 3- to the soil microbial community) was significantly lower in HB plots compared to the control ( p=0.001). Annual cumulative potassium (K +) loss from HB plots was significantly higher than from the other treatments ( p=0.018). HB plots also demonstrated a short-term increase in phosphorus (P) and ammonium (NH 4+) in leachate during the first rainfall event following manure and biochar application ( p<0.0001 and p=0.0002, respectively) as well as a short-term decrease of NO 3- in leachate during a heavy rainfall event following a long dry spell ( p=0.036), though differences between treatments for cumulative nutrient losses were not significant ( p=0.210, p=0.061, and p=0.295, respectively for P, NH 4+, and NO 3-). These data indicate that biochar produced from pine wood chips at 550°C having high ash content (17%) is not likely to impact GHG emissions in systems with high manure application rates. Further research should be conducted in order to investigate the impact of biochar amendment on the dynamics and mobility of nutrients applied in subsequent repeated applications of dairy manure.
  • Authors:
    • Horwath, W. R.
    • Hijmans, R. J.
    • Perlman, J.
  • Source: Global Ecology and Biogiography
  • Volume: 23
  • Issue: 8
  • Year: 2014
  • Summary: Aim: Modelling complex environmental and ecological processes over large geographic areas is challenging, particularly when basic research and model development for such processes has historically been at the local scale. Moving from local toward global analysis brings up numerous issues related to data processing, aggregation, tradeoffs between model quality and data quality, and prioritization of data collection and/or compilation efforts. We studied these issues in the context of modelling emissions of N 2O (a potent greenhouse gas) from agricultural soils. Location: Global. Methods: We developed metamodels of the DeNitrification-DeComposition (DNDC) model, a mechanistic model that simulates greenhouse gas emissions from agricultural soils, to estimate global N 2O emissions from maize and wheat fields. We ran DNDC for a diverse sample of global climate and soil types, and fitted the model output as a function of (sometimes simplified) model input variables, using the random forest machine learning algorithm. We used the metamodels to estimate global N 2O emissions from maize and wheat at a very high spatial resolution ( c. 1 km 2) and examined the effects of different approaches of using soil data as well as the effects of spatial aggregation of soil and climate data. Results: The average coefficient of determination ( R2) between holdout data (DNDC output not used to construct the metamodel) and metamodel predictions was 0.97 for maize and 0.91 for wheat. The metamodels were sensitive to soil properties, particularly to soil organic carbon content. Global emission estimates with the metamodel were highly sensitive to the spatial aggregation and other forms of generalization of soil data, but much less so to aggregation of climate data. Main conclusions: Using a simplified metamodel with data of high spatial resolution could produce results that are more accurate than those obtained with a full mechanistic model and lower-resolution data.
  • Authors:
    • Zhang, W.
    • Li, D. J.
    • Xu, X. L.
    • Luo, Y. Q.
    • Kumar, S.
    • Rafique, R.
    • Asam, Z. U.
  • Source: Global and Planetary Change
  • Volume: 118
  • Year: 2014
  • Summary: Greenhouse gas (GHG) emissions play an important role in regulating the Earth surface temperature. GHG emissions from soils are sensitive to climate change and land management practices. According to general circulation model (GCM) predictions, the Earth will experience a combination of increased temperature and altered precipitation regimes which may result in an increase or a decrease of GHG exchange. The effect of climate change on GHG emissions can be examined through both experiments and by applying process-based models, which have become more popular. The performance of those models can be improved significantly by appropriate calibration procedures. The objectives of this study are to: (i) calibrate the DAYCENT model using advance parameter estimation (PEST) software and to (ii) examine simulated GHG dynamics at daily and seasonal time-scales under a climate change scenario of increased temperature (2°C) and a precipitation regime change where 40% of precipitation during the dry season was redistributed to the wet season. The algorithmic calibration improved the model performance by reducing the sum of weighted squared residual differences by up to 223% (decreased from 1635 to 505 g N 2O-N ha -1 d -1) for N 2O and 22% (decreased from 623 to 507% WFPS) for water filled pore space (WFPS) simulation results. In the altered climate scenario, total N2O and CO2 fluxes decreased by 9% (from 2.31 to 2.10 kg N2O-N ha -1 yr -1) and 38% (from 1134.08 to 699.56 kg CO2 ha -1 yr -1) respectively, whereas CH4 fluxes increased by 10% (from 1.62 to 1.80 kg CH4 ha -1 yr -1). Our results show a larger impact of altered climate on CO2 as compared to N2O and CH4 emissions. The main difference in all GHG emissions was observed in summer period due to drought conditions created by reduced precipitation and increased temperatures. However, the GHG dynamics can also be attributed to no-till practices which play an important role in changing the soil moisture conditions for aerobic and anaerobic microsites. These results are based on a process-based model, therefore, we suggest performing experimental studies to examine the GHG emissions under increased temperature and especially under altered precipitation regimes.
  • Authors:
    • Davidson, E.
    • Phillips, R.
    • Savage, K.
  • Source: Biosciences
  • Volume: 11
  • Issue: 10
  • Year: 2014
  • Summary: Carbon dioxide (CO 2), methane (CH 4), and nitrous oxide (N 2O) are the most important anthropogenic greenhouse gases (GHGs). Variation in soil moisture can be very dynamic, and it is one of the dominant factors controlling the net exchange of these three GHGs. Although technologies for high-frequency, precise measurements of CO 2 have been available for years, methods for measuring soil fluxes of CH 4 and N 2O at high temporal frequency have been hampered by lack of appropriate technology for in situ real-time measurements. A previously developed automated chamber system for measuring CO 2 flux from soils was configured to run in line with a new quantum cascade laser (QCLAS) instrument that measures N 2O and CH 4. Here we present data from a forested wetland in Maine and an agricultural field in North Dakota, which provided examples of both net uptake and production for N 2O and CH 4. The objective was to provide a range of conditions in which to run the new system and to compare results to a traditional manual static-chamber method. The high-precision and more-than-10-times-lower minimum detectable flux of the QCLAS system, compared to the manual system, provided confidence in measurements of small N 2O uptake in the forested wetland. At the agricultural field, the greatest difference between the automated and manual sampling systems came from the effect of the relatively infrequent manual sampling of the high spatial variation, or "hot spots", in GHG fluxes. Hot spots greatly influenced the seasonal estimates, particularly for N 2O, over one 74-day alfalfa crop cycle. The high temporal frequency of the automated system clearly characterized the transient response of all three GHGs to precipitation and demonstrated a clear diel pattern related to temperature for GHGs. A combination of high-frequency automated and spatially distributed chambers would be ideal for characterizing hot spots and "hot moments" of GHG fluxes.
  • Authors:
    • Korth, K.
    • Chen, P.
    • Gbur, E. E.
    • Brye, K. R.
    • Smith, F.
  • Source: Soil Science
  • Volume: 179
  • Issue: 3
  • Year: 2014
  • Summary: One of the most significant contributors to the greenhouse effect is carbon dioxide (CO2) gas in the atmosphere. Soil respiration, the combined production of CO2 from soil, as a result of root and microorganism respiration, is the largest flux of CO2 from the terrestrial ecosystem to the atmosphere. Considering land use can greatly impact soil C storage and cycling, agricultural management practices can also greatly affect soil respiration and CO2 emissions. Therefore, the effects of long-term residue management (i.e., residue burning and nonburning, and conventional [CT] and no-tillage [NT]) and residue level (i.e., high and low) on soil respiration during the soybean [Glycine max (L.) Merr.] growing season were examined over 2 consecutive years (i.e., 2011 and 2012) in a wheat (Triticum aestivum L.)-soybean, double-crop system in a silt-loam soil (Aquic Fraglossudalf) in the Mississippi River Delta region of eastern Arkansas after more than 9 years of consistent management. Soil respiration rates from individual plots ranged from 0.53 to 40.7 and from 0.17 to 13.1 mol CO2.m(-2).s(-1) throughout the 2011 and 2012 soybean growing seasons, respectively, and differed (P < 0.05) among treatment combinations on two and five of nine and 11 measurement dates in 2011 and 2012, respectively. Regardless of residue level, soil respiration was generally greater (P < 0.05) from CT than NT. Estimated season-long CO2 emissions were 10.2% less (18.5 Mg CO2 ha(-1)) from residue burning than from non-burning (20.6 Mg CO2.ha(-1); P = 0.032). Averaged over years and all other field treatments, estimated season-long CO2 emissions were 15.5% greater from CT (21.0 Mg CO2 ha(-1)) than from NT (18.1Mg CO2 ha(-1); P = 0.020). Understanding long-term management effects on soil C losses, such as soil respiration, from common and widespread agricultural systems, such as the wheat-soybean, double-crop system, in eastern Arkansas can help improve policies for soil and environmental sustainability throughout the lower Mississippi River Delta region.
  • Authors:
    • Bandyopadhyay, K. K.
    • Lal, R.
  • Source: Geoderma
  • Volume: 232/234
  • Year: 2014
  • Summary: Soils can be a source or sink for the atmospheric greenhouse gases (GHGs) depending on the land use management, which needs to be understood properly for devising management strategies to mitigate climate change. It is hypothesized that the aggregate size distribution under different land use management practices and the C and N concentration in these aggregates may influence GHG (CO 2, N 2O and CH 4) emissions from soil. To test this hypothesis, a laboratory incubation study was conducted using soils from a 16-year old tillage experiment on corn ( Zea mays L.) and the adjoining forest on a Crosby silt loam soil (Haplic Luvisols) at the Waterman Agricultural and Natural Resource Laboratory of the Ohio State University (OSU), Columbus, Ohio. It was observed that in forest soil, cumulative CO 2 and N 2O emissions were significantly higher than those from the cultivated soil by 81.2 and 100%, respectively. However, there was no significant difference between conventional tillage (CT) and no till (NT) with respect to the cumulative CO 2 and N 2O emissions. Emissions were significantly higher from the large macro-aggregates than from other aggregate size fractions. There was net CH 4 uptake by the soil during the incubation period. The cumulative CO 2 and N 2O emissions and CH 4 uptake from different aggregate size fractions accounted for 59, 56, and 47% of the emissions/uptake of these gases from the bulk soil, respectively. The contributions of the large macro-aggregates towards the bulk soil CO 2 (39%) and N 2O (37.9%) emissions and CH 4 uptake (49.7%) were significantly higher than those of the micro-aggregates and mineral fraction. Total soil carbon, nitrogen, particulate carbon and nitrogen, and mineral associated carbon and nitrogen accounted for 87, 87 and 66% variation in the cumulative CO 2 and N 2O emissions and CH 4 uptake, respectively.