A gap in nitrous oxide emission reporting complicates long-term climate mitigation.

Nitrous oxide (N2O) is an important greenhouse gas (GHG) that also contributes to depletion of ozone in the stratosphere. Agricultural soils account for about 60% of anthropogenic N2O emissions. Most national GHG reporting to the United Nations Framework Convention on Climate Change assumes nitrogen (N) additions drive emissions during the growing season, but soil freezing and thawing during spring is also an important driver in cold climates. We show that both atmospheric inversions and newly implemented bottom-up modeling approaches exhibit large N2O pulses in the northcentral region of the United States during early spring and this increases annual N2O emissions from croplands and grasslands reported in the national GHG inventory by 6 to 16%. Considering this, emission accounting in cold climate regions is very likely underestimated in most national reporting frameworks. Current commitments related to the Paris Agreement and COP26 emphasize reductions of carbon compounds. Assuming these targets are met, the importance of accurately accounting and mitigating N2O increases once CO2 and CH4 are phased out. Hence, the N2O emission underestimate introduces additional risks into meeting long-term climate goals.

Secondary production of the central rangeland region of the United States.

Rangelands are the dominant land use across a broad swath of central North America where they span a wide gradient, from <350 to >900 mm, in mean annual precipitation. Substantial efforts have examined temporal and spatial variation in aboveground net primary production (ANPP) to precipitation (PPT) across this gradient. In contrast, net secondary productivity (NSP, e.g., primary consumer production) has not been evaluated analogously. However, livestock production, which is a form of NSP or primary consumer production supported by primary production, is the dominant non-cultivated land use and an integral economic driver in these regions. Here, we used long-term (mean length = 19 years) ANPP and NSP data from six research sites across the Central Great Plains with a history of a conservative stocking to determine resource (i.e., PPT)-productivity relationships, NSP sensitivities to dry-year precipitation, and regional trophic efficiencies (e.g., NSP:ANPP ratio). PPT-ANPP relationships were linear for both temporal (site-based) and spatial (among site) gradients. The spatial PPT-NSP model revealed that PPT mediated a saturating relationship for NSP as sites became more mesic, a finding that contrasts with many plant-based PPT-ANPP relationships. A saturating response to high growing-season precipitation suggests biogeochemical rather than vegetation growth constraints may govern NSP (i.e., large herbivore production). Differential sensitivity in NSP to dry years demonstrated that the primary consumer production response heightened as sites became more xeric. Although sensitivity generally decreased with increasing precipitation as predicted from known PPT-ANPP relationships, evidence suggests that the dominant species' identity and traits influenced secondary production efficiency. Non-native northern mixed-grass prairie was outperformed by native Central Great Plains rangeland in sensitivity to dry years and efficiency in converting ANPP to NSP. A more comprehensive understanding of the mechanisms leading to differences in producer and consumer responses will require multisite experiments to assess biotic and abiotic determinants of multi-trophic level efficiency and sensitivity.

Climate vs Energy Security: Quantifying the Trade-offs of BECCS Deployment and Overcoming Opportunity Costs on Set-Aside Land.

Bioenergy with carbon capture and storage (BECCS) sits at the nexus of the climate and energy security. We evaluated trade-offs between scenarios that support climate stabilization (negative emissions and net climate benefit) or energy security (ethanol production). Our spatially explicit model indicates that the foregone climate benefit from abandoned cropland (opportunity cost) increased carbon emissions per unit of energy produced by 14-36%, making geologic carbon capture and storage necessary to achieve negative emissions from any given energy crop. The toll of opportunity costs on the climate benefit of BECCS from set-aside land was offset through the spatial allocation of crops based on their individual biophysical constraints. Dedicated energy crops consistently outperformed mixed grasslands. We estimate that BECCS allocation to land enrolled in the Conservation Reserve Program (CRP) could capture up to 9 Tg C year-1 from the atmosphere, deliver up to 16 Tg CE year-1 in emissions savings, and meet up to 10% of the US energy statutory targets, but contributions varied substantially as the priority shifted from climate stabilization to energy provision. Our results indicate a significant potential to integrate energy security targets into sustainable pathways to climate stabilization but underpin the trade-offs of divergent policy-driven agendas.

Beyond ecosystem modeling: A roadmap to community cyberinfrastructure for ecological data-model integration.

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data-model integration requires investment in accessible, scalable, and transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundations of community cyberinfrastructure; data ingest; calibration of models to data; model-data benchmarking; and data assimilation and ecological forecasting. This community-driven approach is a key to meeting the pressing needs of science and society in the 21st century.

Large-scale and local climatic controls on large herbivore productivity: implications for adaptive rangeland management.

Rangeland ecosystems worldwide are characterized by a high degree of uncertainty in precipitation, both within and across years. Such uncertainty creates challenges for livestock managers seeking to match herbivore numbers with forage availability to prevent vegetation degradation and optimize livestock production. Here, we assess variation in annual large herbivore production (LHP, kg/ha) across multiple herbivore densities over a 78-yr period (1940-2018) in a semiarid rangeland ecosystem (shortgrass steppe of eastern Colorado, USA) that has experienced several phase changes in global-level sea surface temperature (SST) anomalies, as measured by the Pacific Decadal Oscillation (PDO) and the El Niño-Southern Oscillation (ENSO). We examined the influence of prevailing PDO phase, magnitude of late winter (February-April) ENSO, prior growing-season precipitation (prior April to prior September) and precipitation during the six months (prior October to current April) preceding the growing season on LHP. All of these are known prior to the start of the growing season in the shortgrass steppe and could potentially be used by livestock managers to adjust herbivore densities. Annual LHP was greater during warm PDO irrespective of herbivore density, while variance in LHP increased by 69% (moderate density) and 91% (high density) under cold-phase compared to warm-phase PDO. No differences in LHP attributed to PDO phase were observed with low herbivore density. ENSO effects on LHP, specifically La Niña, were more pronounced during cold-phase PDO years. High herbivore density increased LHP at a greater rate than at moderate and low densities with increasing fall and winter precipitation. Differential gain, a weighted measure of LHP under higher relative to lower herbivore densities, was sensitive to prevailing PDO phase, ENSO magnitude, and precipitation amounts from the prior growing season and current fall-winter season. Temporal hierarchical approaches using PDO, ENSO, and local-scale precipitation can enhance decision-making for flexible herbivore densities. Herbivore densities could be increased above recommended levels with lowered risk of negative returns for managers during warm-phase PDO to result in greater LHP and less variability. Conversely, during cold-phase PDO, managers should be cognizant of the additional influences of ENSO and prior fall-winter precipitation, which can help predict when to reduce herbivore densities and minimize risk of forage shortages.

Fixing a snag in carbon emissions estimates from wildfires.

Wildfire is an essential earth-system process, impacting ecosystem processes and the carbon cycle. Forest fires are becoming more frequent and severe, yet gaps exist in the modeling of fire on vegetation and carbon dynamics. Strategies for reducing carbon dioxide (CO2 ) emissions from wildfires include increasing tree harvest, largely based on the public assumption that fires burn live forests to the ground, despite observations indicating that less than 5% of mature tree biomass is actually consumed. This misconception is also reflected though excessive combustion of live trees in models. Here, we show that regional emissions estimates using widely implemented combustion coefficients are 59%-83% higher than emissions based on field observations. Using unique field datasets from before and after wildfires and an improved ecosystem model, we provide strong evidence that these large overestimates can be reduced by using realistic biomass combustion factors and by accurately quantifying biomass in standing dead trees that decompose over decades to centuries after fire ("snags"). Most model development focuses on area burned; our results reveal that accurately representing combustion is also essential for quantifying fire impacts on ecosystems. Using our improvements, we find that western US forest fires have emitted 851 ± 228 Tg CO2 (~half of alternative estimates) over the last 17 years, which is minor compared to 16,200 Tg CO2 from fossil fuels across the region.

Measuring and mitigating agricultural greenhouse gas production in the US Great Plains, 1870-2000.

The Great Plains region of the United States is an agricultural production center for the global market and, as such, an important source of greenhouse gas (GHG) emissions. This article uses historical agricultural census data and ecosystem models to estimate the magnitude of annual GHG fluxes from all agricultural sources (e.g., cropping, livestock raising, irrigation, fertilizer production, tractor use) in the Great Plains from 1870 to 2000. Here, we show that carbon (C) released during the plow-out of native grasslands was the largest source of GHG emissions before 1930, whereas livestock production, direct energy use, and soil nitrous oxide emissions are currently the largest sources. Climatic factors mediate these emissions, with cool and wet weather promoting C sequestration and hot and dry weather increasing GHG release. This analysis demonstrates the long-term ecosystem consequences of both historical and current agricultural activities, but also indicates that adoption of available alternative management practices could substantially mitigate agricultural GHG fluxes, ranging from a 34% reduction with a 25% adoption rate to as much as complete elimination with possible net sequestration of C when a greater proportion of farmers adopt new agricultural practices.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment.

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m-2  yr-1 ). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO2 -induced water savings to extend the growing season length. Observed interactive (CO2  × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.

Nitrogen deposition and greenhouse gas emissions from grasslands: uncertainties and future directions.

Increases in atmospheric nitrogen deposition (Ndep) can strongly affect the greenhouse gas (GHG; CO2, CH4, and N2O) sink capacity of grasslands as well as other terrestrial ecosystems. Robust predictions of the net GHG sink strength of grasslands depend on how experimental N loads compare to projected Ndep rates, and how accurately the relationship between GHG fluxes and Ndep is characterized. A literature review revealed that the vast majority of experimental N loads were higher than levels these ecosystems are predicted to experience in the future. Using a process-based biogeochemical model, we predicted that low levels of Ndep either enhanced or reduced the net GHG sink strength of most grasslands, but as experimental N loads continued to increase, grasslands transitioned to a N saturation-decline stage, where the sensitivity of GHG exchange to further increases in Ndep declined. Most published studies represented treatments well into the N saturation-decline stage. Our model results predict that the responses of GHG fluxes to N are highly nonlinear and that the N saturation thresholds for GHGs varied greatly among grasslands and with fire management. We predict that during the 21st century some grasslands will be in the N limitation stage where others will transition into the N saturation-decline stage. The linear relationship between GHG sink strength and N load assumed by most studies can overestimate or underestimate predictions of the net GHG sink strength of grasslands depending on their N baseline status. The next generation of global change experiments should be designed at multiple N loads consistent with future Ndep rates to improve our empirical understanding and predictive ability.

Long-term impacts of manure amendments on carbon and greenhouse gas dynamics of rangelands.

Livestock manure is applied to rangelands as an organic fertilizer to stimulate forage production, but the long-term impacts of this practice on soil carbon (C) and greenhouse gas (GHG) dynamics are poorly known. We collected soil samples from manured and nonmanured fields on commercial dairies and found that manure amendments increased soil C stocks by 19.0 ± 7.3 Mg C ha(-1) and N stocks by 1.94 ± 0.63 Mg N ha(-1) compared to nonmanured fields (0-20 cm depth). Long-term historical (1700-present) and future (present-2100) impacts of management on soil C and N dynamics, net primary productivity (NPP), and GHG emissions were modeled with DayCent. Modeled total soil C and N stocks increased with the onset of dairying. Nitrous oxide (N2 O) emissions also increased by ~2 kg N2 O-N ha(-1)  yr(-1) . These emissions were proportional to total N additions and offset 75-100% of soil C sequestration. All fields were small net methane (CH4 ) sinks, averaging -4.7 ± 1.2 kg CH4 -C ha(-1)  yr(-1) . Overall, manured fields were net GHG sinks between 1954 and 2011 (-0.74 ± 0.73 Mg CO2 e ha(-1)  yr(-1) , CO2 e are carbon dioxide equivalents), whereas nonmanured fields varied around zero. Future soil C pools stabilized 40-60 years faster in manured fields than nonmanured fields, at which point manured fields were significantly larger sources than nonmanured fields (1.45 ± 0.52 Mg CO2 e ha(-1)  yr(-1) and 0.51 ± 0.60 Mg CO2 e ha(-1)  yr(-1) , respectively). Modeling also revealed a large background loss of soil C from the passive soil pool associated with the shift from perennial to annual grasses, equivalent to 29.4 ± 1.47 Tg CO2 e in California between 1820 and 2011. Manure applications increased NPP and soil C storage, but plant community changes and GHG emissions decreased, and eventually eliminated, the net climate benefit of this practice.

Forest ecosystem respiration estimated from eddy covariance and chamber measurements under high turbulence and substantial tree mortality from bark beetles.

Eddy covariance nighttime fluxes are uncertain due to potential measurement biases. Many studies report eddy covariance nighttime flux lower than flux from extrapolated chamber measurements, despite corrections for low turbulence. We compared eddy covariance and chamber estimates of ecosystem respiration at the GLEES Ameriflux site over seven growing seasons under high turbulence [summer night mean friction velocity (u*) = 0.7 m s(-1)], during which bark beetles killed or infested 85% of the aboveground respiring biomass. Chamber-based estimates of ecosystem respiration during the growth season, developed from foliage, wood, and soil CO2 efflux measurements, declined 35% after 85% of the forest basal area had been killed or impaired by bark beetles (from 7.1 ± 0.22 µmol m(-2) s(-1) in 2005 to 4.6 ± 0.16 µmol m(-2) s(-1) in 2011). Soil efflux remained at ~3.3 µmol m(-2) s(-1) throughout the mortality, while the loss of live wood and foliage and their respiration drove the decline of the chamber estimate. Eddy covariance estimates of fluxes at night remained constant over the same period, ~3.0 µmol m(-2) s(-1) for both 2005 (intact forest) and 2011 (85% basal area killed or impaired). Eddy covariance fluxes were lower than chamber estimates of ecosystem respiration (60% lower in 2005, and 32% in 2011), but the mean night estimates from the two techniques were correlated within a year (r(2) from 0.18 to 0.60). The difference between the two techniques was not the result of inadequate turbulence, because the results were robust to a u* filter of >0.7 m s(-1). The decline in the average seasonal difference between the two techniques was strongly correlated with overstory leaf area (r(2) = 0.92). The discrepancy between methods of respiration estimation should be resolved to have confidence in ecosystem carbon flux estimates.

Integrating biorefinery and farm biogeochemical cycles offsets fossil energy and mitigates soil carbon losses.

Crop residues are potentially significant sources of feedstock for biofuel production in the United States. However, there are concerns with maintaining the environmental functions of these residues while also serving as a feedstock for biofuel production. Maintaining soil organic carbon (SOC) along with its functional benefits is considered a greater constraint than maintaining soil erosion losses to an acceptable level. We used the biogeochemical model DayCent to evaluate the effect of residue removal, corn stover, and wheat and barley straw in three diverse locations in the USA. We evaluated residue removal with and without N replacement, along with application of a high-lignin fermentation byproduct (HLFB), the residue by-product comprised of lignin and small quantities of nutrients from cellulosic ethanol production. SOC always decreased with residue harvest, but the decrease was greater in colder climates when expressed on a life cycle basis. The effect of residue harvest on soil N2O emissions varied with N addition and climate. With N addition, N2O emissions always increased, but the increase was greater in colder climates. Without N addition, N2O emissions increased in Iowa, but decreased in Maryland and North Carolina with crop residue harvest. Although SOC was lower with residue harvest when HLFB was used for power production instead of being applied to land, the avoidance of fossil fuel emissions to the atmosphere by utilizing the cellulose and hemicellulose fractions of crop residue to produce ethanol (offsets) reduced the overall greenhouse gas (GHG) emissions because most of this residue carbon would normally be lost during microbial respiration. Losses of SOC and reduced N mineralization could both be mitigated with the application of HLFB to the land. Therefore, by returning the high-lignin fraction of crop residue to the land after production of ethanol at the biorefinery, soil carbon levels could be maintained along with the functional benefit of increased mineralized N, and more GHG emissions could be offset compared to leaving the crop residues on the land.

Long-term climate change mitigation potential with organic matter management on grasslands.

Compost amendments to grasslands have been proposed as a strategy to mitigate climate change through carbon (C) sequestration, yet little research exists exploring the net mitigation potential or the long-term impacts of this strategy. We used field data and the DAYCENT biogeochemical model to investigate the climate change mitigation potential of compost amendments to grasslands in California, USA. The model was used to test ecosystem C and greenhouse gas responses to a range of compost qualities (carbon to nitrogen [C:N] ratios of 11.1, 20, or 30) and application rates (single addition of 14 Mg C/ha or 10 annual additions of 1.4 Mg C · ha(-1) · yr(-1)). The model was parameterized using site-specific weather, vegetation, and edaphic characteristics and was validated by comparing simulated soil C, nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2) fluxes, and net primary production (NPP) with three years of field data. All compost amendment scenarios led to net greenhouse gas sinks that persisted for several decades. Rates of climate change mitigation potential ranged from 130 ± 3 g to 158 ± 8 g CO2-eq · m(-2) ·yr(-1) (where "eq" stands for "equivalents") when assessed over a 10-year time period and 63 ± 2 g to 84 ± 10 g CO2- eq · m(-2) · yr(-1) over a 30-year time period. Both C storage and greenhouse gas emissions increased rapidly following amendments. Compost amendments with lower C:N led to higher C sequestration rates over time. However, these soils also experienced greater N20 fluxes. Multiple smaller compost additions resulted in similar cumulative C sequestration rates, albeit with a time lag, and lower cumulative N2O emissions. These results identify a trade-off between maximizing C sequestration and minimizing N2O emissions following amendments, and suggest that compost additions to grassland soils can have a long-term impact on C and greenhouse gas dynamics that contributes to climate change mitigation.

Synthesis and modeling perspectives of rhizosphere priming.

The rhizosphere priming effect (RPE) is a mechanism by which plants interact with soil functions. The large impact of the RPE on soil organic matter decomposition rates (from 50% reduction to 380% increase) warrants similar attention to that being paid to climatic controls on ecosystem functions. Furthermore, global increases in atmospheric CO2 concentration and surface temperature can significantly alter the RPE. Our analysis using a game theoretic model suggests that the RPE may have resulted from an evolutionarily stable mutualistic association between plants and rhizosphere microbes. Through model simulations based on microbial physiology, we demonstrate that a shift in microbial metabolic response to different substrate inputs from plants is a plausible mechanism leading to positive or negative RPEs. In a case study of the Duke Free-Air CO2 Enrichment experiment, performance of the PhotoCent model was significantly improved by including an RPE-induced 40% increase in soil organic matter decomposition rate for the elevated CO2 treatment--demonstrating the value of incorporating the RPE into future ecosystem models. Overall, the RPE is emerging as a crucial mechanism in terrestrial ecosystems, which awaits substantial research and model development.

Where does the carbon go? A model-data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free-air CO2 enrichment sites.

Elevated atmospheric CO2 concentration (eCO2) has the potential to increase vegetation carbon storage if increased net primary production causes increased long-lived biomass. Model predictions of eCO2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free-air CO2 enrichment (FACE) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO2 effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO2 effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions; careful testing of allocation schemes; and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets.

Simulating greenhouse gas mitigation potentials for Chinese Croplands using the DAYCENT ecosystem model.

Understanding the potential for greenhouse gas (GHG) mitigation in agricultural lands is a critical challenge for climate change policy. This study uses the DAYCENT ecosystem model to predict GHG mitigation potentials associated with soil management in Chinese cropland systems. Application of ecosystem models, such as DAYCENT, requires the evaluation of model performance with data sets from experiments relevant to the climate and management of the study region. DAYCENT was evaluated with data from 350 cropland experiments in China, including measurements of nitrous oxide emissions (N2 O), methane emissions (CH4 ), and soil organic carbon (SOC) stock changes. In general, the model was reasonably accurate with R(2) values for model predictions vs. measurements ranging from 0.71 to 0.85. Modeling efficiency varied from 0.65 for SOC stock changes to 0.83 for crop yields. Mitigation potentials were estimated on a yield basis (Mg CO2 -equivalent Mg(-1) Yield). The results demonstrate that the largest decrease in GHG emissions in rainfed systems are associated with combined effect of reducing mineral N fertilization, organic matter amendments and reduced-till coupled with straw return, estimated at 0.31 to 0.83 Mg CO2 -equivalent Mg(-1) Yield. A mitigation potential of 0.08 to 0.36 Mg CO2 -equivalent Mg(-1) Yield is possible by reducing N chemical fertilizer rates, along with intermittent flooding in paddy rice cropping systems.

Modeling nitrous oxide emissions from irrigated agriculture: testing DayCent with high-frequency measurements.

A unique high temporal frequency data set from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N20 emissions from subtropical vertisols under different irrigation intensities. DayCent was able to simulate the effect of different irrigation intensities on N20 fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a good correlation of predicted vs. measured N20 fluxes (r2 = 0.52), confirming that DayCent can be used to test agricultural practices for mitigating N20 emission from irrigated cropping systems. A 25-year scenario analysis indicated that N20 losses from irrigated cotton-wheat rotations on black vertisols in Australia can be substantially reduced by an optimized fertilizer and irrigation management system (i.e., frequent irrigation, avoidance of excessive fertilizer application), while sustaining maximum yield potentials.

The theoretical limit to plant productivity.

Human population and economic growth are accelerating the demand for plant biomass to provide food, fuel, and fiber. The annual increment of biomass to meet these needs is quantified as net primary production (NPP). Here we show that an underlying assumption in some current models may lead to underestimates of the potential production from managed landscapes, particularly of bioenergy crops that have low nitrogen requirements. Using a simple light-use efficiency model and the theoretical maximum efficiency with which plant canopies convert solar radiation to biomass, we provide an upper-envelope NPP unconstrained by resource limitations. This theoretical maximum NPP approached 200 tC ha(-1) yr(-1) at point locations, roughly 2 orders of magnitude higher than most current managed or natural ecosystems. Recalculating the upper envelope estimate of NPP limited by available water reduced it by half or more in 91% of the land area globally. While the high conversion efficiencies observed in some extant plants indicate great potential to increase crop yields without changes to the basic mechanism of photosynthesis, particularly for crops with low nitrogen requirements, realizing such high yields will require improvements in water use efficiency.

Higher than expected N2O emissions from soybean crops in the Pampas Region of Argentina: Estimates from DayCent simulations and field measurements.

In developing countries, agriculture generally represents a large fraction of GHG emissions reported in National Inventories, and emissions are typically estimated using Tier 1 IPCC guidelines. However, field data and locally adapted simulation models can improve the accuracy of IPCC estimations. In this study we aimed to quantify anthropogenic N2O emissions from croplands of Argentina through field measurements, model simulations and IPCC guidelines. We measured N2O emissions and their controlling factors in 62 plots of the Pampas Region with corn, soybean and wheat/soybean crops and in unmanaged grasslands. We accounted for gross emissions from crops and background emissions from unmanaged grasslands to calculate net anthropogenic emissions from crops as the difference between them. We calibrated and evaluated the DayCent model and then simulated different weather and management scenarios. Finally, we applied IPCC guidelines to estimate anthropogenic N2O emissions at the same plots. The DayCent model accurately simulated annual N2O emission for all crops as compared to measured data (RMSE = 1.4 g N ha-1 day-1). Measured and simulated emissions in soybean crops were higher than in corn and wheat/soybean crops. Gross N2O emissions ranged from 1.4 to 5.1 kg N ha-1 yr-1 for current environmental (soil and weather) and management (crops and fertilizer doses) conditions. Background emissions ranged between 1.1 and 1.3 kg N ha-1 yr-1, and therefore net anthropogenic emissions ranged from 0.3 to 4.0 kg N ha-1 yr-1. IPCC Tier 1 emission factors underestimated N2O releases from soybean, that were on average 4.87 times greater when estimated with DayCent and observations (0.53 vs 2.47 and 2.69 kg N ha-1 yr-1, respectively). On the contrary, IPCC estimates for corn and wheat/soybean crops were similar to modeled and measured values. Our results suggest that N2O emissions from the vast 15 million ha of soybean croplands in the Pampas Region may be substantially underestimated.

The biogeochemistry of bioenergy landscapes: carbon, nitrogen, and water considerations.

The biogeochemical liabilities of grain-based crop production for bioenergy are no different from those of grain-based food production: excessive nitrate leakage, soil carbon and phosphorus loss, nitrous oxide production, and attenuated methane uptake. Contingent problems are well known, increasingly well documented, and recalcitrant: freshwater and coastal marine eutrophication, groundwater pollution, soil organic matter loss, and a warming atmosphere. The conversion of marginal lands not now farmed to annual grain production, including the repatriation of Conservation Reserve Program (CRP) and other conservation set-aside lands, will further exacerbate the biogeochemical imbalance of these landscapes, as could pressure to further simplify crop rotations. The expected emergence of biorefinery and combustion facilities that accept cellulosic materials offers an alternative outcome: agricultural landscapes that accumulate soil carbon, that conserve nitrogen and phosphorus, and that emit relatively small amounts of nitrous oxide to the atmosphere. Fields in these landscapes are planted to perennial crops that require less fertilizer, that retain sediments and nutrients that could otherwise be transported to groundwater and streams, and that accumulate carbon in both soil organic matter and roots. If mixed-species assemblages, they additionally provide biodiversity services. Biogeochemical responses of these systems fall chiefly into two areas: carbon neutrality and water and nutrient conservation. Fluxes must be measured and understood in proposed cropping systems sufficient to inform models that will predict biogeochemical behavior at field, landscape, and regional scales. Because tradeoffs are inherent to these systems, a systems approach is imperative, and because potential biofuel cropping systems and their environmental contexts are complex and cannot be exhaustively tested, modeling will be instructive. Modeling alternative biofuel cropping systems converted from different starting points, for example, suggests that converting CRP to corn ethanol production under conventional tillage results in substantially increased net greenhouse gas (GHG) emissions that can be only partly mitigated with no-till management. Alternatively, conversion of existing cropland or prairie to switchgrass production results in a net GHG sink. Outcomes and policy must be informed by science that adequately quantifies the true biogeochemical costs and advantages of alternative systems.