Browsing by Author "Paustian, Keith, advisor"
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Item Open Access A mechanistic approach to modeling saturation and protection mechanisms of soil organic matter(Colorado State University. Libraries, 2009) Olchin, Gabriel Peter, author; Paustian, Keith, advisorSimulation models have been used extensively as a research tool in the field of soil organic matter (SOM) dynamics and should embody our best understandings of the processes and mechanisms controlling these dynamics. Our objective was to develop and evaluate a SOM model based upon measureable soil organic carbon (SOC) fractions and optimize it against long-term tillage experiments in North America. This model will include (1) soil aggregate dynamics, with direct influence from tillage events; (2); and the mechanisms of SOM stabilization; and (3) explicitly address the concept of potential SOC saturation. The major proposed mechanisms for SOM stabilization-physical occlusion, organic recalcitrance, and organo-mineral interactions-have limited explicit inclusion in current SOM models.Item Open Access Analysis of land use change and greenhouse gas emissions in Kalasin Province, Thailand(Colorado State University. Libraries, 2018) Chailangka, Preeyarat, author; Paustian, Keith, advisor; Fonte, Steven, committee member; Leisz, Stephen, committee memberGrowing global population causes many stresses on the environment, perhaps the most serious is global warming due to Greenhouse Gas (GHG) emissions. Major contributors to GHG emissions include agricultural production and land use change. Southeast Asia is one of the world's fastest growing regions and provides many crops for export, so the land use changes are rapid and not always made in an environmentally conscious manner. The province chosen for this study, Kalasin, is located in a major economic development region with the multi-country East-West Economic Corridor (EWEC) running through it. The EWEC has brought many changes to this province such as expansion of the manufacturing sector, more urban growth to support new factories, and new roads to reach areas which were previously not developed. The largest single land use in Thailand and the Kalasin province is cropland. There have been many changes in farming practices in the province as well, from the types of crops grown to the increasing numbers of commercial farms. These shifts in land use are leading to changes in the amount of GHG emissions and are also leading to land degradation in parts of the province as well. The largest GHGs emissions in agricultural sector come from rice cultivation (45%), followed by biomass carbon stock losses (40%). Some government policies have led to crops being grown on unsuitable lands, which is often associated with greater use of fertilizers and intensive tillage practices applied. Other practices involve draining wetlands, creating rice paddies on unsuitable soils, or clearing forests to farm the area. In this study we look at land use and land use changes throughout the province and use that data to estimate a GHG emissions inventory in the agricultural sector in order to better understand the effects that growth, land use and land use changes in the Kalasin province have on the environment.Item Open Access Conservation agriculture: impacts on soil N2O emissions and adoption by farmers(Colorado State University. Libraries, 2012) Swan, Amy, author; Paustian, Keith, advisor; Ogle, Stephen, advisor; Sherman, Kathleen, committee memberAgriculture is vulnerable to the effects of and a contributor to climate change, as a net source of anthropogenic greenhouse gases (GHG). However, agriculture has potential to reduce emissions and perhaps even become a net sink for GHG, through implementation of improved management practices. Previous research has shown that improved practices that reduce soil disturbance may sequester atmospheric carbon (C) in the form of soil organic matter. However, the impact of these practices on emissions of soil N2O, a potent GHG, are not as well understood. It is important to assess the effects of these practices on GHG emissions, as well as the potential of these practices to be used widely by farmers. I examined the effects of reduced soil disturbance from two conservation practices, no-till (NT) and conversion of cultivated cropland to perennial grassland, on N2O emissions, and evaluated adoption of NT by farmers in the Great Plains region of the U.S. I used a meta-analysis approach to evaluate changes in soil N2O emissions after a shift from full-inversion tillage (FT) to no-till (NT) on cropland and conversion of cultivated croplands to grasslands. Data were collected from published literature and analyzed with a linear mixed-effect modeling method, in which management practices, soil texture and climate were tested as fixed effect. After adoption of NT, soil N2O emissions were predicted to increase in humid climates by 0.4-0.8 kg N2O-N ha-1 yr-1, and decrease in dry climates, especially on soils with low clay contents, by as much as 1 kg N2O-N ha-1 yr-1. Changes in emissions after conversion of cropland to grassland were largely related to changes in N fertilizer rates. When lower rates of N were applied to grasslands, emissions were reduced by as much as 2 kg N2O-N ha-1 yr-1. When there was no change in N fertilizer, emissions were predicted to be higher than cropland rates, especially on moderate clay soils. Though the analysis predicted some clear changes in emissions after NT adoption and conversion of croplands to grasslands, further research is needed to better understand the interacting effects of management, climate and soil texture on soil N2O emissions. The practice of NT has been associated with many environmental benefits, including reduced soil erosion, lower run-off rates, increased soil organic matter, and improved soil structure. In addition to the potential of NT to sequester atmospheric C, results from my research show potential for NT to reduce N2O emissions in dry climates. Furthermore, the ability of NT to increase soil moisture retention may be a great benefit to crop production in dry climates, such as found in the Great Plains, U.S. However, NT is only used on about 17% of all croplands in this region. To evaluate the factors affecting NT adoption in the Great Plains, I conducted a regional analysis using county-level statistics and a local-level analysis using household surveys. Environmental variables, climate, slope, and soil texture, were predictors of adoption at the regional scale. High rates of adoption were predicted in dry, cool climates, which was consistent with the finding in the household surveys that NT farmers were more likely to cite soil moisture conservation as an important issue. Counties with more erodible soils (i.e. steep slopes (water) or high sand (wind)) had higher rates of NT adoption, possibly indicating that farmers in these counties were using NT to control soil erosion. Components of farm structure were also important, with ownership, cropping system, and Conservation Reserve Program (CRP) enrollment influencing NT adoption. Increased ownership rates and higher proportions of wheat cropping, led to lower rates in NT adoption. According to the household surveys, farmers with land enrolled in the CRP were more likely to use NT. Some operator characteristics and attitudes were found to be positively associated with NT adoption. Farmers who had been on their operation longer, expressed trust in the federal government, or hunted on their land for recreation were also more likely to adopt NT. Though some significant predictors of adoption in the Great Plains region may have an economic impact (climate, ownership and wheat cropping), no direct economic measures were found to be significant in predicting NT adoption in this analysis. Barriers to NT adoption in the region may be lack of education on the benefits of NT on crop production and the prevalence of continuous wheat cropping in parts of the region. Because NT adoption rates were higher among farmers who had participated in a government program (CRP) or expressed trust in the federal government, outreach may especially need to be targeted to farmers with less involvement in federal government programs. Though reason for the influence of ownership on NT adoption was unclear, future research may focus on the role of farm size in tillage decisions.Item Open Access Integrated assessment of agricultural ecosystems using simulation-optimization and machine learning(Colorado State University. Libraries, 2018) Nguyen, Trung H., author; Paustian, Keith, advisor; Cotrufo, Francesca, committee member; Kelly, Eugene, committee member; Leisz, Stephen, committee member; Davies, Christian, committee memberAgriculture provides many ecosystem services to human society but is also a major cause of environmental degradation. The key challenge of modern agricultural production is to meet projected increases in global demands for food, water, and energy in sustainable ways. Sustainable agricultural production requires integrated decision-support tools and rigorous assessment methods to improve the efficiency of natural resource management while minimizing its impacts to society and long-term ecosystem health. This dissertation focuses on developing methodology and modeling tools to support decision-making for sustainable agricultural resource management. The Millennium Ecosystem Assessment is used as a guiding framework for all the model development. The dissertation balances between the communication of the integrated assessment methodology and the presentation of the modeling techniques through four independent case studies. The first study links biogeochemical models with life cycle assessment (LCA) to explore the impact of regionally-specific ecosystem carbon stock changes associated with cassava cultivation for ethanol production in Vietnam. The second study couples biogeochemical models with GIS and optimization algorithms to conduct a high-resolution, spatially-explicit trade-off analysis of ecosystem services for irrigated corn production systems in the South Platte River Basin, Colorado, USA. The derived modeling platform is named the "Agricultural Ecosystem Service Optimization" (Ag-EcoSOpt). The third study integrates LCA into the Ag-EcoSOpt for a life-cycle-based optimization of feedstock landscape design for a hybrid corn grain- and stover-based ethanol production system at Front Range Energy biorefinery, Windsor, Colorado, USA. The last study develops a surrogate-based optimization framework for Ag-EcoSOpt to reduce the computational burden of large-scale landscape analyses. The study explores the trade-offs among seven management objectives of the irrigated corn production systems in Colorado, USA at different spatial scales.Item Open Access Mechanisms and management for soil carbon sequestration(Colorado State University. Libraries, 2020) Mosier, Samantha, author; Cotrufo, M. Francesca, advisor; Paustian, Keith, advisor; Davies, Christian, committee member; Denef, Karolien, committee memberSoil organic matter (SOM) holds more carbon (C) than the atmosphere and terrestrial aboveground biomass combined. SOM also provides many other co-benefits in the form of ecosystem services. The rate at which we lose or sequester more C in soils is of great importance for mitigating the rising atmospheric greenhouse gas concentrations as well as for maintaining the fundamental services that soils provide to humanity. Many of the mechanisms involved in accruing and storing soil C are not entirely clear, and factors like litter chemistry and minerology can all come into play when determining the sequestration potential of a specific ecosystem. Additionally, not all soil C is equal in its turnover time or in its ability to resist disturbance. Therefore it is crucial that we better understand how functionally different soil C pools form and persist in the soil environment. Several "climate smart" soil management practices have been analyzed for their potential to sequester more C. However there are still gaps in our knowledge regarding soil C sequestration and how it can be impacted by land use management. The southeast US is a region with particularly severe soil degradation from poor agricultural management, but also has a high potential for increased soil C sequestration and overall soil health. This dissertation looks at some potential mechanisms and management practices involved with storing more stable soil C in the southeastern US. Mechanisms include how litter chemistry and soil C saturation can enhance or inhibit soil C sequestration. Then, we evaluated management practices from pine plantations and grassland grazing in the southeastern US to evaluate if improved management could increase soil C stocks, their distribution, and overall soil health.Item Open Access Methane and nitrous oxide fluxes from cattle excrement on C3 pasture and C4 native rangeland of the shortgrass steppe(Colorado State University. Libraries, 2014) Nichols, Kristopher L., author; Paustian, Keith, advisor; Del Grosso, Stephen, committee member; Derner, Justin, committee member; Follett, Ron, committee member; Archibeque, Shawn, committee memberGrazers play a major role in nutrient cycling of grassland ecosystems through the removal of biomass and the deposition of excrement in the forms of liquid, urine and solid feces. We studied the effects of cattle excrement patches on methane (CH4) and nitrous oxide (N2O) fluxes using semi-static chambers on cool-season (C3), Bozoisky-select pasture, and warm-season (C4-dominated) native rangeland on the shortgrass steppe. Trace gas measurements were conducted over a 2 year period from cattle urine (43 g N m-2) and feces (94 g N m-2) patches within replicated exclosures on each plant community. Cumulative N2O emissions for the 2 year experimental period, on a per area basis, were 55% greater from feces relative to urine patches on native rangeland (1.81 and 1.17 kg N2O-N ha-1) and 25% greater on Bozoisky-select pasture (1.66 and 1.25 kg N2O-N ha-1). While the cumulative N2O emissions were similar within treatments across plant communities, the magnitude of seasonal fluxes were different. Emissions from the excrement treatments were greater on the Bozoisky-select pasture the summer following treatment application, while emissions were greater on the native rangeland the following fall and spring. The emission factors for urine and feces did not differ for urine and feces on native rangeland (0.13 and 0.13%) and Bozoisky-select pasture (0.14 and 0.11%), but these emission factors were substantially less than the IPCC Tier 1 default factor (2%) for manure deposited on pasture, indicating that N2O emissions from these plant communities are currently overestimated. These findings suggest that the IPCC Tier 1 Default N2O emission factor of 2% for manure deposited on pasture is not representative of N2O emissions from cattle excrement on shortgrass steppe. Nitrous oxide emissions from the control plots on native rangeland and Bozoisky-select pasture were similar, 0.61 and 0.65 kg ha-1, respectively. Methane uptake was significantly less from cattle excrement compared to control plots for both plant communities. Cumulative net CH4 uptake rates were 68% greater for urine compared to feces patches on native rangeland (-2.73 and -0.88 kg CH4-C ha-1) and 86% greater on Bozoisky-select pasture (-2.16 and -0.30 kg CH4-C ha-1). Methane uptake rates were also 14% less for the control plots on Bozoisky-select pasture (-3.15 kg CH4 ha-1) compared to native rangeland (-3.60 kg CH4 ha-1). Future research should focus on CH4 and N2O fluxes from pasture 'hotspots', where nitrogen loading and soil compaction are commonly present. We tested the capacity of the biogeochemical model DAYCENT to simulate N2O and CH4 fluxes from control plots and cattle excrement amended soils of the shortgrass steppe for both plant communities. Cumulative N2O emissions from the urine treatment were overestimated using the DAYCENT model by a factor of 4 for native rangeland and by a factor of 5 for the Bozoisky-select pasture. While the measured and modeled cumulative emissions agreed reasonably well for the feces, water, and blank plots, the model did not accurately simulate the magnitude of seasonal N2O emissions from these plots, overestimating emissions during periods of high fluxes during the growing season and underestimating during periods of low fluxes such as the winter. The cause for the poor agreement between measured and modeled N2O emissions may be attributed to an overestimation of total system N, an overestimation of the proportion of nitrified-N emitted as N2O, and the possibility that a substantial amount (> 20%) of the urine-N was rapidly volatilized as NH3 due to the extremely dry conditions at the time of treatment application. Additional model validation for shortgrass steppe soils is needed using data sets that include extensive soil N data to accompany the trace gas data to determine if the model is accurately simulating nitrification rates, the proportion of nitrified-N emitted as N2O, and the proportion of N immobilized in microbial biomass. The model strongly overestimated CH4 uptake rates for the control plots by a factor of 3 for native rangeland and 2 for Bozoisky-select, while the excrement plots were overestimated by a factor of 2 for both plant communities. The model underestimated the optimum water content for maximum CH4 uptake by approximately 5%, which led to an overestimation of CH4 uptake by a factor of 2 to 4 during periods of biological limitation when soils were extremely dry. The agriculture reduction factor, which accounts for fertilization and cultivation events, reduced CH4 uptake from the urine and feces plots, but the uptake rates were still overestimated by a factor of 2 since the modeled failed to capture reduced uptake rates under low soil water content (< 0.15 volumetric water content). The overestimation of CH4 uptake may partly be resolved by increasing the optimum water content at which maximum CH4 uptake occurs, allowing the model to capture biological limitation on CH4 uptake.Item Open Access Modeling bioenergy agroecosystems for climate change mitigation and vulnerability assessment(Colorado State University. Libraries, 2017) Kent, Jeffrey, author; Paustian, Keith, advisor; Ogle, Stephen, committee member; McMaster, Greg, committee member; von Fischer, Joe, committee memberAgriculture is a major driver of anthropogenic climate change while also directly bearing its impacts. In addition to emissions related to farm operations and inputs, substantial greenhouse gases are released from cropland soils. These include carbon dioxide (CO2) fluxes due to long-term changes in soil organic carbon pools, and nitrous oxide (N2O) produced by soil microbes primarily from excess nitrogen (N) fertilizer not assimilated by crops. Agricultural bioenergy systems are expected to produce liquid fuels with lower life-cycle emissions than gasoline. Current US policy specifies several emissions reduction tiers for biomass-derived liquid fuels, ranging from 20% lower than gasoline for corn grain ethanol to 60% lower for ethanol made from perennial grasses or agricultural residues. While these tiers are based on detailed life-cycle assessments of "average" production conditions, they fail to convey the potentially large variability in emissions arising from farm management and biophysical factors. The first half of this dissertation uses a survey of management practices from suppliers of corn grain to a biorefinery in the US Midwest to explore the magnitude and sources of this variability. The first phase of that study finds that feedstock from most of the farms would achieve the statutory threshold of 20%, but that best-performing farms may be producing grain that would lead to fuel with 50% lower life-cycle emissions than gasoline. Key management practices identified are tillage intensity, efficient N fertilizer use and application of livestock manure. Crop residues, such as corn stover, can also be converted to ethanol. The second part of this study explore the sustainability of corn stover collection for ethanol production by a hypothetical dual-feedstock biorefinery. Stover collection presents a tradeoff: when used to produce ethanol, it displaces emissions from gasoline, but at the cost of less soil organic carbon (SOC) accumulation. Still, soils on these farms could sustain relatively high stover collection rates without net SOC losses or erosion, especially in the context of manure application and reduced tillage intensity. Climate change entails two major phenomena – increasing atmospheric [CO2] and increasing extreme high temperatures – likely to have opposing impacts on agricultural productivity, and these impacts will tend to increase over the course of the 21st Century. Chapter 4 of this work reviews the current understanding of crop responses to elevated atmospheric [CO2] and extreme heat as determined from agronomic studies and analyses of historical climate-yield data. It summarizes consensus findings and presents emerging topics in need of further research, and compares the state of knowledge with the simulation approaches employed by several major crop models. The increasing atmospheric [CO2] that largely drives climate change supports increased rates of photosynthesis in C3 plants and improved water use efficiency in all plant types. The magnitude of this fertilization effect is uncertain, however, and recent free atmospheric CO2 enrichment (FACE) experiments appear to show reduced gains relative to earlier enclosure experiments. Chapter 5 tests the hypothesis that the algorithm designed to simulate the CO2 effect in the DayCent ecosystem model overestimates crop responses to elevated [CO2] as observed under FACE conditions.Item Open Access Modeling soil organic matter: theory, development, and applications in bioenergy cropping systems(Colorado State University. Libraries, 2015) Campbell, Eleanor Elizabeth, author; Paustian, Keith, advisor; Parton, William J., committee member; Cotrufo, M. Francesca, committee member; Reardon, Kenneth F., committee memberSoil organic matter (SOM) is a complex, dynamic, and highly variable soil constituent that is of fundamental importance to many soil functions, terrestrial ecosystem processes, and biogeochemical cycles. Its importance extends across scales, ranging from site-specific impacts on soil fertility to the global net exchange of carbon between terrestrial systems and the atmosphere. Soil organic matter is impacted by human activities, as seen most directly in agricultural systems. In this context, SOM models play an important role in integrating the understanding of complex, interacting soil processes across temporal and spatial scales, contributing to land use decision making by providing comparative evaluation of soil impacts associated with different management practices. Crop-based bioenergy feedstock productions systems are an emerging area for these types of SOM model applications. However, model evaluations are dependent on the theoretical basis of a given SOM model, as well as the quality of data used to drive the model for a given system or management scenario. This study therefore explores linkages between advances in the theoretical understanding of SOM dynamics, the development of SOM models to reflect these advances, and the application of SOM models to assess crop-based bioenergy production systems. First, five emerging areas in SOM research were reviewed in the context of SOM models, including SOM stabilization mechanisms, saturation kinetics, temperature sensitivity, dynamics in deep soils, and incorporation into earth system models. These reviews demonstrated the importance of identifying where SOM model development and applications are most limited, whether in theoretical understanding, in model implementation, or in data availability. For example, SOM saturation kinetics is theoretically well understood but remains difficult to implement in SOM models, only yielding improvements in a narrow set of ecological conditions. SOM temperature sensitivity and deep soil dynamics, however, are more limited by poor data availability in addition to poor theoretical understanding of interacting processes. A selection of shortfalls in SOM modeling were then addressed and explored with the Litter Decomposition and Leaching (LIDEL) model, a litter decomposition model that incorporates dynamic microbial carbon use efficiency (CUE) and yields dissolved organic carbon (DOC) as one of the byproducts of litter decomposition. In this analysis a hierarchical Bayesian statistical approach was used to test model performance and estimate unknown model parameters using experimental data. While this analysis showed the LIDEL model successfully integrates hypotheses for litter nitrogen and lignin controls on dynamic microbial CUE and the generation of DOC from litter decomposition, there remains a great deal of uncertainty in the rate of microbial biomass turnover as well as the proportioning of biomass from microbial turnover between solid versus soluble microbial products. Targeted experimental evaluation of the generation of DOC from microbes versus litter would support greater certainty in these model parameters and further model development for more general applications. Finally, the performance of the DAYCENT ecosystem model was evaluated in simulating US corn residue removal and Brazilian sugarcane production, two types of crop-based bioenergy feedstocks. DAYCENT is a process-based ecosystem model that integrates a soil organic carbon model to simulate carbon and nitrogen cycling processes through plant-soil interactions. The results of DAYCENT corn residue removal simulations highlighted several DAYCENT model biases, such as low corn yield estimates in dry regions and an overestimation of soil carbon loss with conventional tillage. Despite these biases, the results showed the importance of considering interactive effects between corn residue removal and other crop management practices in this type of bioenergy feedstock production system. The results suggest corn residue removal is ideally paired with management practices—such as reduced tillage—to maintain or improve soil carbon stocks. The analysis of Brazilian sugarcane management practices also highlighted management practices poorly simulated by DAYCENT, in particular identifying the need to improve DAYCENT simulations of high N₂O emission conditions observed in mechanically-harvested sugarcane, perhaps by adding simulation of DOC movement across the soil profile. However, this analysis also identified a need for more accurate and consistent daily precipitation data to drive DAYCENT simulations of N₂O emissions from Brazilian sugarcane management practices, particularly as there is interest in regionally-scaled analyses of direct greenhouse gas emissions from sugarcane production in Brazil. Taken together, the results of this study show the importance of a close connection between emerging areas in SOM theory, SOM model developments, and SOM model applications in crop-based bioenergy feedstock production systems. This connection allows for the identification of specific areas in need of further research, whether developing new modeling approaches or gathering additional data to parameterize, drive, and evaluate model simulations. This connection should remain a central emphasis as SOM models are increasingly incorporated into crop-based bioenergy policy and land management decision making.Item Open Access Simulating canopy dynamics, productivity and water balance of annual crops from field to regional scales(Colorado State University. Libraries, 2016) Zhang, Yao, author; Paustian, Keith, advisor; Arabi, Mazdak, committee member; Parton, William, committee member; Schipanski, Meagan, committee memberTo provide better understanding of natural processes and predictions for decision support, dynamic models have been used to assess impact of climate, soils and management on crop production, water use, and other responses from field to regional scales. It is important to continue to improve the prediction accuracy and increase the reliability. In this work, we first improved the DayCent ecosystem model by developing a new empirical method for simulating green leaf area index (GLAI) of annual crops. Its performance has been validated using experimental observations from different experimental field locations as well as more aggregate NASS yield data spanning the country. Additionally, sensitivity and uncertainty of important parts of the crop growth model have been quantified. Our results showed the new model provided reliable predictions on crop GLAI, biomass, grain yield, evapotranspiration (ET), and soil water content (SWC) at field scale at various locations. At national scale, the predictions of grain yields were generally accurate with the model capable of representing the geographically-distributed differences in crop yields due to climate, soil, and management. The results indicated that the model is capable of providing insightful predictions for use in management and policy decision making. Although there are challenges to be addressed, our results indicate that the DayCent model can be a valuable tool to assess crop yield changes and other agroecosystem processes under scenarios of climate change in the future.Item Open Access Towards the systematic identification of low-cost ecosystem-mediated carbon sequestration opportunities in bioenergy supply chains(Colorado State University. Libraries, 2015) Field, John L., author; Willson, Bryan, advisor; Paustian, Keith, advisor; Bradley, Thomas, committee member; Leach, Jan, committee member; Marchese, Anthony, committee memberBecause the dedicated production of terrestrial biomass feedstocks involves the fixation of atmospheric carbon, carefully managed biofuel and bioenergy supply chains are increasingly recognized as an opportunity for carbon sequestration in soils or geological reservoirs in addition to their climate change mitigation value via the displacement of fossil fuel use. Bioenergy involves the coupling of agricultural systems and industrial supply chains, and finding optimal system designs often requires navigating a fundamental tension between maximizing overall system productivity while simultaneously limiting the intensification of feedstock exploitation to sustainable levels. Bioenergy sustainability analyses are further complicated by strong spatial heterogeneities in feedstock production performance, fundamentally different emission mechanisms across the agricultural and industrial phases of the biofuel lifecycle, and the tendency to perform environmental assessments and economic analyses in isolation. Well-designed integrated assessments are necessary to identify the total amounts and time dynamics of sequestration possible in such systems, to put those results in context relative to other supply chain impacts, and to understand tradeoffs between various environmental impact criteria and production costs. This dissertation starts with a thorough review of the bioenergy lifecycle assessment (LCA) literature to identify outstanding climate impact accounting challenges and inform the integration of production cost estimates. Two integrated assessment case studies are then undertaken to identify low-cost opportunities for improving carbon sequestration at different points in the bioenergy supply chain. The first focuses on feedstock production, assessing the potential for increasing soil carbon sequestration in bioenergy landscapes based on the cultivation of perennial grasses. A spatially-explicit landscape analysis system is created around a newly-parameterized version of the DayCent biogeochemistry model, and switchgrass productivity and soil greenhouse gas balance are assessed across gradients of land quality and cultivation intensity in a real-world bioenergy landscape in western Kansas. Integrating these ecosystem simulation results with existing LCA, farm enterprise budget, and biomass transport models allows for the quantification of landscape level cost – mitigation tradeoffs under various system design strategies and policy constraints. The second case study focuses downstream in the supply chain, considering the use of low-value conversion co-products as soil amendments to improve agroecosystem sustainability. The biochar co-product from a hypothetical thermochemical conversion system in the Colorado Front Range is assessed using simplified models of biochar recalcitrance and agronomic benefits as a function of feedstock material and conversion method. Together, these case study results are illustrative of the potential costs of improving ecosystem-mediated carbon sequestration in bioenergy systems, and the ongoing work required for full global supply chain optimization.