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Post, Wilfred M

Publications and source records attributed to Post, Wilfred M.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Global Simulation of Bioenergy Crop Productivity: Analytical framework and Case Study for Switchgrass

Contemporary global assessments of the deployment potential and sustainability aspects of biofuel crops lack quantitative details. This paper describes an analytical framework capable of meeting the challenges associated with global scale agro-ecosystem modeling. We designed a modeling platform for bioenergy crops, consisting of five major components: (i) standardized global natural resources and management data sets, (ii) global simulation unit and management scenarios, (iii) model calibration and validation, (iv) high-performance computing (HPC) modeling, and (v) simulation output processing and analysis. A case study with the HPC- Environmental Policy Integrated Climate model (HPC-EPIC) to simulate a perennial bioenergy crop, switchgrass (Panicum virgatum L.) and global biomass feedstock analysis on grassland demonstrates the application of this platform. The results illustrate biomass feedstock variability of switchgrass and provide insights on how the modeling platform can be expanded to better assess sustainable production criteria and other biomass crops. Feedstock potentials on global grasslands and within different countries are also shown. Future efforts involve developing databases of productivity, implementing global simulations for other bioenergy crops (e.g. miscanthus, energycane and agave), and assessing environmental impacts under various management regimes. We anticipated this platform will provide an exemplary tool and assessment data for international communities to conduct global analysis of biofuel biomass feedstocks and sustainability.

Nair, S. Surendran↗
DOE OSTI2013

AggModel: A soil organic matter model with measurable pools for use in incubation studies

Current soil organic matter (SOM) models are empirical in nature by employing few conceptual SOM pools that have a specific turnover time, but that are not measurable and have no direct relationship with soil structural properties. Most soil particles are held together in aggregates and the number, size and stability of these aggregates significantly affect the size and amount of organic matter contained in these aggregates, and its susceptibility to decomposition. While it has been shown that soil aggregates and their dynamics can be measured directly in the laboratory and in the field, the impact of soil aggregate dynamics on SOM decomposition has not been explicitly incorporated in ecosystem models. Here, we present AggModel, a conceptual and simulation model that integrates soil aggregate and SOM dynamics. In AggModel, we consider unaggregated and microaggregated soil that can exist within or external to macroaggregated soil. Each of the four aggregate size classes contains particulate organic matter and mineral-associated organic matter fractions. We used published data from laboratory incubations to calibrate and validate the biological and environmental effects on the rate of formation and breakdown of macroaggregates and microaggregates, and the organic matter dynamics within these different aggregate fractions. After calibration, AggModel explained more than 70% of the variation in aggregate masses and over 90% of the variation in aggregate-associated carbon. The model estimated the turnover time of macroaggregates as 32 days and 166 days for microaggregates. Sensitivity analysis of AggModel parameterization supported the notion that macroaggregate turnover rate has a strong control over microaggregate masses and, hence, carbon sequestration. In addition to AggModel being a proof-of-concept, the advantage of a model that is based on measurable SOM fractions is that its internal structure and dynamics can be directly calibrated and validated by using experimental data. In conclusion, AggModel successfully incorporates the explicit representation for the turnover of soil aggregates and their influence on SOM dynamics and can form the basis for new SOM modules within existing ecosystem models.

Macroaggregates↗
DOE OSTI2013

Hierarchical Marginal Land Assessment for Land Use Planning

Marginal land provides an alternative potential for food and bioenergy production in the face of limited land resources; however, effective assessment of marginal lands is not well addressed. Concerns over environmental risks, ecosystem services and sustainability for marginal land have been widely raised. The objective of this study was to develop a hierarchical marginal land assessment framework for land use planning and management. We first identified major land functions linking production, environment, ecosystem services and economics, and then classified land resources into four categories of marginal land using suitability and limitations associated with major management goals, including physically marginal land, biologically marginal land, environmental-ecological marginal land, and economically marginal land. We tested this assessment framework in south-western Michigan, USA. Our results indicated that this marginal land assessment framework can be potentially feasible on land use planning for food and bioenergy production, and balancing multiple goals of land use management. We also compared our results with marginal land assessment from the Conservation Reserve Program (CRP) and land capability classes (LCC) that are used in the US. The hierarchical assessment framework has advantages of quantitatively reflecting land functions and multiple concerns. This provides a foundation upon which focused studies can be identified in order to improve the assessment framework by quantifying high-resolution land functions associated with environment and ecosystem services as well as their criteria are needed to improve the assessment framework.

Kang, Shujiang↗
DOE OSTI2013

A note on the reverse Michaelis-Menten kinetics

We theoretically derive a general equation describing the enzyme kinetics that can be further simplified to the typical Michaelis-Menten (M-M) kinetics and the reverse M-M equation (RM-M) proposed by Schimel and Weintraub (2003). We discuss the conditions under which the RM-M is valid with this theoretical derivation. These conditions are contrary to the assumptions of Schimel and Weintraub (2003) and limit the applicability of the model in field soil environments. Nonetheless, Schimel and Weintraub s RM-M model is useful and has the ability to produce a non-linear response of SOM decomposition to enzyme concentration consistent with observations. Regardless of the theoretical basis, if we assume that the M-M and the RM-M could be equivalent, our sensitivity analysis indicates that enzyme plays a more sensitive role in the M-M kinetics compared with in the RM-M kinetics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

A global analysis of soil microbial biomass carbon, nitrogen and phosphorus in terrestrial ecosystems

Soil microbes play a pivotal role in regulating land-atmosphere interactions; the soil microbial biomass carbon (C), nitrogen (N), phosphorus (P) and C:N:P stoichiometry are important regulators for soil biogeochemical processes; however, the current knowledge on magnitude, stoichiometry, storage, and spatial distribution of global soil microbial biomass C, N, and P is limited. In this study, 3087 pairs of data points were retrieved from 281 published papers and further used to summarize the magnitudes and stoichiometries of C, N, and P in soils and soil microbial biomass at global- and biome-levels. Finally, global stock and spatial distribution of microbial biomass C and N in 0-30 cm and 0-100 cm soil profiles were estimated. The results show that C, N, and P in soils and soil microbial biomass vary substantially across biomes; the fractions of soil nutrient C, N, and P in soil microbial biomass are 1.6% in a 95% confidence interval of (1.5%-1.6%), 2.9% in a 95% confidence interval of (2.8%-3.0%), and 4.4% in a 95% confidence interval of (3.9%-5.0%), respectively. The best estimates of C:N:P stoichiometries for soil nutrients and soil microbial biomass are 153:11:1, and 47:6:1, respectively, at global scale, and they vary in a wide range among biomes. Vertical distribution of soil microbial biomass follows the distribution of roots up to 1 m depth. The global stock of soil microbial biomass C and N were estimated to be 15.2 Pg C and 2.3 Pg N in the 0-30 cm soil profiles, and 21.2 Pg C and 3.2 Pg N in the 0-100 cm soil profiles. We did not estimate P in soil microbial biomass due to data shortage and insignificant correlation with soil total P and climate variables. The spatial patterns of soil microbial biomass C and N were consistent with those of soil organic C and total N, i.e. high density in northern high latitude, and low density in low latitudes and southern hemisphere.

Xu, Xiaofeng↗
DOE OSTI2013

Development of microbial-enzyme-mediated decomposition model parameters through steady-state and dynamic analyses

We developed a Microbial-ENzyme-mediated Decomposition (MEND) model, based on the Michaelis-Menten kinetics, that describes the dynamics of physically defined pools of soil organic matter (SOC). These include particulate, mineral-associated, dissolved organic matter (POC, MOC, and DOC, respectively), microbial biomass, and associated exoenzymes. The ranges and/or distributions of parameters were determined by both analytical steady-state and dynamic analyses with SOC data from the literature. We used an improved multi-objective parameter sensitivity analysis (MOPSA) to identify the most important parameters for the full model: maintenance of microbial biomass, turnover and synthesis of enzymes, and carbon use efficiency (CUE). The model predicted an increase of 2 C (baseline temperature =12 C) caused the pools of POC-Cellulose, MOC, and total SOC to increase with dynamic CUE and decrease with constant CUE, as indicated by the 50% confidence intervals. Regardless of dynamic or constant CUE, the pool sizes of POC, MOC, and total SOC varied from 8% to 8% under +2 C. The scenario analysis using a single parameter set indicates that higher temperature with dynamic CUE might result in greater net increases in both POC-Cellulose and MOC pools. Different dynamics of various SOC pools reflected the catalytic functions of specific enzymes targeting specific substrates and the interactions between microbes, enzymes, and SOC. With the feasible parameter values estimated in this study, models incorporating fundamental principles of microbial-enzyme dynamics can lead to simulation results qualitatively different from traditional models with fast/slow/passive pools.

09 BIOMASS FUELS↗
DOE OSTI2013

The Unified North American Soil Map and Its Implication on the Soil Organic Carbon Stock in North America

The Unified North American Soil Map (UNASM) was developed to provide more accurate regional soil information for terrestrial biosphere modeling. The UNASM combines information from state-of-the-art U.S. STATSGO2 and Soil Landscape of Canada (SLCs) databases. The area not covered by these datasets is filled with the Harmonized World Soil Database version 1.1 (HWSD1.1). The UNASM contains maximum soil depth derived from the data source as well as seven soil attributes (including sand, silt, and clay content, gravel content, organic carbon content, pH, and bulk density) for the top soil layer (0-30 cm) and the sub soil layer (30-100 cm) respectively, of the spatial resolution of 0.25 degrees in latitude and longitude. There are pronounced differences in the spatial distributions of soil properties and soil organic carbon between UNASM and HWSD, but the UNASM overall provides more detailed and higher-quality information particularly in Alaska and central Canada. To provide more accurate and up-to-date estimate of soil organic carbon stock in North America, we incorporated Northern Circumpolar Soil Carbon Database (NCSCD) into the UNASM. The estimate of total soil organic carbon mass in the upper 100 cm soil profile based on the improved UNASM is 347.70 Pg, of which 24.7% is under trees, 14.2% is under shrubs, and 1.3% is under grasses and 3.8% under crops. This UNASM data will provide a resource for use in land surface and terrestrial biogeochemistry modeling both for input of soil characteristics and for benchmarking model output.

Liu, Shishi↗
DOE OSTI2013

Marginal Lands: Concept, Assessment and Management

Marginal lands have received wide attention for their potential to improve food security and support bioenergy production. However, environmental, ecosystem service, and sustainability concerns have been widely raised over the use of marginal land. Knowledge of the extent, location, and quality of marginal lands as well as their assessment and management are limited and diverse. This paper provides a review of the historical development of marginal concept, its application and assessment. Limitations and priority research needs of marginal land assessment and management were discussed.

Kang, Shujiang↗
DOE OSTI2013

Global Simulation of Bioenergy Crop Productivity: Analytical Framework and Case Study for Switchgrass

A global energy crop productivity model that provides geospatially explicit quantitative details on biomass potential and factors affecting sustainability would be useful, but does not exist now. This study describes a modeling platform capable of meeting many challenges associated with global-scale agro-ecosystem modeling. We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized natural resources datasets, (ii) global field-trial data and crop management practices, (iii) simulation units and management scenarios, (iv) model calibration and validation, (v) high-performance computing (HPC) simulation, and (vi) simulation output processing and analysis. The HPC-Environmental Policy Integrated Climate (HPC-EPIC) model simulated a perennial bioenergy crop, switchgrass (Panicum virgatum L.), estimating feedstock production potentials and effects across the globe. This modeling platform can assess soil C sequestration, net greenhouse gas (GHG) emissions, nonpoint source pollution (e.g., nutrient and pesticide loss), and energy exchange with the atmosphere. It can be expanded to include additional bioenergy crops (e.g., miscanthus, energy cane, and agave) and food crops under different management scenarios. The platform and switchgrass field-trial dataset are available to support global analysis of biomass feedstock production potential and corresponding metrics of sustainability.

Kang, Shujiang↗
DOE OSTI2013

Decomposition of added and native organic carbon from physically separated fractions of diverse soils

There have been increasing efforts to understand the dynamics of organic carbon (OC) associated with measurable fractions of bulk soil.We compared the decomposition of native OC (native C) with that of an added substrate (glucose) on physically separated fractions of a diverse suite of soils. Five soil orders were selected from four contrasting climate zones (Mollisol from temperate, Ultisol and Oxisol from tropics, Andisol from sub-arctic, and Gelisol from arctic region). Soils from the A horizon were fractionated into particulate OC (POC) and mineral-associated OC (MOC) by a sizebased method. Fractions were incubated at 20 C and 50 % water-holding capacity in the dark after the addition of unlabeled D-glucose (0.4 mg C g 1 fraction) and U 14C glucose (296 Bq g 1 fraction). Respiration of glucose 14C indicated 64 to 84 % of added glucose 14C which was respired from POC and 62 to 70 % from MOC within 150 days of incubation, with more than half of the cumulative respiration occurring within 4 days. Native C respiration varied widely across fractions: 12 to 46 % of native C was respired from POC and 3 to 10 % was respired from MOC fractions. This suggested that native C was more stabilized on the MOC than on the POC, but respiration from the added glucose was generally similar for MOC and POC fractions. Our study suggests a fundamental difference between the behavior of freshly added C and native C from MOC and POC fractions of soils.

Jagadamma, Sindhu↗
DOE OSTI2012

Management Opportunities for Enhancing Terrestrial Carbon Dioxide Sinks

The potential for mitigating increasing atmospheric carbon dioxide concentrations through the use of terrestrial biological carbon (C) sequestration is substantial. Here, we estimate the amount of C being sequestered by natural processes at global, North American, and national US scales. We present and quantify, where possible, the potential for deliberate human actions – through forestry, agriculture, and use of biomass-based fuels – to augment these natural sinks. Carbon sequestration may potentially be achieved through some of these activities but at the expense of substantial changes in land-use management. Some practices (eg reduced tillage, improved silviculture, woody bioenergy crops) are already being implemented because of their economic benefits and associated ecosystem services. Given their cumulative greenhouse-gas impacts, other strategies (eg the use of biochar and cellulosic bioenergy crops) require further evaluation to determine whether widespread implementation is warranted.

Post, W M↗
DOE OSTI2012

North America carbon dioxide sources and sinks: magnitude, attribution, and uncertainty

North America is both a source and sink of atmospheric CO2. Sources, predominately fossil-fuel combustion in the United States along with contributions from deforestation in Mexico, add CO2 to the atmosphere. Most North America ecosystems, particularly regrowing forests in the United States, are sinks for atmospheric CO2. CO2 is removed from the atmosphere in photosynthesis, converted into biomass and stored as carbon in vegetation, soil and wood products. Fossil-fuel emissions dominate the North American source-sink balance. North America is a net source of atmospheric CO2 with ecosystem sinks balancing approximately 35% of fossil-fuel CO2 emissions from North America.

King, Anthony W↗
DOE OSTI2012

North American Carbon Project (NACP) Regional Interim Synthesis: Terrestrial Biospheric Model Intercomparison

Understanding of carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding to much larger terrestrial regions. Although models vary in their specific goals and approaches, their central role within carbon cycle science is to provide a better understanding of the mechanisms currently controlling carbon exchange. Recently, the North American Carbon Program (NACP) organized several interim-synthesis activities to evaluate and inter-compare models and observations at local to continental scales for the years 2000 to 2005. Here, we compare the results from the TBMs collected as part of the regional and continental interim-synthesis (RCIS) activities. The primary objective of this work is to synthesize and compare the 19 participating TBMs to assess current understanding of the terrestrial carbon cycle in North America.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Reconciling estimates of the contemporary North American carbon balance among terrestrial biosphere models, atmospheric inversions and a new approach for estimating net ecosystem exchange from inventory-based data

While fossil fuel emissions are calculated with relatively high precision, understanding the fate of those emissions with respect to sequestration in terrestrial ecosystems requires data and methods that can reduce uncertainties in the diagnosis of land-based CO2 sinks. The wide range in the land surface flux estimates is related to a number of factors, but most generally because of the different methodologies used to develop estimates of carbon stocks and flux, and the uncertainties inherent in each approach. The alternative approaches to estimating continental scale carbon fluxes that we explored here can be broadly classified as applying a top-down or bottom-up perspective. Top-down approaches calculate land-atmosphere carbon fluxes based on atmospheric budgets and inverse modeling. Bottom-up approaches rely primarily on measurements of carbon stock changes (the inventory approach) or on spatially distributed simulations of carbon stocks and/or fluxes using process-based modeling (the forward modelapproach).

Hayes, D J↗
DOE OSTI2012

Bioenergy crop models: Descriptions, data requirements and future challenges

Field studies that address the production of lignocellulosic biomass as a potential source of renewable energy are making available critical information for the development, validation, and use of bioenergy crop models. A literature survey revealed that 14 models have been developed and validated for herbaceous and woody bioenergy crops, and for Crassulacean acid metabolism (CAM) crops adapted to arid lands. These models simulate field-scale production of biomass for switchgrass (ALMANAC, EPIC, and Agro-BGC), miscanthus (MISCANFOR, MISCANMOD, and WIMOVAC), sugarcane (APSIM, AUSCANE, and CANEGRO), and poplar and willow (SECRETS and 3PG). Two models are adaptations of dynamic global vegetation models and simulate biomass yields of miscanthus and sugarcane as plant function types at regional scales (Agro-IBIS and LPJmL). A model of biomass production in CAM plants has been developed (EPI), but lacks the sophistication of the other models. Except for CAM plants, all the models include representations of leaf area dynamics, radiation interception and utilization, biomass production, and partitioning of biomass to roots and shoots. A few of the models are capable of simulating soil water, nutrient, and carbon cycle processes, making them especially useful for assessing environmental consequences (e.g., erosion and nutrient losses) associated with the field-scale deployment of bioenergy crops. Similar to other process-based models, simulations are challenged by computing and data management issues and an integrated framework for model testing and inter-comparison is needed. Considerable work remains concerning the development of models for unconventional bioenergy crops like CAM plants, generation and distribution of high-quality field data for model development and validation, and development of an integrated framework for efficient execution of large-scale simulations for use in planning regional to global sustainable bioenergy production systems.

Surendran Nair, Sujith↗
DOE OSTI2012

Parameter estimation for models of ligninolytic and cellulolytic enzyme kinetics

While soil enzymes have been explicitly included in the soil organic carbon (SOC) decomposition models, there is a serious lack of suitable data for model parameterization. This study provides well-documented enzymatic parameters for application in enzyme-driven SOC decomposition models from a compilation and analysis of published measurements. In particular, we developed appropriate kinetic parameters for five typical ligninolytic and cellulolytic enzymes ( -glucosidase, cellobiohydrolase, endo-glucanase, peroxidase, and phenol oxidase). The kinetic parameters included the maximum specific enzyme activity (Vmax) and half-saturation constant (Km) in the Michaelis-Menten equation. The activation energy (Ea) and the pH optimum and sensitivity (pHopt and pHsen) were also analyzed. pHsen was estimated by fitting an exponential-quadratic function. The Vmax values, often presented in different units under various measurement conditions, were converted into the same units at a reference temperature (20 C) and pHopt. Major conclusions are: (i) Both Vmax and Km were log-normal distributed, with no significant difference in Vmax exhibited between enzymes originating from bacteria or fungi. (ii) No significant difference in Vmax was found between cellulases and ligninases; however, there was significant difference in Km between them. (iii) Ligninases had higher Ea values and lower pHopt than cellulases; average ratio of pHsen to pHopt ranged 0.3 0.4 for the five enzymes, which means that an increase or decrease of 1.1 1.7 pH units from pHopt would reduce Vmax by 50%. (iv) Our analysis indicated that the Vmax values from lab measurements with purified enzymes were 1 2 orders of magnitude higher than those for use in SOC decomposition models under field conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

A Theoretical Reassessment of Microbial Maintenance and Implications for Microbial Ecology Modeling

We attempted to reconcile three microbial maintenance models (Herbert, Pirt, and Compromise) through a critical reassessment. We provided a rigorous proof that the true growth yield coefficient (YG) is the ratio of the specific maintenance rate (a in Herbert) to the maintenance coefficient (m in Pirt). Other findings from this study include: (1) the Compromise model is identical to the Herbert for computing microbial growth and substrate consumption, but it expresses the dependence of maintenance on both microbial biomass and substrate; (2) the maximum specific growth rate in the Herbert ( max,H) is higher than those in the other two models ( max,P and max,C), and the difference is the physiological maintenance factor (mq = a); and (3) the overall maintenance coefficient (mT) is more sensitive to mq than to the specific growth rate ( G) and YG. Our critical reassessment of microbial maintenance provides a new approach for quantifying some important components in soil microbial ecology models.

09 BIOMASS FUELS↗