Our first efforts in this direction have focused on s-wave superconductivity. We correctly reproduce the equilibrium behavior, as well as the basic ideas regarding superconductivity, e.g. super currents. Proceeding on to pumping, we have results indicating the presence of Higgs, or amplitude mode oscillations. The Higgs mode is a fundamental concept in broken symmetry states, yet has been elusive. In a superconductor, the Higgs mode does not couple directly to external fields, making it difficult to observe. By going to pump-probe experiments, one can perturb the superconductivity in such a way that the Higgs mode arises naturally. This is only possible in non-equilibrium, making it one of the first physical phenomena that are uniquely accessible by pump-probe experiments. Secondly, we completed and published our findings regarding the time-resolved photo emission response in the weak pumping limit. Following this, we further extended the code to allow for the self-consistent calculation of the electron Green’s function, which allowed us to observe the effect of strong pumping on the interactions. Recent experimental results indicated that upon illuminating the sample with a strong pump, the hallmarks of electron-phonon coupling known as “kinks” weaken. This was attributed to the decoupling of the electrons from the lattice. Our results showed that this is not the case; rather, the electrons are scattered to higher energies, leading to a similar reduction in the kink, although the coupling remains constant. In fact, we showed that there is a conserved sum rule for the electron-phonon interactions, indicating that this is a conserved quantity. This work provides a framework for future discussion of results in the field,hydroponic nft system where one needs to go beyond quasiequilibrium models and consider the full effects of the pump.

This LDRD integrates existing ESD expertise in ecosystem modeling and environmental microbiology to develop a modeling capability for the carbon and nitrogen cycle in high-latitude soils. High-latitude permafrost soils underlie approximately 26 % of terrestrial ecosystems and have the potential to significantly impact the future balance of Earth’s C and N cycles. Several models suggest that up to 90 % of the near-surface Arctic permafrost could thaw by 2100 affecting the structure and function of the microbial communities that mediate the majority of biological C and N cycling. These thermal, hydrological, geochemical and biological changes could lead to substantial increases in atmospheric CO2, CH4 and N2O. The efflux magnitudes of these gases from thawing permafrost are largely dependent on complex feed backs centering on the in situ diversity of C- and N-cycling microorganisms, the availability of N, and the physical changes that occur as permafrost thaws. Therefore, the development of a framework for simulating the emergence of microbial community structure based on a few physiological and genomic traits is a critical first step towards predicting how microbial communities will respond to the geochemical, thermal and hydrological changes accompanying permafrost thaw. A further outcome of understanding community emergence is the accurate prediction of rates that is a consequence of the emergence of particular microbial communities. Research over this part year has focused on one of the main goals of this LDRD, improvements of Earth System models using mechanistically focused trait-based models. Specifically, we have been developing a trait-based model of nitrogen fixation that will improve both the mechanistic approach the Community Land Model takes to predicting global and local rates of nitrogen fixation, and address fundamental questions regarding the limitation of ecosystem processes by nitrogen across local and regional scales. We take a comprehensive approach to modeling high-latitude microbial ecosystems, including the explicit representation of autotrophic and heterotrophic nitrogen fixers, and heterotrophic bacterial and fungal decomposers. Our model includes representations of both the phosphorus and molybdenum cycles and more broad environmental factors that limit microbial activity.

Our approach also accounts for physiologically important processes, including microbial nutrient use efficiency. This approach is important for understanding the interactions between the carbon and nitrogen cycle.Our approach sets out to answer why nitrogen is chronically limited, and also address how the niche of nitrogen fixing organisms might change over the coming decades, and the feedback this will have with the carbon cycle.This model couples the carbon, nitrogen and phosphorus cycles in an approach that has rarely been applied prior to our current work. This work will continue through additional funding from the NGEE-Arctic and NGEE-Tropics SFAs. Our most significant accomplishment to date is the further development of an experimental workflow for multi-modal characterization of microbial functional distribution in soils. To detect activity hot-spots in the soils we have developed approaches using short-lived 11C and 13N radioisotopes. We have successfully imaged 11CO2 fixation through photosynthesis in plants and biological soil crusts, 11C-CH4 retention by methane oxidizing bacteria and have shown preliminary data supporting our ability to visualize 13N2 fixation through endophytic nitrogen fixers. These labeling methods have been coupled with Positron Emission Tomography or Radio Phosphor Storage imaging. We have developed a workflow to sort soil individual aggregates from soils under sterile conditions and to characterize their surface chemical composition non-destructively via Fourier Transform Infrared spectroscopy equipped with an ATR prism. Aggregates are then clustered into chemotypes based on their chemical spectra. Aggregate scale genomic techniques have been developed to determine the microbial composition and metabolic potential microbial composition, these include efficient DNA extraction and purification procedures and novel picogram scale high throughput DNA sequencing library construction methods – the first of their kind for soil systems. We are attempting to define relationships between microbial metabolic potential and aggregate chemical and physical properties. To determine the physical constraints on microbial activity at the aggregate scale we have further developed X-ray micro/nano-computed tomography to achieve nanometer scale measurements of pore volume and pore network topography – these data are now being used to parameterize pore scale models of microbial activity.

We have continued to test our improved experimental workflow on several contrasting soils and successfully analyzed their bio-geochemical properties. Three manuscripts are in draft form and a fourth has been published.This LDRD project started in May 2013. A postdoctoral researcher with extensive experience with ecosystem demography modeling was hired in June 2013 , and significant progress has been made addressing all questions. Jennifer Holm and Robinson Negron-Juarez also participated in LDRD activities. These activities included completing a sensitivity analysis using a version of the Ecosystem Demography model to rising atmospheric CO2, and a comparison of that CO2 response to extensive field data from a Central Amazon site in Brazil. The modeling and analytical work for this activity has been accomplished, and a manuscript is just about ready to submit . We also made significant progress integrating ED2 functionality into the larger CLM framework, including developing a test bed with data from the Central Amazon site, which enables exploration of drought-mortality interactions in a landscape context. Additional work focused on model structures required to simulate shifts in disturbance regimes. Work carried out under this LDRD was instrumental in Berkeley Lab being tasked by DOE-BER to lead the Next Generation Ecosystem Experiment Tropics , and the PI of this LDRD has been tasked to lead NGEE Tropics as Director. The NGEE Tropics proposal is currently under review, with a final decision expected late February 2015. The field of hydrogeophysics has advanced the ability to use geophysical data to quantify the shallow subsurface over large spatial extents and in a minimally invasive manner. Remote sensing methodologies have also greatly improved in recent years,nft channel enabling high resolution estimation of land surface properties, such as topography and vegetation density. The purpose of this project is to develop new methods to combine unmanned aerial vehicle technology with ground surface geophysical characterization to perform co-characterization of above and below ground terrestrial processes. Such co-characterization offers a new paradigm for quantifying of many critical zone processes that involve interactions between above- and below ground processes relevant to carbon cycling, agriculture, energy production and water resources. The proposed scope takes advantage of and forms a new collaboration between the Earth Sciences and Engineering Divisions at LBNL. The first task is to develop a self contained instrumentation package capable of data acquisition, storage, and independent communication with remotely based controllers. This will enable us to run time-lapse based acquisition with optimal automatization using UAV- and/or pole- based platforms. The second task is to develop infrastructure to reconstruct mosaics and digital surface models from above ground datasets, and process such data to a point where they can be meaningfully integrated with below ground datasets. We note that such co-characterization approach does not exist and thus the outcome is expected to make a strong contribution to research in the field of Earth system. A significant accomplishment has been to develop a reproducible protocol to acquire multi-spectral images using UAV- and/or pole- based platforms. To this end, a mini-computer has been used to implement an “in house” developed software that enable controlling the camera parameters ), data storage and data transfer. This platform can be adapted to many types of different multi-spectral cameras. The approach has been successfully tested for continuous monitoring of landscape properties using a pole-based approach at the Next Generation Ecosystem Experiment site in Barrow, and will be tested using a UAV-based approach as soon as a FAA authorization will be obtained.

A second main accomplishment is the development of an infrastructure that enables georeferenced mosaic reconstruction, estimation of various spatial metrics and calibration of remote sensing measurements using ‘point’ measurements. Testing this approach to infer DSM and mosaics along a 450×40 m corridor using a kite-based approach at the NGEE-Arctic field site has been successful; comparison with ground control points showed an error of less than -+ 5 cm in x,y and z direction and a spatial resolution of about 2 cm. In addition, an approach has been developed to correct for various light conditions the images acquired using a pole-based approach at the NGEE site. The cocharacterization enabled by the above developments has showed amongst others that vegetation greenness index and subsurface bulk electrical conductivity reach a correlation coefficient up to 0.86 at the peak of the growing season. The study has documented the significant co-variability of vegetation and soil moisture in the Arctic ecosystem, and the ability of advanced above-and-below ground sensing approaches to monitor their interactions and feed backs.The purpose of this one-year project was to develop and exercise a method to investigate the pore geometry, connectedness, and flow in nanoporous materials including shales and tight sandstones at the meso scale . Pore geometry and connectedness control natural gas movement at this scale. Included in this project were high-resolution 3-D imaging of the porespace of a large sample , and simulation of single-phase flow through the porespace of the sample. Previous studies have attempted this, but have been hindered by the scale that the pore geometry could be quantified because the pores are very small , and the porosity is low . These studies resulted in a very limited number of very short flow paths which are not adequate for use to describe flow at a larger scale. Our approach was to extend previous studies of tight media to larger scales that approach and exceed the representative elementary volume scale. We also sought to link imaging and computational techniques in order to understand mesoscale emergent processes. We sought to perform high-resolution simulations of flow through the porespace using the Chombo code and the high-performance computing facilities at NERSC. We have had several significant accomplishments. First, we obtained several large data sets, which are amongst the largest in the world if not the largest, using the Focused Ion Beam/Scanning Electron Microscope technique. We engaged Tescan USA in support of codeveloping the imaging technique using their newly developed plasma milling tool, based on preliminary work performed using the gallium ion milling tool at the Molecular Foundry. We focused on the structure and porespace of one Marcellus shale sample. This sample was selected because it is from a productive region of the Marcellus, and several other studies have been conducted on nearby samples. A number of data sets were collected at a variety of resolutions in support of this.