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DOE OSTI2024

Quantitative phenotyping of crop roots with spectral electrical impedance tomography: a rhizotron study with optimized measurement design

Background: Root systems are key contributors to plant health, resilience, and, ultimately, yield of agricultural crops. To optimize plant performance, phenotyping trials are conducted to breed plants with diverse root traits. However, traditional analysis methods are often labour-intensive and invasive to the root system, therefore limiting high-throughput phenotyping. Spectral electrical impedance tomography (sEIT) could help as a non-invasive and cost-efficient alternative to optical root analysis, potentially providing 2D or 3D spatio-temporal information on root development and activity. Although impedance measurements have been shown to be sensitive to root biomass, nutrient status, and diurnal activity, only few attempts have been made to employ tomographic algorithms to recover spatially resolved information on root systems. In this study, we aim to establish relationships between tomographic electrical polarization signatures and root traits of different fine root systems (maize, pinto bean, black bean, and soy bean) under hydroponic conditions. Results: Our results show that, with the use of an optimized data acquisition scheme, sEIT is capable of providing spatially resolved information on root biomass and root surface area for all investigated root systems. We found strong correlations between the total polarization strength and the root biomass (R 2 = 0.82) and root surface area (R 2 = 0.8). Our findings suggest that the captured polarization signature is dominated by cell-scale polarization processes. Additionally, we demonstrate that the resolution characteristics of the measurement scheme can have a significant impact on the tomographic reconstruction of root traits. Conclusion: Our findings showcase that sEIT is a promising tool for the tomographic reconstruction of root traits in high-throughput root phenotyping trials and should be evaluated as a substitute for traditional, often time-consuming, root characterization methods.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗

DOE OSTI2025

Electron Energy-Loss Spectroscopy and Differential Phase Contrast Imaging with Active Decision in Multimodal Electron Microscopy: Isotopic detection at the atomic scale

Isotopic engineering provides a powerful route to control phonon behavior in crystalline solids, enabling fundamental studies of lattice dynamics and heat transport at the atomic scale. Here, we directly visualize isotope-dependent phonon propagation in epitaxial Cr 2 O 3 using aberration-corrected scanning transmission electron microscopy (STEM) combined with monochromated, high-energy-resolution electron energy-loss spectroscopy (EELS). Guided by ab initio phonon calculations, we demonstrate that optical phonon modes above 70 meV are predominantly oxygen-derived and exhibit measurable redshifts upon substitution of natural 16 O by enriched 18 O. Spatially resolved vibrational spectrum imaging reveals isotope-enriched tracer layers within Cr 2 O 3 thin films, correlating isotope concentration with phonon intensity variations and vibrational energy shifts. At the nanometer and atomic scales, vibrational EELS mapping uncovers coherent phonon propagation across isotopic interfaces, consistent with theoretical phonon density of states and dispersion relations. These results establish vibrational EELS as a quantitative probe for isotope-dependent phonon transport in materials, opening new possibilities for studying energy dissipation and lattice dynamics.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Extended X-Ray Monitoring of Gravitational Lenses with Chandra and Joint Constraints on X-Ray Emission Regions

We present an X-ray photometric analysis of six gravitationally lensed quasars, with observation campaigns spanning from 5 to 14 years, measuring the total (0.83–21.8 keV restframe), soft- (0.83–3.6 keV), and hard- (3.6–21.8 keV) band image flux ratios for each epoch. Using the ratios of the model-predicted macro-magnifications as baselines, we build differential microlensing light curves and obtain joint likelihood functions for the average X-ray emission region sizes. Our analysis yields a probability distribution function for the average half-light radius of the X-ray emission region in the sample that peaks slightly above 1 gravitational radius and with nearly indistinguishable 68% confidence (one-sided) upper limits of 17.8 and 18.9 gravitational radii for the soft and hard X-ray emitting regions, assuming a mean stellar mass of 0.3 M {sub ⊙}. We see hints of energy dependent microlensing between the soft and hard bands in two of the objects. In a separate analysis on the root-mean-square (rms) of the microlensing variability, we find significant differences between the soft and hard bands, but the sign of the difference is not consistent across the sample. This suggests the existence of some kind of spatial structure to the X-ray emission in an otherwise extremely compact source. We also discover a correlation between the rms microlensing variability and the average microlensing amplitude.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Downscaling Solar Power Output to 4-Seconds for Use in Integration Studies (Presentation)

High penetration renewable integration studies require solar power data with high spatial and temporal accuracy to quantify the impact of high frequency solar power ramps on the operation of the system. Our previous work concentrated on downscaling solar power from one hour to one minute by simulation. This method used clearness classifications to categorize temporal and spatial variability, and iterative methods to simulate intra-hour clearness variability. We determined that solar power ramp correlations between sites decrease with distance and the duration of the ramp, starting at around 0.6 for 30-minute ramps between sites that are less than 20 km apart. The sub-hour irradiance algorithm we developed has a noise floor that causes the correlations to approach ~0.005. Below one minute, the majority of the correlations of solar power ramps between sites less than 20 km apart are zero, and thus a new method to simulate intra-minute variability is needed. These intra-minute solar power ramps can be simulated using several methods, three of which we evaluate: a cubic spline fit to the one-minute solar power data; projection of the power spectral density toward the higher frequency domain; and average high frequency power spectral density from measured data. Each of these methods either under- or over-estimates the variability of intra-minute solar power ramps. We show that an optimized weighted linear sum of methods, dependent on the classification of temporal variability of the segment of one-minute solar power data, yields time series and ramp distributions similar to measured high-resolution solar irradiance data.

14 SOLAR ENERGY↗

DOE OSTI2013

Downscaling Solar Power Output to 4-Seconds for Use in Integration Studies: Preprint

14 SOLAR ENERGY↗

DOE OSTI2018

A Big Data Analytics Framework for HPC Log Data: Three Case Studies Using the Titan Supercomputer Log

Reliability, availability and serviceability (RAS) logs of high performance computing (HPC) resources, when closely investigated in spatial and temporal dimensions, can provide invaluable information regarding system status, performance, and resource utilization. These data are often generated from multiple logging systems and sensors that cover many components of the system. The analysis of these data for finding persistent temporal and spatial insights faces two main difficulties: the volume of RAS logs makes manual inspection difficult and the unstructured nature and unique properties of log data produced by each subsystem adds another dimension of difficulty in identifying implicit correlation among recorded events. To address these issues, we recently developed a multi-user Big Data analytics framework for HPC log data at Oak Ridge National Laboratory (ORNL). This paper introduces three in-progress data analytics projects that leverage this framework to assess system status, mine event patterns, and study correlations between user applications and system events. We describe the motivation of each project and detail their workflows using three years of log data collected from ORNL's Titan supercomputer.

Park, Byung↗

DOE OSTI2012

An underestimated role of precipitation frequency in regulating summer soil moisture

Soil moisture induced droughts are expected to become more frequent under future global climate change. Precipitation has been previously assumed to be mainly responsible for variability in summer soil moisture. However, little is known about the impacts of precipitation frequency on summer soil moisture, either interannually or spatially. To better understand the temporal and spatial drivers of summer drought, 415 site yr measurements observed at 75 flux sites world wide were used to analyze the temporal and spatial relationships between summer soil water content (SWC) and the precipitation frequencies at various temporal scales, i.e., from half-hourly, 3, 6, 12 and 24 h measurements. Summer precipitation was found to be an indicator of interannual SWC variability with r of 0.49 (p < 0.001) for the overall dataset. However, interannual variability in summer SWC was also significantly correlated with the five precipitation frequencies and the sub-daily precipitation frequencies seemed to explain the interannual SWC variability better than the total of precipitation. Spatially, all these precipitation frequencies were better indicators of summer SWC than precipitation totals, but these better performances were only observed in non-forest ecosystems. Our results demonstrate that precipitation frequency may play an important role in regulating both interannual and spatial variations of summer SWC, which has probably been overlooked or underestimated. However, the spatial interpretation should carefully consider other factors, such as the plant functional types and soil characteristics of diverse ecoregions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Building spatial symmetries into parameterized quantum circuits for faster training

Abstract Practical success of quantum learning models hinges on having a suitable structure for the parameterized quantum circuit. Such structure is defined both by the types of gates employed and by the correlations of their parameters. While much research has been devoted to devising adequate gate-sets, typically respecting some symmetries of the problem, very little is known about how their parameters should be structured. In this work, we show that an ideal parameter structure naturally emerges when carefully considering spatial symmetries (i.e. the symmetries that are permutations of parts of the system under study). Namely, we consider the automorphism group of the problem Hamiltonian, leading us to develop a circuit construction that is equivariant under this symmetry group. The benefits of our novel circuitstructure, called ORB, are numerically probed in several ground-state problems. We find a consistent improvement (in terms of circuit depth, number of parameters required, and gradient magnitudes) compared to literature circuit constructions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

XCT analysis of the influence of melt strategies on defect population in Ti–6Al–4V components manufactured by Selective Electron Beam Melting

Selective Electron Beam Melting (SEBM) is a promising powder bed Additive Manufacturing technique for near-net-shape manufacture of high-value titanium components. However without post-manufacture HIPing the fatigue life of SEBM parts is currently dominated by the presence of porosity. In this study, the size, volume fraction, and spatial distribution of the pores in model samples have been characterised in 3D, using X-ray Computed Tomography, and correlated to the process variables. The average volume fraction of the pores (< 0.2%) was measured to be lower than that usually observed in competing processes, such as selective laser melting, but a strong relationship was found with the different beam strategies used to contour, and infill by hatching, a part section. The majority of pores were found to be small spherical gas pores, concentrated in the infill hatched region; this was attributed to the lower energy density and less focused beam used in the infill strategy allowing less opportunity for gas bubbles to escape the melt pool. Overall, increasing the energy density or focus of the beam was found to correlate strongly to a reduction in the level of gas porosity. Rarer irregular shaped pores were mostly located in the contour region and have been attributed to a lack of fusion between powder particles. - Graphical abstract: Display Omitted - Highlights: • Vast majority of defects detected were small spherical gas pores. • Gas bubbles trapped in the powder granules expand and coalesce in the melt pool. • Pores have been shown not to be randomly distributed. • Larger and deeper melt pools give more opportunity for gas to escape. • Minor changes to melt strategy result in significant reductions in pore population.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Spatial Mode Correction of Single Photons Using Machine Learning

Abstract Spatial modes of light constitute valuable resources for a variety of quantum technologies ranging from quantum communication and quantum imaging to remote sensing. Nevertheless, their vulnerabilities to phase distortions, induced by random media, impose significant limitations on the realistic implementation of numerous quantum‐photonic technologies. Unfortunately, this problem is exacerbated at the single‐photon level. Over the last two decades, this challenging problem has been tackled through conventional schemes that utilize optical nonlinearities, quantum correlations, and adaptive optics. In this article, the self‐learning and self‐evolving features of artificial neural networks are exploited to correct the complex spatial profile of distorted Laguerre–Gaussian modes at the single‐photon level. Furthermore, the potential of this technique is used to improve the channel capacity of an optical communication protocol that relies on structured single photons. The results have important implications for real‐time turbulence correction of structured photons and single‐photon images.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Spatially Resolved Photoexcited Charge-Carrier Dynamics in Phase-Engineered Monolayer MoS 2

A fundamental understanding of the intrinsic optoelectronic properties of atomically thin transition metal dichalcogenides (TMDs) is crucial for its integration into high performance semiconductor devices. We investigate the transport properties of chemical vapor deposition (CVD) grown monolayer molybdenum disulfide (MoS 2 ) under photo-excitation using correlated scanning photocurrent microscopy and photoluminescence imaging. We examined the effect of local phase transformation underneath the metal electrodes on the generation of photocurrent across the channel length with diffraction-limited spatial resolution. While maximum photocurrent generation occurs at the Schottky contacts of semiconducting (2H-phase) MoS 2 , after the metallic phase transformation (1T-phase), the photocurrent peak is observed towards the center of the device channel, suggesting a strong reduction of native Schottky barriers. Analysis using the bias and position dependence of the photocurrent indicates that the Schottky barrier heights are few meV for 1T- and ~200 meV for 2H-contacted devices. We also demonstrate that a reduction of native Schottky barriers in a 1T device enhances the photo responsivity by more than one order of magnitude, a crucial parameter in achieving high performance optoelectronic devices. The obtained results pave a pathway for the fundamental understanding of intrinsic optoelectronic properties of atomically thin TMDs where Ohmic contacts are necessary for achieving high efficiency devices with low power consumption.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Relationship between surface μ‐roughness and interface slurry particle spatial distribution during glass polishing

Abstract During optical glass polishing, a number of interactions between the workpiece (i.e., glass), polishing slurry, and pad can influence the resulting workpiece roughness at different spatial scale lengths. In our previous studies, the particle size distribution of the slurry, the pad topography, and the amount of material removed by a single particle on the workpiece were shown to strongly correlate with roughness at AFM scale lengths (nm‐μm) and weakly at μ‐roughness scale lengths (μm‐mm). In this study, the polishing slurry pH and the generation of glass removal products are shown to influence the slurry particle spatial and height distribution at the polishing interface and the resulting μ‐roughness of the glass workpiece. A series of fused silica and phosphate glass samples were polished with various ceria and colloidal silica slurries over a range of slurry pH , and the resulting AFM roughness and μ‐roughness were measured. The AFM roughness was largely invariant with pH , suggesting that the removal function of a single particle is unchanged with pH . However, the μ‐roughness changed significantly, increasing linearly with pH for phosphate glass and having a maximum at an intermediate pH for fused silica. In addition, the spatial and height distribution of slurry particles on the pad (as measured by laser confocal microscopy) was determined to be distinctly different at low and high pH during phosphate glass polishing. Also, the zeta potential as a function of pH was measured for the workpiece, slurry, and pad with and without surrogate glass products (K 3 PO 4 for phosphate glass and Si( OH ) 4 for silica) to assess the role of interfacial charge during polishing. The addition of K 3 PO 4 significantly raised the zeta potential, whereas addition of Si( OH ) 4 had little effect on the zeta potential. An electrostatic DLVO three‐body force model, using the measured zeta potentials, was used to calculate the particle–particle, particle–workpiece, and particle–pad attractive and repulsive forces as a function of pH and the incorporation of glass products at the interface. The model predicted an increase in particle–pad attraction with an increase in pH and phosphate glass products consistent with the measured slurry distribution on the pads during phosphate glass polishing. Finally, a slurry “island” distribution gap ( IDG ) model has been formulated which utilizes the measured interface slurry distributions and a load balance to determine the interface gap, the contact area fraction, and the load on each slurry “island”. The IDG model was then used to simulate the workpiece surface topography and μ‐roughness; the results show an increase in roughness with pH similar to that observed experimentally.

Suratwala, Tayyab↗

DOE OSTI2012

Computerized scheme for evaluating mammographic phantom images

Purpose: The authors developed a computer algorithm to automatically evaluate images of the American College of Radiology (ACR) mammography accreditation phantom. Methods: The developed algorithm consist of the edge detection of wax insert, nonuniformity correction of background, and correction for magnification and also calculate the cross-correlation coefficient by image matching technique. The algorithm additionally evaluates target shape for fibers, target contrast for speck groups, and target circularity for masses. To obtain an ideal template image without noise and spatial resolution loss, the wax insert containing the embedded test pattern was extracted from the phantom and radiographed. Two template images and ten test phantom images were prepared for this study. The results of evaluation using the algorithm outputs were compared with the averaged results of observer studies by six skilled observers. Results: In comparing the results from the algorithm outputs with the results of observers, the authors found that the computer outputs were well correlated with the evaluations by observers, and they indicate the quality of the phantom image. The correlation coefficients between results of observer studies and two outputs of computer algorithm, i.e., the cross-correlation coefficient by template matching and indices of target shape for fibers, were 0.89 (95% confidence interval, 0.82-0.93; hereinafter the same) and 0.85 (0.76-0.91). The correlation coefficients between observer's results and two outputs: the cross-correlation coefficient and indices of target contrast for speck groups, were 0.83 (0.79-0.86) and 0.85 (0.81-0.88) and between observer's results and two outputs: the cross-correlation coefficient and indices of target circularity for masses, were 0.90 (0.84-0.94) and 0.87 (0.77-0.92). Conclusions: Image evaluation using the ACR phantom is indispensable in quality control of a mammography system. The proposed algorithm is useful for quality control and image evaluation of mammography units.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2015

GIANT MOLECULAR CLOUDS IN THE EARLY-TYPE GALAXY NGC 4526

We present a high spatial resolution (≈20 pc) of {sup 12}CO(2 −1) observations of the lenticular galaxy NGC 4526. We identify 103 resolved giant molecular clouds (GMCs) and measure their properties: size R, velocity dispersion σ{sub v}, and luminosity L. This is the first GMC catalog of an early-type galaxy. We find that the GMC population in NGC 4526 is gravitationally bound, with a virial parameter α ∼ 1. The mass distribution, dN/dM ∝ M{sup −2.39±0.03}, is steeper than that for GMCs in the inner Milky Way, but comparable to that found in some late-type galaxies. We find no size–line width correlation for the NGC 4526 clouds, in contradiction to the expectation from Larson’s relation. In general, the GMCs in NGC 4526 are more luminous, denser, and have a higher velocity dispersion than equal-size GMCs in the Milky Way and other galaxies in the Local Group. These may be due to higher interstellar radiation field than in the Milky Way disk and weaker external pressure than in the Galactic center. In addition, a kinematic measurement of cloud rotation shows that the rotation is driven by the galactic shear. For the vast majority of the clouds, the rotational energy is less than the turbulent and gravitational energy, while the four innermost clouds are unbound and will likely be torn apart by the strong shear at the galactic center. We combine our data with the archival data of other galaxies to show that the surface density Σ of GMCs is not approximately constant, as previously believed, but varies by ∼3 orders of magnitude. We also show that the size and velocity dispersion of the GMC population across galaxies are related to the surface density, as expected from the gravitational and pressure equilibrium, i.e., σ{sub v} R{sup −1/2} ∝ Σ{sup 1/2}.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Microscopic origins of hydrodynamic transport in the type-II Weyl semimetal WP 2

A microscopic understanding of hydrodynamic transport in Dirac and Weyl semimetals has remained elusive in theoretical descriptions and experimental measurements. We investigate the structure and microscopic properties of transport in WP 2 , a type-II Weyl semimetal exhibiting hydrodynamic transport. Here, we characterize the nature of the microscopic properties of WP 2 as a function of temperature through ab initio calculations of the relevant scattering processes, including electron-phonon and electron-electron lifetimes, and provide equivalent calculations for copper as a point of reference. Additionally, we present an approach to calculate phonon drag, a mechanism invoked in recent experiments, through predictions of a phonon-mediated electron-electron lifetime. We show that the resistivity is very well described by the electron-phonon interaction alone, indicating WP 2 exhibits conventional metallic electrical behavior in which strong electron-electron correlations do not play a significant role. After establishing the zone-averaged behavior of the calculated lifetimes, we further investigate specific features of the spatial distribution of the electron-phonon lifetime across the Fermi surfaces of WP 2 to study possible scattering channels involved in hydrodynamic transport and quantify the degree of lifetime anisotropy in electron and hole pockets. This description of microscopic dynamics in WP 2 prompts additional investigation of specific scattering channels and indicates the importance of phonon interactions in understanding connections between transport in hydrodynamic materials and strongly correlated systems including unconventional metals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2013

EARLY STAGES OF CLUSTER FORMATION: FRAGMENTATION OF MASSIVE DENSE CORES DOWN TO {approx}< 1000 AU

In order to study the fragmentation of massive dense cores, which constitute the cluster cradles, we observed the continuum at 1.3 mm and the CO (2-1) emission of four massive cores with the Plateau de Bure Interferometer in the most extended configuration. We detected dust condensations down to {approx}0.3 M {sub Sun} and separate millimeter sources down to 0.''4 or {approx}< 1000 AU, comparable to the sensitivities and separations reached in optical/infrared studies of clusters. The CO (2-1) high angular resolution images reveal high-velocity knots usually aligned with previously known outflow directions. This, in combination with additional cores from the literature observed at similar mass sensitivity and spatial resolution, allowed us to build a sample of 18 protoclusters with luminosities spanning three orders of magnitude. Among the 18 regions, {approx}30% show no signs of fragmentation, while 50% split up into {approx}> 4 millimeter sources. We compiled a list of properties for the 18 massive dense cores, such as bolometric luminosity, total mass, and mean density, and found no correlation of any of these parameters with the fragmentation level. In order to investigate the combined effects of the magnetic field, radiative feedback, and turbulence in the fragmentation process, we compared our observations to radiation magnetohydrodynamic simulations and found that the low-fragmented regions are reproduced well in the magnetized core case, while the highly fragmented regions are consistent with cores where turbulence dominates over the magnetic field. Overall, our study suggests that the fragmentation in massive dense cores could be determined by the initial magnetic field/turbulence balance in each particular core.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Trade-offs between microbiome diversity and productivity in a stratified microbial mat

Productivity is a major determinant of ecosystem diversity. Microbial ecosystems are the most diverse on the planet yet very few relationships between diversity and productivity have been reported as compared to macro-ecological studies. Here we evaluated the spatial relationships of productivity and microbiome diversity in a laboratory-cultivated photosynthetic mat. The goal was to determine how spatial diversification of microorganisms drives localized carbon and energy acquisition rates. We measured sub-millimeter depth profiles of net primary-productivity and gross oxygenic photosynthesis in the context of the localized microenvironment and community structure and observed negative correlations between species richness and productivity within the energy-replete, photic zone. Variations between localized community structures were associated with distinct taxa as well as environmental profiles describing a continuum of biological niches. Spatial regions corresponding to high primary productivity and photosynthesis rates had relatively low species richness and high evenness. Hence, this system exhibited negative species-productivity and species–energy relationships. These negative relationships may be indicative of photosynthetically-driven, light-controlled mat ecosystems that are able to be the most productive with a relatively smaller, even distributions of species that specialize within the highly-oxic, photic zones.

59 BASIC BIOLOGICAL SCIENCES↗