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At least 235 records · Page 13

Development of direct injection/ionization mass spectrometry methods for whole molecule characterization

Determining uranium isotopic and concentration information from environmental samples typically involves extensive chemical and physical processing prior to analysis. Harsh sample preparation results in the loss of the original uranium chemical speciation (i.e. what the uranium was bonded to/with when found in the environment) as well as the mixing of anthropogenic uranium with background material contained within the collection media (e.g. a swipe or soil). The objective of this work is to adapt a bioanalytical mass spectrometry technology called paper spray ionization mass spectrometry for the rapid analysis of intact uranium complexes. Soft ionization facilitates detection of whole molecule uranyl complexes including uranyl acetate, uranyl nitrate, and uranyl-tributylphosphate complex. Cotton swipe samples doped with a multi-element standard containing μg levels of U, Bi, Pb, Cd, Fe, and Zn were directly analyzed without purification, representing a major improvement over existing methods. Uranium quantitation is demonstrated using internal standards to obtain linear calibration curves. Limits of detection were determined to be approximately 100 ng for UO 2 and uranyl acetate through measurement of ppb level solutions. The development and qualification of PSI-MS techniques could lead to significant safeguards-related cost reduction and timeliness by facilitating the triage and queueing of swipe samples for more sensitive and time-consuming analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Nuclear forensics: Soil content

Nuclear Forensics is a growing field that is concerned with all stages of the process of creating and detonating a nuclear weapon. The main goal is to prevent nuclear attack by locating and securing nuclear material before it can be used in an aggressive manner. This stage of the process is mostly paperwork; laws, regulations, treaties, and declarations made by individual countries or by the UN Security Council. There is some preliminary leg work done in the form of field testing detection equipment and tracking down orphan materials; however, none of these have yielded any spectacular or useful results. In the event of a nuclear attack, the first step is to analyze the post detonation debris to aid in the identification of the responsible party. This aspect of the nuclear forensics process, while reactive in nature, is more scientific. A rock sample taken from the detonation site can be dissolved into liquid form and analyzed to determine its chemical composition. The chemical analysis of spent nuclear material can provide valuable information if properly processed and analyzed. In order to accurately evaluate the results, scientists require information on the natural occurring elements in the detonation zone. From this information, scientists can determine what percentage of the element originated in the bomb itself rather than the environment. To this end, element concentrations in soils from sixty-nine different cities are given, along with activity concentrations for uranium, thorium, potassium, and radium in various building materials. These data are used in the analysis program Python.

54 ENVIRONMENTAL SCIENCES↗

Machine learning approaches to streamline and enhance the analysis of multiscale imaging data for bioaerosol and soil particles

Bioaerosol and soil particles are ubiquitous in the environment. They are multicomponent and complex in nature displaying mixed inorganic and organic components. The way components are mixed in a bioaerosol sample is referred to as its mixing state. Soil particles are also a mixture of inorganic (mineral) and organic (soil organic matter) components. Bioaerosol particles contribute to a major fraction of coarse mode atmospheric particles, especially in the tropical areas, contributing up to 80 % of the particle mass concentration. The mixing state of particles is crucial to evaluate because it impacts several important environmental processes such as warm and cold cloud formation and radiation budget. Mixing states in aerosols are accompanied by chemical reactions across solid-liquid-gas interfaces. In this study, we utilized elemental compositions and microcopy images of thousands of atmospheric particles acquired by computer-controlled scanning electron microscope equipped with an energy-dispersive x-ray spectrometer to compute the mixing state of atmospheric particles. A 2D convolutional neural network (CNN), also known as convnet, was used to model the relationship between low resolution imaging data and higher resolution spectroscopy data, with the former as training input and the latter as target output. Two types of CNNs were implemented and tested; a basic CNN and an Inception-v3 network. For binary classification, the basic CNN achieved an accuracy of 84.29 % across all atom types, and the Inception-v3-like network achieved an accuracy 85.51 %. This study demonstrates the applicability of deep learning to handle large amounts of imaging/chemical spectroscopy data efficiently and evaluate particle mixing state from a range of environmental samples.

54 ENVIRONMENTAL SCIENCES↗

Baseline Risk Assessment Supporting Closure at Waste Management Area C at the Hanford Site Washington

The Office of River Protection under the U.S. Department of Energy is pursuing closure of the Single-Shell Tank (SST) Waste Management Area (WMA) C under the requirements of the Hanford Federal Facility Agreement and Consent Order (HFFACO). A baseline risk assessment (BRA) of current conditions is based on available characterization data and information collected at WMA C. The baseline risk assessment is being developed as a part of a Resource Conservation and Recovery Act (RCRA) Facility Investigation (RFI)/Corrective Measures Study (CMS) at WMA C that is mandatory under Comprehensive Environmental Response, Compensation, and Liability Act and RCRA corrective action. The RFI/CMS is needed to identify and evaluate the hazardous chemical and radiological contamination in the vadose zone from past releases of waste from WMA C. WMA C will be under Federal ownership and control for the foreseeable future, and managed as an industrial area with restricted access and various institutional controls. The exposure scenarios evaluated under these conditions include Model Toxics Control Act (MTCA) Method C, industrial worker, maintenance and surveillance worker, construction worker, and trespasser scenarios. The BRA evaluates several unrestricted land use scenarios (residential all-pathway, MTCA Method B, and Tribal) to provide additional information for risk management. Analytical results from 13 shallow zone (0 to 15 ft. below ground surface) sampling locations were collected to evaluate human health impacts at WMA C. In addition, soil analytical data were screened against background concentrations and ecological soil screening levels to determine if soil concentrations have the potential to adversely affect ecological receptors. Analytical data from 12 groundwater monitoring wells were evaluated between 2004 and 2013. A screening of groundwater monitoring data against background concentrations and Federal maximum concentration levels was used to determine vadose zone contamination impacts on groundwater. Waste Management Area C is the first of the Hanford tank farms to begin the closure planning process. The current baseline risk assessment will provide valuable information for making corrective actions and closure decisions for WMA C, and will also support the planning for future tank farm soil investigation and baseline risk assessments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The Impact of Below Detection Limit Samples in (NPP) Decommissioning Residual Risk Assessment - 17033

There are some technical problems with finalizing regulations and standards that address nuclear power plant (NPP) decommissioning site soil analyses for license termination. It is difficult to know how to best include detection limit observations from site soil analysis, because typical soil collection data is reported above, at, and below the detection limit. In addition, multiple detection limits are required to adequately estimate the soil radionuclide concentrations. In the literature, researchers analyzing environmental data refer to below the detection limit observations as 'left-censored data'. Left-censored data are less than the detection limit of the instrument(s) that made the measurements. Conventional approaches to managing left-censored data either ignore or simply replace the detection limits with zero, a fraction of the detection limit, or the detection limit itself. However, these approaches are statistically biased and limited in their usefulness. The Kaplan-Meier method, robust regression on order statistics method, and maximum likelihood estimation method are proposed to estimate the left-censored data more precisely. The proposed methods are applied to data from a Monazite powder manufacturing plant and the Colorado School of Mines Research Institute. Summary statistics such as the sample mean, sample standard deviation, sample percentiles are calculated from each data set and are used in risk and volume estimation calculations. Previous environmental analyses, such as the exposure assessment, recognize the uncertainty issue that is addressed in this research using the Latin hypercube sampling approach. Next, probabilistic distributions of the input parameters are developed for the uncertainty analyses. Finally, a framework methodology depicting the decision-making process in the proposed method is presented. The framework defines the critical steps, the amount of radioactivity, types of distributions, censoring percentage, sample size, and number of detection limits; it also allows the user to select the appropriate approach based on their site-specific data and analyses. The goal of this research is to develop a more precise risk assessment, estimate of the volume of soil removal, examine potential cost savings. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Democratization of fungal highway columns as a tool to investigate bacteria associated with soil fungi

ABSTRACT Bacteria–fungi interactions (BFIs) are essential in ecosystem functioning. These interactions are modulated not only by local nutritional conditions but also by the physicochemical constraints and 3D structure of the environmental niche. In soils, the unsaturated and complex nature of the substrate restricts the dispersal and activity of bacteria. Under unsaturated conditions, some bacteria engage with filamentous fungi in an interaction (fungal highways) in which they use fungal hyphae to disperse. Based on a previous experimental device to enrich pairs of organisms engaging in this interaction in soils, we present here the design and validation of a modified version of this sampling system constructed using additive printing. The 3D printed devices were tested using a novel application in which a target fungus, the common coprophilous fungus Coprinopsis cinerea, was used as bait to recruit and identify bacterial partners using its mycelium for dispersal. Bacteria of the genera Pseudomonas, Sphingobacterium and Stenotrophomonas were highly enriched in association with C. cinerea. Developing and producing these new easy-to-use tools to investigate how bacteria overcome dispersal limitations in cooperation with fungi is important to unravel the mechanisms by which BFIs affect processes at an ecosystem scale in soils and other unsaturated environments.

54 ENVIRONMENTAL SCIENCES↗

Phosphate addition increases tropical forest soil respiration primarily by deconstraining microbial population growth

Tropical ecosystems are an important sink for atmospheric CO 2 ; however, plant growth is restricted by phosphorus (P) availability. Although soil microbiota facilitate organic P turnover and inorganic P mobilization, their role in carbon-phosphorus coupled processes remains poorly understood. To advance this topic, soils collected from four sites representing highly weathered tropical soils in the El Yunque National Forest, Puerto Rico were incubated with exogenous PO 4 3- under controlled laboratory conditions. P amendment increased CO 2 respiration by 14–23% relative to control incubations for soils sampled from all but the site with the greatest total and bioavailable soil P. Metatranscriptomics revealed an increase in the relative transcription of genes involved in cell growth and uptake of other nutrients in response to P amendment. A new methodology to normalize gene expression by population-level relative (DNA) abundance revealed that the pattern of increased transcription of cell growth and division genes with P amendment was community-wide. Soil communities responsive to P amendment possessed a greater relative abundance of α-glucosyl polysaccharide biosynthesis genes, suggestive of enhanced C storage under P-limiting conditions. Phosphorylase genes governing the degradation of α-glucosyl polysaccharides were also more abundant and increased in relative transcription with P amendment, indicating a shift from energy storage towards growth. Inversely, microbial communities in soils nonresponsive to P amendment were found to have metabolisms tuned for the phosphorolysis of labile plant-derived substrates, such as β-glucosyl polysaccharides. Accordingly, our results provided quantitative estimates of increased soil respiration upon alleviation of P constraints and elucidated several underlying ecological and molecular mechanisms involved in this response.

59 BASIC BIOLOGICAL SCIENCES↗

From individual leaves to forest stands: importance of niche, distance decay, and stochasticity vary by ecosystem type and functional group for fungal community composition

Abstract Community assembly is influenced by environmental niche processes as well as stochastic processes that can be spatially dependent (e.g. dispersal limitation) or independent (e.g. priority effects). Here, we sampled senesced tree leaves as unit habitats to investigate fungal community assembly at two spatial scales: (i) small neighborhoods of overlapping leaves from differing tree species and (ii) forest stands of differing ecosystem types. Among forest stands, ecosystem type explained the most variation in community composition. Among adjacent leaves within stands, variability in fungal composition was surprisingly high. Leaf type was more important in stands with high soil fertility and dominated by differing tree mycorrhizal types (sugar maple vs. basswood or red oak), whereas distance decay was more important in oak-dominated forest stands with low soil fertility. Abundance of functional groups was explained by environmental factors, but predictors of taxonomic composition within differing functional groups were highly variable. These results suggest that fungal community assembly processes are clearest for functional group abundances and large spatial scales. Understanding fungal community assembly at smaller spatial scales will benefit from further study focusing on differences in drivers for different ecosystems and functional groups, as well as the importance of spatially independent factors such as priority effects.

59 BASIC BIOLOGICAL SCIENCES↗

Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET

Abstract. The ability to monitor, understand, and predict the dynamics of the terrestrial carbon cycle requires the capacity to robustly and coherently synthesize multiple streams of information that each provide partial information about different pools and fluxes. In this study, we introduce a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon “reanalysis” product that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. We first calibrated this system against plant trait and flux tower net ecosystem exchange (NEE) using a novel emulated hierarchical Bayesian approach. Next, we extended the Tobit–Wishart ensemble filter (TWEnF) state data assimilation (SDA) framework, a generalization of the common ensemble Kalman filter which accounts for censored data and provides a fully Bayesian estimate of model process error, to a regional-scale system with a calibrated localization. Combined with additional workflows for propagating parameter, initial condition, and driver uncertainty, this represents the most complete and robust uncertainty accounting available for terrestrial carbon models. Our initial reanalysis was run on an irregular grid of ∼ 500 points selected using a stratified sampling method to efficiently capture environmental heterogeneity. Remotely sensed observations of aboveground biomass (Landsat LandTrendr) and leaf area index (LAI) (MODIS MOD15) were sequentially assimilated into the SIPNET model. Reanalysis soil carbon, which was indirectly constrained based on modeled covariances, showed general agreement with SoilGrids, an independent soil carbon data product. Reanalysis NEE, which was constrained based on posterior ensemble weights, also showed good agreement with eddy flux tower NEE and reduced root mean square error (RMSE) compared to the calibrated forecast. Ultimately, PEcAn's new open-source regional data assimilation framework provides a scalable workflow for harmonizing multiple data constraints and providing a uniform synthetic platform for carbon monitoring, reporting, and verification (MRV) as well as accelerating terrestrial carbon cycle research.

54 ENVIRONMENTAL SCIENCES↗

Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe’s terrestrial ecosystems: A review

Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO 2 , CH 4 , N 2 O, H 2 O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. Finally, the use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.

54 ENVIRONMENTAL SCIENCES↗

Soil microbiome predictability increases with spatial and taxonomic scale

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remark- able scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. Here, by focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent

Biogeography↗

Data from Raczka et al., Interactions between microbial diversity and substrate chemistry determine the fate of carbon in soil, from Elizabeth Woods in Morgantown, West Virginia, USA

File types include: Soil respiration as 13C cumulative respiration from soil incubation experiment, qSIP (quantitative stable isotope probing) data that is "18S apes wide" which is the fungal atom percent excess or how much the fungi took up of the labeled litter and "16S apes wide" which is the bacterial atom percent excess or how much the bacteria took up of the labeled litter, metabolomic data from the incubated soil samples called "Metab Soil Unique Filtered", which is the metabolomic data that had an initial filter from the raw data, and lipidomic data from the incubated soil samples called "All lipids soil". These files were used according to methods in Raczka et al. 2021 Scientific Reports. Headers show soil type (Oak, Poplar) and litter type (also called substrate here, which is labeled as no litter (control), poplar, and oak). This research was done to understand interactions between ecosystem-level processes and microbial diversity that impacts the composition of decomposition products that can form stable soil organic matter.

54 ENVIRONMENTAL SCIENCES↗

Data from: Temporal dynamics of free‐living nitrogen fixation in the switchgrass rhizosphere

Here we present data associated with the manuscript, Temporal dyanmics of free-living nitrogen fixation in the switchgrass rhizosphere. Free-living nitrogen fixation (FLNF) represents an important terrestrial N source and is gaining interest for its potential to contribute plant available N to bioenergy cropping systems. Switchgrass, a cellulosic bioenergy crop, may be reliant on FLNF when particularly when grown on low N marginal lands. These potential contributions of FLNF to switchgrass and the controls on this process are not well understood. We evaluated drivers of FLNF rates and N-fixing microbial community composition in field-grown switchgrass systems over two years with high temporal sampling. We found climate variables to be strong drivers of FLNF in switchgrass systems, compared to other environmental and biological factors including soil nutrients and N-fixing microbial community composition. Increased soil moisture availability tended to promote FLNF, but extreme rainfall events appeared to be detrimental. These climate-related responses suggest FLNF-derived N contributions may be reduced under projected climate shifts. We also found a significant, but weak correlation between N-fixing microbial community composition and FLNF rates including an observed shift in community composition between 2017 and 2018 and a similarly significant difference in FLNF rates between years. Lastly, we found that seasonal FLNF N contributions, based on measurement with high temporal resolution, may meet up to 80% of switchgrass N demands.

09 BIOMASS FUELS↗

Optimizing Cryo-Focused Pyrolysis GC/MS for Tracing Soil Organic Matter Across Diverse Ecosystems

The cycling of organic matter in terrestrial soils and sediments is central to a range of biogeochemical processes that regulate nutrient cycling, crop productivity, trace gas emissions, and contaminant transport. Pyrolysis-gas chromatography/mass spectrometry (py-GC/MS) is a powerful tool for characterizing bulk soil organic matter (SOM) at the molecular level. In this study, we used a cryo-focused py-GC/MS system to analyze soil samples from seven diverse ecosystems: vernal pool, prairie pothole, temperate forest, tropical forest, tundra, wildfire-affected boreal forest, and grassland. We addressed a key bottleneck in molecular-level SOM characterization by developing an automated data analysis pipeline to optimize py-GC/MS and complementary evolved gas analysis/mass spectrometry (EGA/MS) methods, incorporating advanced tools for peak deconvolution, developing a custom compound class library, and implementing fragmentation spectrum-based molecular networking for the first time. This improved workflow was applied to soil samples from all seven ecosystems, including multiple depths and density fractions. Our findings demonstrate that ecosystem type plays a dominant role in shaping compositional differences in SOM. We also identified trends in the source of SOM compounds (e.g., microbial vs plantderived) across soil depth and density fractions, which are critical for understanding persistence and turnover of SOM. Our molecular networking analysis indicated that although many compounds are widespread across ecosystems, others are restricted to specific environments, such as wetlands. This underscores the utility of molecular-level data in elucidating the complexity of SOM composition and the environmental drivers that shape it. Such molecular-level insights can deepen our knowledge of biogeochemical SOM cycles.

54 ENVIRONMENTAL SCIENCES↗

Remediation of 130 mSv/hr. Soil Contamination Under a Hot Cell - 17301

Department of Energy (DOE) contractor CH2M HILL Plateau Remediation Company (CH2M) is currently engineering a system to safely remove and dispose of highly contaminated soil underneath Building 324 located adjacent to the Columbia River on the Hanford Site in Washington State. Cleaning up the waste site will allow for the eventual demolition of the building, which is a top priority for DOE and CH2M due to the proximity of the Columbia River and City of Richland. Building 324 at Hanford was originally constructed in 1966 and was operated for a number of years serving various missions. One of the missions involved development of treatment processes for liquid high activity waste. As of result of one particular mission, liquid high activity waste was spilled in one of the building's hot cells (known as 'B' Cell) and the liquid leaked from a breach in a sump and through construction joints in the hot cell floor and into the soil. Sampling efforts using borehole technology revealed significant under-building contamination with dose rates measuring has high as 130 mSv/hr (13,000 R/hr.). The Hanford Federal Facility Agreement and Consent Order (Tri-Party Agreement) between the Washington State, Department of Ecology (Ecology), the U.S. Environmental Protection Agency and the DOE has established a 2021 milestone for demolition and removal of the Building 324. Before building demolition can be undertaken, the highly contaminated soil must be removed from beneath the hot cell while the hot cell structure remains in place to provide shielding and containment during the soil remediation. CH2M will fabricate and install remotely operated equipment that will remove debris and grout in the cell, the floor of the hot cell, and the contaminated soil beneath the hot cell and package that soil for disposal. To ensure that the structure remains intact and does not shift during soil removal, support for the building structure must also be constructed as a prerequisite for the planned work. CH2M will use a full-scale mock-up of the Building 324 B Cell and airlock area to assist in the testing of the remotely operated equipment and the training of the soil removal team in a contamination-free environment to ensure efficient and safe performance of the challenging work of the project. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Niche Partitioning of Microbial Communities at an Ancient Vitrified Hillfort: Implications for Vitrified Radioactive Waste Disposal

A pre-Viking era vitrified hillfort, Broborg, provides a habitat analogue for disposed radioactive waste glass and shows strong niche partitioning among the organisms involved in glass alteration. Microbes cannot be eliminated from radioactive waste disposal facilities and the consequences of bio-colonization must be understood. We use Broborg as a model system to inform what microbial processes might influence long-term radioactive waste glass durability by examining anthropogenic glass that has been subjected to bio-colonization for over 1,500 years. Scanning electron microscopy (SEM) images reveal the surficial biofilm structure, and chemical/mineralogy analysis in combination with deoxyribonucleic acid (DNA) sequencing of samples from the vitrified substrate, the adjacent soil, and the general topsoil provide insight into niche partitioning. The ancient glass niche supports a unique microbial community of bacteria, fungi, and protists that manifests the species response to local geochemical and mineralogical conditions. Communities from the geochemical niche associated with the glass are distinct and less diverse than soil communities. The microbiome of the glass and adjacent soil are dominated by lichens, lichen-associated microorganisms, and other epilithic, endolithic, and epigeic organisms. Pseudomonads dominate the prokaryotic communities on the vitrified material, but not the adjacent soil. In contrast, the general topsoil communities are enriched in plant rhizosphere organisms. Taxa associated with vitrification have bio-corrosive properties that could be detrimental to glass durability, including silicate mineral dissolution, extraction of essential elements, secretion of geochemically reactive organic acids, and dissolution induced by improved water retention. However, these stable long-term biofilms also possess a homeostatic function that could limit glass alteration. Overall, this study demonstrates the potential impacts that microbial colonization and niche partitioning can have on glass alteration and subsequent release of radionuclides from a disposal facility for vitrified radioactive waste.

59 BASIC BIOLOGICAL SCIENCES↗

Calibration of 2-D soil zymography for correct analysis of enzyme distribution

Soil zymography is a new technique developed to visualize two-dimensional distributions of enzyme activities. The method is composed of incubating a membrane saturated with an enzyme-specific fluorogenic substrate on a surface of the soil sample, followed by recording the membrane image generated by a fluorescent product (e.g. MUF: methylumbelliferone) in ultraviolet light. Despite its relative ease of use, performing zymography involves multiple user-made decisions that might affect the accuracy of enzyme activity estimates. Thus, unification of the zymography methodology is required for correct estimations and comparisons of various studies. We investigated the following methodological aspects of the implementation of zymography: (a) camera settings and image processing, (b) effects of evaporation and (c) calibration procedures. Camera settings (shutter speeds or exposure time) affected the intensity of background fluorescence and signal-to-noise ratios (SNR). However, because their combined effects varied depending on MUF concentrations, light and camera setting need to be optimized for the expected range of MUF concentrations prior to zymography. Evaporation of MUF solution from the membrane had no effect on fluorescence. Relations between MUF concentration and intensity of fluorescence during calibrations demonstrated a saturated pattern and were strongly affected by image noise outside the optimal range (e.g. 8–14 μm MUF pixel -1 ). We developed a new calibration approach that is based on a piecewise linear regression. The new approach accounted for specific ranges of MUF concentration and uses nonuniformly saturated membranes, reflecting the real distribution of enzyme activities in soil. The new calibration algorithm eliminated biases of the standard calibration and resulted in greater accuracy in predicting MUF concentrations.

59 BASIC BIOLOGICAL SCIENCES↗

Specialized Plant Growth Chamber Designs to Study Complex Rhizosphere Interactions

The rhizosphere is a dynamic ecosystem shaped by complex interactions between plant roots, soil, microbial communities and other micro- and macro-fauna. Although studied for decades, critical gaps exist in the study of plant roots, the rhizosphere microbiome and the soil system surrounding roots, partly due to the challenges associated with measuring and parsing these spatiotemporal interactions in complex heterogeneous systems such as soil. To overcome the challenges associated with in situ study of rhizosphere interactions, specialized plant growth chamber systems have been developed that mimic the natural growth environment. This review discusses the currently available lab-based systems ranging from widely known rhizotrons to other emerging devices designed to allow continuous monitoring and non-destructive sampling of the rhizosphere ecosystems in real-time throughout the developmental stages of a plant. We categorize them based on the major rhizosphere processes it addresses and identify their unique challenges as well as advantages. We find that while some design elements are shared among different systems (e.g., size exclusion membranes), most of the systems are bespoke and speaks to the intricacies and specialization involved in unraveling the details of rhizosphere processes. We also discuss what we describe as the next generation of growth chamber employing the latest technology as well as the current barriers they face. We conclude with a perspective on the current knowledge gaps in the rhizosphere which can be filled by innovative chamber designs.

59 BASIC BIOLOGICAL SCIENCES↗