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At least 343 records · Page 19

Effects of Catalytic Action and Ligand Binding on Conformational Ensembles of Adenylate Kinase

Crystal structures of adenylate kinase (AdK) from Escherichia coli capture two states: an “open” conformation (apo) obtained in the absence of ligands and a “closed” conformation in which ligands are bound. Other AdK crystal structures suggest intermediate conformations that may lie on the transition pathway between these two states. To characterize the transition from open to closed states in solution, X-ray solution scattering data were collected from AdK in the apo form and with progressively increasing concentrations of five different ligands. Scattering data from apo AdK are consistent with scattering predicted from the crystal structure of AdK in the open conformation. In contrast, data from AdK samples saturated with Ap5A do not agree with that calculated from AdK in the closed conformation. Using cluster analysis of available structures, we selected representative structures in five conformational states: open, partially open, intermediate, partially closed, and closed. We used these structures to estimate the relative abundances of these states for each experimental condition. X-ray solution scattering data obtained from AdK with AMP are dominated by scattering from AdK in the open conformation. For AdK in the presence of high concentrations of ATP and ADP, the conformational ensemble shifts to a mixture of partially open and closed states. Even when AdK is saturated with Ap5A, a significant proportion of AdK remains in a partially open conformation. Here, these results are consistent with an induced-fit model in which the transition of AdK from an open state to a closed state is initiated by ATP binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Anomalously high elastic modulus of a poly(ethylene oxide)-based composite electrolyte

The practical use of lithium metal anodes in solid-state batteries requires a polymer membrane with high lithium-ion conductivity, thermal/electrochemical stability, and mechanical strength. The primary challenge is to effectively decouple the ionic conductivity and mechanical strength of the polymer electrolytes. We report a remarkably facile single step synthetic strategy based on in-situ crosslinking of poly(ethylene oxide) (xPEO) in the presence of a woven glass fiber (GF). Such a simple method yields composite polymer electrolytes (CPE) of anomalously high elastic modulus up to 2.5 GPa over a broad temperature range (20 °C – 245 °C) that has never been previously documented. An unsupervised machine learning algorithm, K-mean clustering analysis, was implemented on the hyperspectral Raman mapping at the xPEO/GF interface. Using such a unique means, we show for the first time that the promoted mechanical strength originates from xPEO and GF interactions through dynamic hydrogen and ionic bonding. High ionic conductivity is achieved by the addition plasticizer (e.g. tetraglyme), where trifluoromethanesulfonate anions are tethered to the xPEO matrix and Li + cations are favorably transported through coordination with the plasticizer. Further, stringent galvanostatic cycling tests indicates the CPE can be stably cycled for >3000 h in a Li-metal symmetric cell at a moderate temperature (nearly 1500 Coulombs/cm 2 Li equivalents), outperforming most of the PEO-based electrolytes. The GF reinforced CPE reported here has multifunctional uses, such as solid electrolytes for all solid-state batteries and membranes for redox-flow batteries. Although the focus of this study is on lithium-based batteries, the results are equally promising for other alkali metal based batteries such as sodium and potassium.

25 ENERGY STORAGE↗

Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem

Coastal terrestrial-aquatic interfaces (TAIs) are crucial contributors to global biogeochemical cycles and carbon exchange. A systematic evaluation of the interaction between coastal catchment properties and carbon dioxide (CO2) emission by soil respiration is significant for assessing carbon dynamics and predicting the future trajectory of atmospheric CO2 concentrations in coastal TAIs. The soil CO2 efflux in these transition zones is however poorly understood due to the high spatiotemporal dynamics of TAIs, as various sub-ecosystems in this region are compressed and expanded by complex influences of tides, changes in river levels, climate, and land use. We focus on the Chesapeake Bay region to (i) investigate the spatial heterogeneity of the coastal ecosystem and identify spatial zones with similar environmental characteristics based on the spatial data layers, including vegetation index (kNDVI), climate, landcover, diversity, topography, soil property, and relative tidal elevation; (ii) understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. Specifically, we employed hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, followed by the determination of main driving factors using Random Forest regression and SHapley Additive exPlanations. Maximum and minimum temperature are the main drivers common to all sub-ecosystems, while each region also has additional unique major drivers that differentiate them from one another. Precipitation exerts an influence on vegetated lands, while soil pH value holds importance specifically in forested lands. In croplands characterized by high clay content and low sand content, the significant role is attributed to bulk density. Wetlands demonstrate the importance of both elevation and sand content, with clay content being more relevant in non-inundated wetlands than in inundated wetlands. The topographic wetness index significantly contributes to the mixed vegetation areas, including shrub, grass, pasture, and forest. Additionally, our research reveals that dense vegetation land covers and urban/developed areas exhibit distinct soil property drivers. Overall, there is no one-size-fits-all approach to modeling carbon fluxes in coastal TAIs, and our study highlights the importance of further research and monitoring practices to improve our understanding of carbon dynamics and promote the sustainable management of coastal TAIs.

54 ENVIRONMENTAL SCIENCES↗

Tracking Elevated Pollution Layers with a Newly Developed Hyperspectral Sun/Sky Spectrometer (4STAR): Results from the TCAP 2012 and 2013 Campaigns

Total columnar amounts of water vapor, nitrogen dioxide (NO2) and ozone (O3) are derived from a newly developed, hyperspectral airborne sun-sky spectrometer (4STAR) for the first time during the two intensive phases of the Two Column Aerosol Project (TCAP) in summer 2012 and winter 2013 aboard the DOE G-1 aircraft. We compare results with coincident measurements. We find 0.045 g/cm2 (4.2%) negative bias and 0.28 g/cm2 (26.3%) root-mean-square (RMS) difference in water vapor layer comparison with in-situ hygrometer, and an overall RMS difference of 1.28 g/m3 (38%) water vapor amount in profile by profile comparisons, with differences distributed evenly around zero in most cases. The RMS differences for O3 values average to 3%, with a 1% negative bias for 4STAR compared with the spaceborne Ozone Measuring Instrument (OMI) along the aircraft flight-track for 14 flights during both TCAP phases. Ground-based comparisons with the Pandora spectrometer system at the Goddard Space Flight Center (GSFC), Greenbelt, Maryland showed excellent agreement between the instruments for both O3 and NO2, further emphasizing 4STAR’s new capabilities. During the summer phase, we have succeeded in identifying variations in elevated pollution layers corresponding to urban pollution outflow and transported biomass burning. This was done using clustering analysis of the retrieved products (e.g. Ångstrom exponent, NO2 and columnar water vapor), and was confirmed by aerosol type identification by HSRL2 aboard the NASA B-200 aircraft. These newly demonstrated 4STAR capabilities are expected to be instrumental in improving our understanding of atmospheric composition variability and aerosol-trace-gas interactions; they open new horizons and opportunities in airborne sunphotometry.

4STAR↗

Daily-scale planetary wave patterns and the modulation of cold season weather in the northern extratropics

Here, tropospheric planetary waves, often linked to asymmetries in lower boundary forcing,significantly modulate atmospheric blocking and storm track structures that are, in turn, linked to extremesurface weather events. Day-to-day variability in the planetary scale circulation, taken as wave numbers 1 to 5in the daily 500 hPa geopotential heights, and the associated impact on storm tracks and regional weather arestudied for the period 1950–2005. Six boreal cold-season distinct planetary wave patterns are identified viahierarchical cluster analysis. The first, second, and sixth patterns feature a prominent zonal wave number 1structure, while the fourth and fifth patterns resemble the negative and positive phases of northern annularmode, respectively. The second pattern represents an amplification of the climatological mean wavestructure, while the third pattern resembles the zonal wave number 3 pattern. A multitaper spectral analysisof the daily projection indices indicates that the planetary wave patterns are primarily intraseasonal innature. The first (sixth) pattern combines the positive (negative) phase of the Pacific-North Americanteleconnection pattern and negative (positive) phase of the North Atlantic Oscillation, inducing poleward(equatorward) shifts in the Pacific storm track and a weakened (strengthened) Atlantic storm track. Incontrast, the fourth (fifth) pattern results in a simultaneous equatorward (poleward) displacement of bothstorm tracks. Extreme cold waves over the continental United States (U.S.) are favored during occurrences ofthe fourth and sixth patterns. During episodes of the first pattern, increased rainfall prevails over much ofthe U.S., while precipitation anomalies induced by the other patterns are more regional in nature.

54 ENVIRONMENTAL SCIENCES↗

Western North Pacific Tropical Cyclone Model Tracks in Present and Future Climates

Western North Pacific tropical cyclone (TC) model tracks are analyzed in two large multimodel ensembles, spanning a large variety of models and multiple future climate scenarios. Two methodologies are used to synthesize the properties of TC tracks in this large data set: cluster analysis and mass moment ellipses. First, the models' TC tracks are compared to observed TC tracks' characteristics, and a subset of the models is chosen for analysis, based on the tracks' similarity to observations and sample size. Potential changes in track types in a warming climate are identified by comparing the kernel smoothed probability distributions of various track variables in historical and future scenarios using a Kolmogorov-Smirnov significance test. Two track changes are identified. The first is a statistically significant increase in the north-south expansion, which can also be viewed as a poleward shift, as TC tracks are prevented from expanding equatorward due to the weak Coriolis force near the equator. The second change is an eastward shift in the storm tracks that occur near the central Pacific in one of the multimodel ensembles, indicating a possible increase in the occurrence of storms near Hawaii in a warming climate. The dependence of the results on which model and future scenario are considered emphasizes the necessity of including multiple models and scenarios when considering future changes in TC characteristics.

54 ENVIRONMENTAL SCIENCES↗

Ecohydrology of wetland plant communities along an estuarine to tidal river gradient

Abiotic filters that interact with wetland plant communities along tidal–fluvial gradients are highly dynamic, and understanding their quantitative thresholds and relationships to interspecific competition is important during an era of sea-level rise and watershed hydrologic change. Yet, landscape-scale studies of major coastal rivers from the river mouth to the head of tide, such as this study, remain rare. Here, we develop a new predictive framework for estuarine–tidal river research and management using a river-specific low-water datum and the wetland inundation indicator SEVg, the growing-season sum exceedance value of hourly surface-water depth. The distribution and variability of the wetland species pool (n = 203) on the 234 river kilometer (rkm) lower Columbia River and estuary floodplain are described for the first time. 4,940 quadrats at 50 marshes were surveyed (2005–2016). Throughout the estuarine–tidal river system, SEVg was well suited to describe the wetland inundation regime and its variability based on the combination of longitudinal river position and elevation. SEVg increased significantly landward. Two primary wetland inundation regimes were identified: the seaward-tidal, usually greatest during the winter months, and landward-fluvial, greatest during the growing season. Nearest the ocean, salinity is the abiotic factor limiting species richness and non-native species. Farther upriver, the daily, seasonal, and interannual variability of the wetting and drying cycle encourage disturbance-tolerant species and non-natives and limit the number of hydrophytes and total vegetative cover. Hence, the average between-year similarity of site-scale areal cover significantly decreased landward. Hierarchical cluster analysis indicated five vegetative groups and five ecohydrologic zones between rkm 0 and 234 were discriminated with 76 significant species–zone associations. All zones had unique indicator species. Species with high indicator values were Carex lyngbyei throughout the estuarine zones, and Eleocharis palustris, Sagittaria latifolia, and the invasive non-native Phalaris arundinacea in the upper estuarine and lower, middle, and upper tidal river zones (IV > 0.90). Competition from C. lyngbyei nearest the ocean and P. arundinacea in the tidal river was associated with reduced species richness when total cover was >65%. This framework of filters informs the design and prediction of future wetland plant communities on coastal river floodplains.

54 ENVIRONMENTAL SCIENCES↗

Reconstruction of Central European daily weather types back to 1763

Weather type classifications (WTCs) are a simple tool to analyse variations in weather patterns. Long series of WTCs could be used to address decadal changes in weather as a basis for studying changes in variability or extremes or for addressing contributions of sea-surface temperature or external forcings using climate models. However, there is no long series of daily objective weather types (WTs). A new method (Shortest Mahalanobis Distance, SMD) using daily European weather data is developed to reconstruct WTCs back in time. Here the SMD method is applied on the Cluster Analysis of Principal Components (CAP9) classification used by MeteoSwiss. The CAP9 daily WT time series (computed with ERA-40) is used as reference over the 1958–1998 period. Daily data (temperature, mean sea level pressure and pressure tendency) from 13 European stations covering the period 1763–2009 are used for the reconstruction. The reference CAP9 is reduced from nine to seven types so the new daily WTC is called CAP7. As an assessment, CAP7 is compared to the original classification CAP9 and to the same WTs computed with the Twentieth Century Reanalysis (20CR and 20CRv2c). Over the reference period up to 90% of all the daily WTs can be correctly reproduced in the new WTC compared to the original series, with higher reliability in winter than in summer. In addition, the reliability of the classification is increasing from 1763 onward. The annual occurrence of each type reveals some trends, mostly a decrease in the number of cyclonic days and an increase of cyclonic days.

54 ENVIRONMENTAL SCIENCES↗

Computing and visualizing time-varying merge trees for high-dimensional data

We introduce a new method that identifies and tracks features in arbitrary dimensions using the merge tree -- a structure for identifying topological features based on thresholding in scalar fields. This method analyzes the evolution of features of the function by tracking changes in the merge tree and relates features by matching subtrees between consecutive time steps. Using the time-varying merge tree, we present a structural visualization of the changing function that illustrates both features and their temporal evolution. We demonstrate the utility of our approach by applying it to temporal cluster analysis of high-dimensional point clouds.

97 MATHEMATICS AND COMPUTING↗

Pollution and Risk of PAHs in Surface Sediments from the Tributaries and Their Relation to Anthropogenic Activities, in the Main Urban Districts of Chongqing City, Southwest China

Concentrations, sources and risk of 16 priority polycyclic aromatic hydrocarbons (PAHs) were investigated in surface sediments from 19 representative tributaries in a regional scale of Chongqing City. The total concentration of 16 PAHs (ΣPAHs) ranged from 221 to 3205 ng g{sup −1} with a mean of 1055 ng g{sup −1}. Most tributaries of the Jialing River exhibited significantly higher ΣPAHs concentrations (mean 1864 ng g{sup −1}) compared to those flowing into the Yangtze River (mean 787 ng g{sup −1}). Isomeric ratio and hierarchical clustering analysis showed combustion may impact sedimentary PAHs at most center sites of the City, while PAHs at most sites were mixed of petrogenic and pyrogenic sources. Toxicity equivalency concentration for carcinogenic PAH were 2–4 times more than the Dutch limit. More comprehensive assessment of safety is suggested to reduce environmental risk of PAHs in sediments.

54 ENVIRONMENTAL SCIENCES↗

Temporal and Spatial Evolution of Non-Elastic Strain Accumulation in Stanstead Granite During Brittle Creep

Understanding the long-term behavior of brittle rocks requires fundamental consideration of time-dependent strain evolution and brittle creep processes. Previous studies have evaluated sub-critical crack growth during time-dependent deformation and damage evolution in brittle rocks; however, there is an incomplete knowledge of how damage evolves spatially and temporally within the body of intact rocks, where distributed regions of damage interact and coalesce during creep. This paper presents laboratory research focusing on evaluating brittle creep damage processes in Stanstead granite (SG) using 2-dimensional digital image correlation (2D-DIC). In the laboratory, the prismatic SG specimens were loaded beyond an estimated Crack Damage stress threshold (CD) level and then maintained a constant stress to initiate the creep process. DIC was used to characterize full-field spatiotemporal strain evolution, which was then interpreted in the context of local regions of “damage”, determined according to a strain-based criterion. Here, a method was proposed for identifying “existing” and “new” damage regions over specified intervals during the test, followed by spatial clustering of these regions to assess their spatiotemporal evolution. The clustering analysis results demonstrated the extension of existing damage regions was the main damage process during brittle creep, which is consistent with existing models of sub-critical crack growth. In addition, temporal analysis of tensile and shear strains on a point-by-point basis revealed both new damage formation and the strain concentration within existing damaged regions significantly contribute to overall specimen strain during primary creep. In contrast, during secondary creep, increases in specimen deformation are influenced by the accumulation of strains within already damaged regions.

58 GEOSCIENCES↗

Modeling regional precipitation over the Indus River basin of Pakistan using statistical downscaling

Complex processes govern spatiotemporal distribution of precipitation within the high-mountainous headwater regions (commonly known as the upper Indus basin (UIB)), of the Indus River basin of Pakistan. Reliable precipitation simulations particularly over the UIB present a major scientific challenge due to regional complexity and inadequate observational coverage. Here, we present a statistical downscaling approach to model observed precipitation of the entire Indus basin, with a focus on UIB within available data constraints. Taking advantage of recent high altitude (HA) observatories, we perform precipitation regionalization using K-means cluster analysis to demonstrate effectiveness of low-altitude stations to provide useful precipitation inferences over more uncertain and hydrologically important HA of the UIB. We further employ generalized linear models (GLM) with gamma and Tweedie distributions to identify major dynamic and thermodynamic drivers from a reanalysis dataset within a robust cross-validation framework that explain observed spatiotemporal precipitation patterns across the Indus basin. Final statistical models demonstrate higher predictability to resolve precipitation variability over wetter southern Himalayans and different lower Indus regions, by mainly using different dynamic predictors. The modeling framework also shows an adequate performance over more complex and uncertain trans-Himalayans and the northwestern regions of the UIB, particularly during the seasons dominated by the westerly circulations. However, the cryosphere-dominated trans-Himalayan regions, which largely govern the basin hydrology, require relatively complex models that contain dynamic and thermodynamic circulations. Furthermore, we also analyzed relevant atmospheric circulations during precipitation anomalies over the UIB, to evaluate physical consistency of the statistical models, as an additional measure of reliability. Overall, our results suggest that such circulation-based statistical downscaling has the potential to improve our understanding towards distinct features of the regional-scale precipitation across the upper and lower Indus basin. Additionally, such understanding should help to assess the response of this complex, data-scarce, and climate-sensitive river basin amid future climatic changes, to serve communal and scientific interests.

54 ENVIRONMENTAL SCIENCES↗

Zinc concentration affects the functional groups of microbial communities in sugarcane-cultivated soil

The addition of zinc (Zn) to the soil has significant gains in sugarcane productivity. The understanding of the consequences of zinc application requires insight into ecological aspects of changes in soil microbial communities. Here, we evaluated the effects of zinc application on richness, diversity, evenness and structure of microbial functional genes in sugarcane-cultivated soil, and response thresholds of abundance for groups of microbial functional genes on different zinc concentrations added to the soil (0, 5, 10 and 20 kg Zn ha -1 ) in two sugarcane fields in the Northeastern São Paulo state, Brazil. Using a high-density functional gene array termed GeoChip 5.0, which contains 101,796 distinct probes belonging to gene categories involved in zinc transport, secondary metabolism, stress, virulence and nutrient cycling, differences were observed in the functional gene structure of microbial communities and abundance of specific gene families with a threshold between 5 and 10 kg Zn ha -1 . However, the richness, diversity and evenness of functional genes did not differ across the zinc gradients in soil. Cluster analysis based on microbial functional subcategories revealed variation in abundances across the gradient of zinc concentrations in soil mainly for virulence, stress, secondary metabolism, and carbon- and phosphorus-cycling-related gene families. A threshold in abundance was observed between 5 and 10 kg Zn ha -1 with high abundance of microbial gene families associated with zinc transporter proteins, antioxidant enzymes, exoenzymes associated with infection, secretion proteins, virulence regulatory genes, carbon fixation, and phosphorus utilization in soils supplemented with up to 5 kg Zn ha -1 . In these same soils, reduced abundance was observed for gene families associated with methanogenesis, metabolism of halogen and carotenoid, and antiphagocytosis compared with soil supplements with 10 or 20 kg Zn ha -1 . The results suggest that changes in microbial functional gene structure and abundance could be used to evaluate the impact of soil management practices on soil microbial communities in sugarcane production fields.

54 ENVIRONMENTAL SCIENCES↗

The role of histone tails in the nucleosome: A computational study

Histone tails play an important role in gene transcription and expression. We present here a systematic computational study of the role of histone tails in the nucleosome, using replica exchange molecular dynamics simulations with an implicit solvent model and different well-established force fields. We performed simulations for all four histone tails, H4, H3, H2A, and H2B, isolated and with inclusion of the nucleosome. The results confirm predictions of previous theoretical studies for the secondary structure of the isolated tails but show a strong dependence on the force field used. In the presence of the entire nucleosome for all force fields, the secondary structure of the histone tails is destabilized. Specific contacts are found between charged lysine and arginine residues and DNA phosphate groups and other binding sites in the minor and major DNA grooves. Using cluster analysis, we found a single dominant configuration of binding to DNA for the H4 and H2A histone tails, whereas H3 and H2B show multiple binding configurations with an equal probability. The leading stabilizing contribution for those binding configurations is the attractive interaction between the positively charged lysine and arginine residues and the negatively charged phosphate groups, and thus the resulting charge neutralization. Lastly, we present results of molecular dynamics simulations in explicit solvent to confirm our conclusions. Results from both implicit and explicit solvent models show that large portions of the histone tails are not bound to DNA, supporting the complex role of these tails in gene transcription and expression and making them possible candidates for binding sites of transcription factors, enzymes, and other proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Occupancy data analytics and prediction: A case study

Occupants are a critical impact factor of building energy consumption. Numerous previous studies emphasized the role of occupants and investigated the interactions between occupants and buildings. However, a fundamental problem, how to learn occupancy patterns and predict occupancy schedule, has not been well addressed due to highly stochastic activities of occupants and insufficient data. This study proposes a data mining based approach for occupancy schedule learning and prediction in office buildings. The proposed approach first recognizes the patterns of occupant presence by cluster analysis, then learns the schedule rules by decision tree, and finally predicts the occupancy schedules based on the inducted rules. A case study was conducted in an office building in Philadelphia, U.S. Based on one-year observed data, the validation results indicate that the proposed approach significantly improves the accuracy of occupancy schedule prediction. The proposed approach only requires simple input data (i.e., the time series data of occupant number entering and exiting a building), which is available in most office buildings. Furthermore, this approach is practical to facilitate occupancy schedule prediction, building energy simulation and facility operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Linking human-building interactions in shared offices with personality traits

Occupant behavior influences office building energy performance. The level of human-building interactions (HBIs) in shared offices strongly influences building energy use and occupant well-being. This study explored the link between occupant personality types and their behaviors of sharing energy and environment control systems and interactions with their colleagues. Inspired by the Five-Factor Model (FFM), we classified HBI behaviors into four dimensions: willingness to share control, knowledge of control, group decision behavior, and adaptive strategies. These four variables can be mapped to the four personality traits proposed by the FFM: agreeableness, openness, extraversion, and conscientiousness. Our cluster analysis identified six behavioral patterns: average (17.7%), reserved (15.3%), environmentally friendly (16.6%), role model (24.2%), self-centered (17.2%), and mechanist (9.0%). We further applied association rules, a widely utilized machine learning technique, to discover how demographics, building-related contextual factors, and perception-attitudinal factors influence HBI behaviors. Country, control feature accessibility, and group dynamics were found to be the three most influential factors that determine occupants’ HBI behaviors. Finally, the study provides insights about building design and operation, as well as policy to promote socially and environmentally desirable HBI behaviors in a shared office environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Seasonal differences in trace element concentrations and distribution in Spartina alterniflora root tissue

This study uses nanometer-scale synchrotron X-ray nanofluorescence to investigate season differences in concentrations and distributions of major (Ca, K, S and P) and trace elements (As, Cr, Cu, Fe and Zn) in the root system of Spartina alterniflora collected from Jamaica Bay, New York, in April and September 2015. The root samples were cross-sectioned at a thickness of 10 μm. Selected areas in the root epidermis and endodermis were mapped with a sampling resolution of 100 and 200 nm, varying with the mapping areas. The results indicate that trace element concentrations in the epidermis and endodermis vary among the elements measured, possibly because of their different chemical properties or their ability to act as micronutrients for the plants. Elemental concentrations (As, Ca, Cr, Cu, Fe, K, P, S and Zn) within each individual root sample and between the root samples collected during two different seasons are both significantly different (p < 0.01). Furthermore, this study indicates that the nonessential elements (As and Cr) are significantly correlated (p < 0.01) with Fe, with high concentrations in the root epidermis, while others are not, implying that Fe may be a barrier to nonessential element transport in the root system. Hierarchy cluster analysis shows two distinct groups, one including As, Cr and Fe and the other the rest of the elements measured. Factor analysis also indicates that the processes and mechanisms controlling element transport in the root system can be different between the nutrient and nonessential elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗