Time-averaged copper concentrations from continuous exposures predicts pulsed exposure toxicity to the marine diatom, Phaeodactylum tricornutum: importance of uptake and elimination

Intermittent, fluctuating and pulsed contaminant discharges result in organisms receiving highly variable contaminant exposures. Current water quality guidelines are predominantly derived using data from continuous exposure toxicity tests, and most frequently applied by regulators with the assumption that concentrations from a single sampling event will provide a meaningful approach to assessing potential effects. This study investigated the effect of single and multiple (daily) dissolved copper pulses on the marine diatom, Phaeodactylum tricornutum, including measurements of copper uptake and elimination to investigate the toxic mechanism. Copper pulses of between 0.5 and 24 h and continuous exposures with equivalent 72-h time-averaged concentrations (TACs) resulted in similar biomass inhibition of P. tricornutum, with continuous exposures often being marginally more toxic. Rates of cell division generally recovered to control levels within 24 h of the copper pulse removal. Upon resuspension in clean seawater, the extracellular copper per cell decreased rapidly, whereas the intracellular copper per cell decreased slowly. Negligible loss of copper from the total algal biomass indicated that P. tricornutum did not have an effective mechanism for eliminating copper from cells, rather the intracellular copper decreased as a result of dilution by cellular division as the algal growth rate recovered. The measurement of copper uptake after 72-h exposure and kinetics of elimination thereafter suggest that continuous exposures are marginally more toxic to P. tricornutum than pulsed copper exposures with equivalent TACs because slow internalization and saturation of algal membrane transport sites results in less copper uptake into pulse-exposed cells than continuously-exposed cells coupled with dilution of internalized copper via cellular division in the post-exposure period. In the case of P. tricornutum, the results indicate that water quality guidelines for copper based on continuous exposure will be conservative when applied to short-term discharges

Disproportionation of Iron in Almandine-Pyrope-Grossular Garnet From 25 to 65 GPa

The production of metal via the iron disproportionation reaction in the deep Earth has been a long debated topic with important implications for the geochemistry of the lower mantle. To explore the occurrence of the iron disproportionation reaction from 25 to 65 GPa, a natural almandine-pyrope-grossular garnet was studied with in situ X-ray diffraction (XRD) in the laser-heated diamond anvil cell and ex situ scanning electron microscopy (SEM) techniques. Upon heating the natural almandine-pyrope-grossular garnet up to 3000 K up to 65 GPa, the formation of phase assemblage consisting of bridgmanite, stishovite, and davemaoite was confirmed by XRD, but because of the low abundance of Fe metal and small grain size, XRD was determined not to be effective in detecting the disproportionation reaction. Examination of the samples recovered between 39 and 64 GPa by SEM analysis revealed the presence of nm-scale disproportionated iron metal grains as an additional product of this reaction that was not detectable in the XRD patterns. Volume compression data of bridgmanite synthesized in the experiments were fit to the Birch-Murnaghan equation of state and compared to similar compositions. Bridgmanite was found to decompress to the LiNbO3-type structure, indicating a high FeAlO3 content, in accordance with the occurrence of a disproportionation reaction. The experimental confirmation of disproportionated metallic Fe has significant implications for the distribution of siderophile and volatile elements in the lower mantle

16.精子形成のホルモン支配(第669回千葉医学会例会・第38回千葉泌尿器科集談会)

Understanding the temporal and spatial variability in a crop yield is viewed as one of the key steps in the implementation of precision agriculture practices. Therefore, a study on a center pivot irrigated 23.5 ha field in Saudi Arabia was conducted to assess the variability in alfalfa yield using Landsat-8 imagery and a hay yield monitor data. In addition, the study was designed to also explore the potential of predicting the alfalfa yield using vegetation indices. A calibrated yield monitor mounted on a large rectangular hay baler was used to measure the actual alfalfa yield for four alfalfa harvests performed in the period from October 2013 to May 2014. A total of 18 Landsat-8 images, representing different crop growth stages, were used to derive different vegetation indices (VIs). Data from the yield monitor was used to generate yield maps, which illustrated a definite spatial variation in alfalfa yield across the experimental field for the four studied harvests as indicated by the high spatial correlation values (0.75 to 0.97) and the low P-values (4.7E-103 to 8.9E-27). The yield monitor-measured alfalfa actual yield was compared to the predicted yield form the Vis. Results of the study showed that there was a correlation between actual and predicted yield. The highest correlations were observed between actual yield and the predicted using NIR reflectance, SAVI and NDVI with maximum correlation coefficients of 0.69, 0.68 and 0.63, respectively

Forest top canopy bacterial communities are influenced by elevation and host tree traits

Background: The phyllosphere microbiome is crucial for plant health and ecosystem functioning. While host species play a determining role in shaping the phyllosphere microbiome, host trees of the same species that are subjected to different environmental conditions can still exhibit large degrees of variation in their microbiome diversity and composition. Whether these intra-specific variations in phyllosphere microbiome diversity and composition can be observed over the broader expanse of forest landscapes remains unclear. In this study, we aim to assess the variation in the top canopy phyllosphere bacterial communities between and within host tree species in the temperate European forests, focusing on Fagus sylvatica (European beech) and Picea abies (Norway spruce).Results: We profiled the bacterial diversity, composition, driving factors, and discriminant taxa in the top canopy phyllosphere of 211 trees in two temperate forests, Veluwe National Parks, the Netherlands and Bavarian Forest National Park, Germany. We found the bacterial communities were primarily shaped by host species, and large variation existed within beech and spruce. While we showed that there was a core microbiome in all tree species examined, community composition varied with elevation, tree diameter at breast height, and leaf-specific traits (e.g., chlorophyll and P content). These driving factors of bacterial community composition also correlated with the relative abundance of specific bacterial families.Conclusions: While our results underscored the importance of host species, we demonstrated a substantial range of variation in phyllosphere bacterial diversity and composition within a host species. Drivers of these variations have implications at both the individual host tree level, where the bacterial communities differed based on tree traits, and at the broader forest landscape level, where drivers like certain highly plastic leaf traits can potentially link forest canopy bacterial community variations to forest ecosystem processes. We eventually showed close associations between forest canopy phyllosphere bacterial communities and host trees exist, and the consistent patterns emerging from these associations are critical for host plant functioning

Using Bayesian Networks to Predict Risk to Estuary Water Quality and Patterns of Benthic Environmental DNA in Queensland

Predictive modeling can inform natural resource management by representing stressor-response pathways in a logical way and quantifying the effects on selected endpoints. This study demonstrates a risk assessment model using the Bayesian network-relative risk model (BNRRM) approach to predict water quality and; for the first time, eukaryote environmental DNA (eDNA) data as a measure of benthic community structure. Environmental DNA sampling is a technique for biodiversity measurements that involves extracting DNA from environmental samples, amplicon sequencing a targeted gene, in this case the 18s rDNA gene which targets eukaryotes, and matching the sequences to organisms. Using a network of probability distributions, the BN-RRM model predicts risk to water quality objectives and the relative richness of benthic taxa groups in the Noosa, Pine, and Logan estuaries in South East Queensland (SEQ), Australia. The model predicts Dissolved Oxygen more accurately than the Chlorophyll-a water quality endpoint, and photosynthesizing benthos more accurately than heterotrophs. Results of BN-RRM modeling given current inputs indicate that the water quality and benthic assemblages of the Noosa are relatively homogenous across all sub risk regions, and that the Noosa has a 73 – 92 percent probability of achieving water quality objectives, indicating a low relative risk. Conversely, the Middle Logan, Middle Pine, and Lower Pine regions are much less likely to meet objectives (15 – 55 percent probability), indicating a relatively higher risk to water quality in those regions. The benthic community richness patterns associated with risk in the Noosa are high Diatom relative richness and low Green Algae relative richness. The only benthic pattern consistently associated with the relatively higher risk to water quality is high richness of fungi species. The BN-RRM model provides a basis for future predictions and adaptive management at the direction of resource managers

High-Resolution In-situ Synchrotron X-ray Studies of Inorganic Perovskite CsPbBr3_3: New Symmetry Assignments and Structural Phase Transitions

Perovskite photovoltaic ABX$_3$ systems are being studied due to their high energy-conversion efficiencies with current emphasis placed on pure inorganic systems. In this work, synchrotron single-crystal diffraction measurements combined with second harmonic generation measurements reveal the absence of inversion symmetry below room temperature in CsPbBr$_3$. Local structural analysis by pair distribution function and X-ray absorption fine structure methods are performed to ascertain the local ordering, atomic pair correlations, and phase evolution in a broad range of temperatures. The currently accepted space group assignments for CsPbBr$_3$ are found to be incorrect in a manner that profoundly impacts physical properties. New assignments are obtained for the bulk structure: $Im$$\bar{3}$ (above $\sim$ 410 K), $P$2$_1$/$m$ (between $\sim$ 300 K and $\sim$ 410 K), and the polar group $Pm$ (below $\sim$ 300 K), respectively. The newly observed structural distortions exist in the bulk structure consistent with the expectation of previous photoluminescence and Raman measurements. High-pressure measurements reveal multiple low-pressure phases, one of which exists as a metastable phase at ambient pressure. This work should help guide research in the perovskite photovoltaic community to better control the structure under operational conditions and further improve transport and optical properties.Comment: 7 Figures in main text (20 pages), 18 Figure groups and 10 Table groups in supplementary documentation (42 pages

Ecosystems monitoring powered by environmental genomics: a review of current strategies with an implementation roadmap

A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or “in development”, hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics-based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (a) Taxonomy-based analyses focused on identification of known bioindicators or described taxa; (b) De novo bioindicator analyses; (c) Structural community metrics including inferred ecological networks; and (d) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programmes that leverage recent analytical advancements, while pointing out current limitations and future research needs.publishedVersio

Heavy metal soil contamination detection using combined geochemistry and field spectroradiometry in the United Kingdom

Technological advances in hyperspectral remote sensing have been widely applied in heavy metal soil contamination studies, as they are able to provide assessments in a rapid and cost-effective way. The present work investigates the potential role of combining field and laboratory spectroradiometry with geochemical data of lead (Pb), zinc (Zn), copper (Cu) and cadmium (Cd) in quantifying and modelling heavy metal soil contamination (HMSC) for a floodplain site located in Wales, United Kingdom. The study objectives were to: (i) collect field- and lab-based spectra from contaminated soils by using ASD FieldSpec® 3, where the spectrum varies between 350 and 2500 nm; (ii) build field- and lab-based spectral libraries; (iii) conduct geochemical analyses of Pb, Zn, Cu and Cd using atomic absorption spectrometer; (iv) identify the specific spectral regions associated to the modelling of HMSC; and (v) develop and validate heavy metal prediction models (HMPM) for the aforementioned contaminants, by considering their spectral features and concentrations in the soil. Herein, the field- and lab-based spectral features derived from 85 soil samples were used successfully to develop two spectral libraries, which along with the concentrations of Pb, Zn, Cu and Cd were combined to build eight HMPMs using stepwise multiple linear regression. The results showed, for the first time, the feasibility to predict HMSC in a highly contaminated floodplain site by combining soil geochemistry analyses and field spectroradiometry. The generated models help for mapping heavy metal concentrations over a huge area by using space-borne hyperspectral sensors. The results further demonstrated the feasibility of combining geochemistry analyses with filed spectroradiometric data to generate models that can predict heavy metal concentrations