Temporal and spatial characteristics of ozone depletion events from measurements in the Arctic

Following polar sunrise in the Arctic springtime, tropospheric ozone episodically decreases rapidly to near-zero levels during ozone depletion events (ODEs). Many uncertainties remain in our understanding of ODE characteristics, including the temporal and spatial scales, as well as environmental drivers. Measurements of ozone, bromine monoxide (BrO), and meteorology were obtained during several deployments of autonomous, ice-tethered buoys (O-Buoys) from both coastal sites and over the Arctic Ocean; these data were used to characterize observed ODEs. Detected decreases in surface ozone levels during the onset of ODEs corresponded to a median estimated apparent ozone depletion timescale (based on both chemistry and the advection of O₃-depleted air) of 11 h. If assumed to be dominated by chemical mechanisms, these timescales would correspond to larger-than-observed BrO mole fractions based on known chemistry and assumed other radical levels. Using backward air mass trajectories and an assumption that transport mechanisms dominate observations, the spatial scales for ODEs (defined by time periods in which ozone levels ≤15 nmol mol⁻¹) were estimated to be 877 km (median), while areas estimated to represent major ozone depletions (<10 nmol mol⁻¹) had dimensions of 282 km (median). These observations point to a heterogeneous boundary layer with localized regions of active, ozone-destroying halogen chemistry, interspersed among larger regions of previously depleted air that retain reduced ozone levels through hindered atmospheric mixing. Based on the estimated size distribution, Monte Carlo simulations showed it was statistically possible that all ODEs observed could have originated upwind, followed by transport to the measurement site. Local wind speed averages were low during most ODEs (median of ~3.6 m s⁻¹), and there was no apparent dependence on local temperature

Differentiated neuroprogenitor cells incubated with human or canine adenovirus, or lentiviral vectors have distinct transcriptome profiles

Several studies have demonstrated the potential for vector-mediated gene transfer to the brain. Helper-dependent (HD) human (HAd) and canine (CAV-2) adenovirus, and VSV-G-pseudotyped self-inactivating HIV-1 vectors (LV) effectively transduce human brain cells and their toxicity has been partly analysed. However, their effect on the brain homeostasis is far from fully defined, especially because of the complexity of the central nervous system (CNS). With the goal of dissecting the toxicogenomic signatures of the three vectors for human neurons, we transduced a bona fide human neuronal system with HD-HAd, HD-CAV-2 and LV. We analysed the transcriptional response of more than 47,000 transcripts using gene chips. Chip data showed that HD-CAV-2 and LV vectors activated the innate arm of the immune response, including Toll-like receptors and hyaluronan circuits. LV vector also induced an IFN response. Moreover, HD-CAV-2 and LV vectors affected DNA damage pathways - but in opposite directions - suggesting a differential response of the p53 and ATM pathways to the vector genomes. As a general response to the vectors, human neurons activated pro-survival genes and neuron morphogenesis, presumably with the goal of re-establishing homeostasis. These data are complementary to in vivo studies on brain vector toxicity and allow a better understanding of the impact of viral vectors on human neurons, and mechanistic approaches to improve the therapeutic impact of brain-directed gene transfer

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959-2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free vs. ice-influenced) and bottom depth (shelf vs. deep ocean). The models performed relatively well for the most recent decade and towards the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. . Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling

Taxonomic and Environmental Variability in the Elemental Composition and Stoichiometry of Individual Dinoflagellate and Diatom Cells from the NW Mediterranean Sea

Here we present, for the first time, the elemental concentration, including C, N and O, of single phytoplankton cells collected from the sea. Plankton elemental concentration and stoichiometry are key variables in phytoplankton ecophysiology and ocean biogeochemistry, and are used to link cells and ecosystems. However, most field studies rely on bulk techniques that overestimate carbon and nitrogen because the samples include organic matter other than plankton organisms. Here we used X-ray microanalysis (XRMA), a technique that, unlike bulk analyses, gives simultaneous quotas of C, N, O, Mg, Si, P, and S, in single-cell organisms that can be collected directly from the sea. We analysed the elemental composition of dinoflagellates and diatoms (largely Chaetoceros spp.) collected from different sites of the Catalan coast (NW Mediterranean Sea). As expected, a lower C content is found in our cells compared to historical values of cultured cells. Our results indicate that, except for Si and O in diatoms, the mass of all elements is not a constant fraction of cell volume but rather decreases with increasing cell volume. Also, diatoms are significantly less dense in all the measured elements, except Si, compared to dinoflagellates. The N:P ratio of both groups is higher than the Redfield ratio, as it is the N:P nutrient ratio in deep NW Mediterranean Sea waters (N:P = 20–23). The results suggest that the P requirement is highest for bacterioplankton, followed by dinoflagellates, and lowest for diatoms, giving them a clear ecological advantage in P-limited environments like the Mediterranean Sea. Finally, the P concentration of cells of the same genera but growing under different nutrient conditions was the same, suggesting that the P quota of these cells is at a critical level. Our results indicate that XRMA is an accurate technique to determine single cell elemental quotas and derived conversion factors used to understand and model ocean biogeochemical cycles

DSYB catalyses the key step of dimethylsulfoniopropionate biosynthesis in many phytoplankton

Dimethylsulfoniopropionate (DMSP) is a globally important organosulfur molecule and the major precursor for dimethyl sulfide. These compounds are important info-chemicals, key nutrients for marine microorganisms, and are involved in global sulfur cycling, atmospheric chemistry and cloud formation1,2,3. DMSP production was thought to be confined to eukaryotes, but heterotrophic bacteria can also produce DMSP through the pathway used by most phytoplankton4, and the DsyB enzyme catalysing the key step of this pathway in bacteria was recently identified5. However, eukaryotic phytoplankton probably produce most of Earth’s DMSP, yet no DMSP biosynthesis genes have been identified in any such organisms. Here we identify functional dsyB homologues, termed DSYB, in many phytoplankton and corals. DSYB is a methylthiohydroxybutryate methyltransferase enzyme localized in the chloroplasts and mitochondria of the haptophyte Prymnesium parvum, and stable isotope tracking experiments support these organelles as sites of DMSP synthesis. DSYB transcription levels increased with DMSP concentrations in different phytoplankton and were indicative of intracellular DMSP. Identification of the eukaryotic DSYB sequences, along with bacterial dsyB, provides the first molecular tools to predict the relative contributions of eukaryotes and prokaryotes to global DMSP production. Furthermore, evolutionary analysis suggests that eukaryotic DSYB originated in bacteria and was passed to eukaryotes early in their evolution

Parameterizing the impact of seawater temperature and irradiance on dimethylsulfide (DMS) in the Great Barrier Reef and the contribution of coral reefs to the global sulfur cycle

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Jackson, R. L., Gabric, A. J., Matrai, P. A., Woodhouse, M. T., Cropp, R., Jones, G. B., Deschaseaux, E. S. M., Omori, Y., McParland, E. L., Swan, H. B., & Tanimoto, H. Parameterizing the impact of seawater temperature and irradiance on dimethylsulfide (DMS) in the Great Barrier Reef and the contribution of coral reefs to the global sulfur cycle. Journal of Geophysical Research:Oceans, 126(3), (2021): e2020JC016783, https://doi.org/10.1029/2020JC016783.Biogenic emissions of dimethylsulfide (DMS) are an important source of sulfur to the atmosphere, with implications for aerosol formation and cloud albedo over the ocean. Natural aerosol sources constitute the largest uncertainty in estimates of aerosol radiative forcing and climate and thus, an improved understanding of DMS sources is needed. Coral reefs are strong point sources of DMS; however, this coral source of biogenic sulfur is not explicitly included in climatologies or in model simulations. Consequently, the role of coral reefs in local and regional climate remains uncertain. We aim to improve the representation of tropical coral reefs in DMS databases by calculating a climatology of seawater DMS concentration (DMSw) and sea-air flux in the Great Barrier Reef (GBR), Australia. DMSw is calculated from remotely sensed observations of sea surface temperature and photosynthetically active radiation using a multiple linear regression model derived from field observations of DMSw in the GBR. We estimate that coral reefs and lagoon waters in the GBR (∼347,000 km2) release 0.03–0.05 Tg yr−1 of DMS (0.02 Tg yr−1 of sulfur). Based on this estimate, global tropical coral reefs (∼600,000 km2) could emit 0.08 Tg yr−1 of DMS (0.04 Tg yr−1 of sulfur), with the potential to influence the local radiative balance.Australian Research Council. Grant Number: DP150101649 National Science Foundation (NSF). Grant Number: 1543450 Ministry of Education, Culture, Sports, Science and Technology Grants-in-Aid for Scientific Research. Grant Number: 23310016,16H02967,24241010,15H01732 Ministry of Education, Culture, Sports, Science and Technology Grant-in-Aid for Young Scientists. Grant Number: 17K1281

Introducing the construct of risky cannabis use: designing and piloting a co-created educational intervention on cannabis health literacy among adolescents and young adults. The CAHLY (CAnabis Health LiteracY) study.

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An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters