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Rather than being solid throughout, sea ice contains liquid brine inclusions, solid salts, microalgae, trace elements, gases, and other impurities which all exist in the interstices of a porous, solid ice matrix. This multiphase structure of sea ice arises from the fact that the salt that exists in seawater cannot be incorporated into lattice sites in the pure ice component of sea ice, but remains in liquid solution. Depending on the ice permeability (determined by temperature, salinity and gas content), this brine can drain from the ice, taking other sea ice constituents with it. Thus, sea ice salinity and microstructure are tightly interconnected and play a significant role in polar ecosystems and climate. As large-scale climate modeling efforts move toward \"earth system\" simulations that include biological and chemical cycles, renewed interest in the multiphase physics of sea ice has strengthened research initiatives to observe, understand and model this complex system. This review article provides an overview of these efforts, highlighting known difficulties and requisite observations for further progress in the field. We focus on mushy layer theory, which describes general multiphase materials, and on numerical approaches now being explored to model the multiphase evolution of sea ice and its interaction with chemical, biological and climate systems.

Research on the interactions between the field voles (Microtus agrestis) of Kielder Forest and their natural parasites dates back to the 1930s. These early studies were primarily concerned with understanding how parasites shape the characteristic cyclic population dynamics of their hosts. However, since the early 2000s, research on the Kielder field voles has expanded considerably and the system has now been utilized for the study of host–parasite biology across many levels, including genetics, evolutionary ecology, immunology and epidemiology. The Kielder field voles therefore represent one of the most intensely and broadly studied natural host–parasite systems, bridging theoretical and empirical approaches to better understand the biology of infectious disease in the real world. This article synthesizes the body of work published on this system and summarizes some important insights and general messages provided by the integrated and multidisciplinary study of host–parasite interactions in the natural environment.

The epidemiology of osteoporosis in male and minority populations is understudied. We compared BMD in 1,209 Black, Hispanic, and White men. Black men exhibited higher BMD than Hispanic or White men. Age-related BMD decreases were greatest among Hispanic men. Results may help explain variation in hip fracture rates by race/ethnicity. The epidemiology of osteoporosis in male and minority populations is understudied. To address this concern, we conducted a study of skeletal health in a diverse population of adult males. A total of 367 Black, 401 Hispanic, and 451 White men aged 30-79 years were randomly sampled from Boston, MA. Bone densitometry (bone area (BA), bone mineral content (BMC), and bone mineral density (BMD)) at the whole body, hip, lumbar spine, and forearm was performed. Multiple regression analyses on 1,209 men with available data were used to describe race/ethnic group-specific means (height- and age-adjusted) and age trends (height-adjusted) in BMC, BA, and BMD. Results were weighted to represent the Boston male population aged 30-79 years. Black men had greater BMC and BMD than Hispanic or White men. Femoral neck BMD was 5.6% and 13.3% higher in Black men than in Hispanic and White men, respectively. Differences between Hispanic and White subjects were restricted to the hip. Age-related declines in BMC and BMD were significantly steeper among Hispanic than Black or White men. Differences in BMC and BMD could explain variation in fracture rates among Black, Hispanic, and White men. The steeper age-related BMD decline in Hispanic men is of particular concern.

A robust classification scheme for partitioning water chemistry samples into homogeneous groups is an important tool for the characterization of hydrologic systems. In this paper we test the performance of the many available graphical and statistical methodologies used to classify water samples including: Collins bar diagram, pie diagram, Stiff pattern diagram, Schoeller plot, Piper diagram, Q-mode hierarchical cluster analysis, K-means clustering, principal components analysis, and fuzzy k-means clustering. All the methods are discussed and compared as to their ability to cluster, ease of use, and ease of interpretation. In addition, several issues related to data preparation, database editing, data-gap filling, data screening, and data quality assurance are discussed and a database construction methodology is presented.The use of graphical techniques proved to have limitations compared with the multivariate methods for large data sets. Principal components analysis is useful for data reduction and to assess the continuity/overlap of clusters or clustering/similarities in the data. The most efficient grouping was achieved by statistical clustering techniques. However, these techniques do not provide information on the chemistry of the statistical groups. The combination of graphical and statistical techniques provides a consistent and objective means to classify large numbers of samples while retaining the ease of classic graphical presentations.

This paper documents the biogeochemistry configuration of the Energy Exascale Earth System Model (E3SM), E3SMv1.1‐BGC. The model simulates historical carbon cycle dynamics, including carbon losses predicted in response to land use and land cover change, and the responses of the carbon cycle to changes in climate. In addition, we introduce several innovations in the treatment of soil nutrient limitation mechanisms, including explicit dependence on phosphorus availability. The suite of simulations described here includes E3SM contributions to the Coupled Climate‐Carbon Cycle Model Intercomparison Project and other projects, as well as simulations to explore the impacts of structural uncertainty in representations of nitrogen and phosphorus limitation. We describe the model spin‐up and evaluation procedures, provide an overview of results from the simulation campaign, and highlight key features of the simulations. Cumulative warming over the twentieth century is similar to observations, with a midcentury cold bias offset by stronger warming in recent decades. Ocean biomass production and carbon uptake are underpredicted, likely due to biases in ocean transport leading to widespread anoxia and undersupply of nutrients to surface waters. The inclusion of nutrient limitations in the land biogeochemistry results in weaker carbon fertilization and carbon‐climate feedbacks than exhibited by other Earth System Models that exclude those limitations. Finally, we compare with an alternative representation of terrestrial biogeochemistry, which differs in structure and in initialization of soil phosphorus. While both configurations agree well with observational benchmarks, they differ significantly in their distribution of carbon among different pools and in the strength of nutrient limitations. Plain Language Summary A new state‐of‐the‐art Earth System Model has been funded by the United States Department of Energy (DOE) to explore questions relevant to DOE's mission. The Energy Exascale Earth System Model version 1.1 (E3SMv1.1) represents nitrogen and phosphorous controls on the carbon cycle and extends the recently released E3SMv1 to include active biogeochemistry in the land, ocean, and ice components. E3SMv1.1 also includes an alternative representation of terrestrial carbon and nutrient cycles that is used to explore model structural uncertainties. E3SMv1.1's capabilities are demonstrated through a set of experiments described by the Coupled Climate‐Carbon Cycle Model Intercomparison Project, aimed at understanding the influence of changes in climate and CO2 on the carbon cycle. Simulations of the land surface properties and terrestrial carbon cycle compare well with observations, as does the simulated global and regional climate. Nutrient limitations result in less land carbon uptake compared to models that exclude these limitations. However, variations in model structure and initialization influence the magnitude of those limitations and carbon cycle dynamics. The ocean biogeochemistry in E3SMv1.1 simulates less biomass and slightly lower anthropogenic carbon uptake than is observed. Future efforts will aim to reduce model biases as well as to include additional aspects of global carbon cycle dynamics. Key Points Introduces the U.S. DOE's Energy Exascale Earth System Model‐Biogeochemistry version, E3SMv1.1‐BGC, is introduced Ecosystem‐climate responses are characterized in a standard set of C4MIP‐type simulations The impacts of terrestrial nitrogen and phosphorus limitations and their structural uncertainties are explored

Local inflammation elicited by Neisseria gonorrhoeae correlates closely with sensitivity to killing by normal human serum. Serum-sensitive (SS) isolates are rendered resistant in vitro by lipooligosaccharide sialylation. Differences in C3b processing on N. gonorrhoeae in vitro were found to match findings at the cervical level in vivo. Nonsialylated SS gonococci bound 5-fold more C3b than did stably serum-resistant (SR) gonococci; most was processed to iC3b, yet significant C3b persisted. Sialylated SS gonococci bound 4-fold less total C3 antigen than did SR gonococci, which was promptly converted to iC3b. C3b bound later on stably SR gonococci but again was processed swiftly to iC3b. In vivo, the iC3b/C3 ratio of SS isolates more closely resembled nonsialylated SS isolates in vitro, implying heterogeneous sialylation or desialylation in vivo. In vitro, total IgM bound was unchanged by sialylation of SS isolates, but total C4 bound decreased by 75%, suggesting that sialylation may indirectly regulate the classical complement pathway.

A new sea ice dynamical core, the Discrete Element Model for Sea Ice (DEMSI), is under development for use in coupled Earth system models. DEMSI is based on the discrete element method, which models collections of ice floes as interacting Lagrangian particles. In basin-scale sea ice simulations the Lagrangian motion results in significant convergence and ridging, which requires periodic remapping of sea ice variables from a deformed particle configuration back to an undeformed initial distribution. At the resolution required for Earth system models we cannot resolve individual sea ice floes, so we adopt the sub-grid-scale thickness distribution used in continuum sea ice models. This choice leads to a series of hierarchical tracers depending on ice fractional area or concentration that must be remapped consistently. The circular discrete elements employed in DEMSI help improve the computational efficiency at the cost of increased complexity in the effective element area definitions for sea ice cover that are required for the accurate enforcement of conservation. An additional challenge is the accurate remapping of element values along the ice edge, the location of which varies due to the Lagrangian motion of the particles. In this paper we describe a particle-to-particle remapping approach based on well-established geometric remapping ideas that enforces conservation, bounds preservation, and compatibility between associated tracer quantities, while also robustly managing remapping at the ice edge. One element of the remapping algorithm is a novel optimization-based flux correction that enforces concentration bounds in the case of nonuniform motion. We demonstrate the accuracy and utility of the algorithm in a series of numerical test cases.

Icepack (v1.1.0) – the column thermodynamics model of the Community Ice CodE (CICE) version 6 – is used to assess how changing the thermodynamics from the Bitz and Lipscomb (1999) physics (hereafter BL99) to the mushy-layer physics impacts the model performance in reproducing in situ landfast ice observations from two ice mass balance (IMB) buoys co-deployed in the landfast ice close to Nain (Labrador) in February 2017. To this end, a new automated surface retrieval algorithm is used to determine the in situ ice thickness, snow depth, basal ice congelation and snow-ice formation from the measured vertical temperature profiles. Icepack simulations are run to reproduce these observations using each thermodynamics scheme, with a particular interest in how the different physics influence the representation of snow-ice formation and ice congelation. Results show that the BL99 parameterization represents well the ice congelation but underrepresents the snow-ice contribution to the ice mass balance. In particular, defining snow-ice formation based on the hydrostatic balance alone does not reproduce the negative freeboards observed for several days in the IMB observations, resulting in an earlier snow-flooding onset, a positive ice thickness bias and reduced snow depth variations. We find that the mushy-layer thermodynamics with default parameters significantly degrades the model performance, overestimating both the congelation growth and snow-ice formation. The simulated thermodynamics response to flooding, however, better represents the observations, and the best results are obtained when allowing for negative freeboards in the mushy-layer physics. We find that the mushy-layer thermodynamics produces a larger variability in congelation rates at the ice bottom interface, alternating between periods of exceedingly fast growth and periods of unrealistic basal melt. This pattern is related to persistent brine dilution in the lowest ice layer by the congelation and brine drainage parameterizations. We also show that the mushy-layer congelation parameterization produces significant frazil formation, which is not expected in a landfast ice context. This behavior is attributed to the congelation parameterization not fully accounting for the conductive heat flux imbalance at the ice–ocean boundary. We propose a modification of the mushy-layer congelation scheme that largely reduces the frazil formation and allows for better tuning of the congelation rates to match the observations. Our results demonstrate that the mushy-layer physics and its parameters can be tuned to closely match the in situ observations, although more observations are needed to better constrain them.

A recombinant strain of attenuated Salmonella enterica serovar Typhi surface-expressing Yersinia pestis F1 antigen was generated by transforming strain BRD1116 ( aroA aroC htrA) with plasmid pAH34L encoding the Y. pestis caf operon. BRD1116/pAH34L was stable in vitro and in vivo. An immunisation regimen of two intranasal doses of 1×10 8 cfu of BRD1116/pAH34L given intranasally to mice 7 days apart induced the strongest immune response compared to other regimens and protected 13 out of 20 mice from lethal challenge with Y. pestis. Intranasal immunisation of mice constitutes a model for oral immunisation with Salmonella vaccines in humans. Thus, the results demonstrate that attenuated strains of S. enterica serovar Typhi which express Y. pestis F1 antigen may be developed to provide an oral vaccine against plague suitable for use in humans.

We present MPAS-Seaice, a sea-ice model which uses the Model for Prediction Across Scales (MPAS) framework and spherical centroidal Voronoi tessellation (SCVT) unstructured meshes. As well as SCVT meshes, MPAS-Seaice can run on the traditional quadrilateral grids used by sea-ice models such as CICE. The MPAS-Seaice velocity solver uses the elastic–viscous–plastic (EVP) rheology and the variational discretization of the internal stress divergence operator used by CICE, but adapted for the polygonal cells of MPAS meshes, or alternatively an integral (“finite-volume”) formulation of the stress divergence operator. An incremental remapping advection scheme is used for mass and tracer transport. We validate these formulations with idealized test cases, both planar and on the sphere. The variational scheme displays lower errors than the finite-volume formulation for the strain rate operator but higher errors for the stress divergence operator. The variational stress divergence operator displays increased errors around the pentagonal cells of a quasi-uniform mesh, which is ameliorated with an alternate formulation for the operator. MPAS-Seaice shares the sophisticated column physics and biogeochemistry of CICE and when used with quadrilateral meshes can reproduce the results of CICE. We have used global simulations with realistic forcing to validate MPAS-Seaice against similar simulations with CICE and against observations. We find very similar results compared to CICE, with differences explained by minor differences in implementation such as with interpolation between the primary and dual meshes at coastlines. We have assessed the computational performance of the model, which, because it is unstructured, runs with 70 % of the throughput of CICE for a comparison quadrilateral simulation. The SCVT meshes used by MPAS-Seaice allow removal of equatorial model cells and flexibility in domain decomposition, improving model performance. MPAS-Seaice is the current sea-ice component of the Energy Exascale Earth System Model (E3SM).