Formulation and implementation of a residual-mean ocean circulation model

A parameterization of mesoscale eddies in coarse-resolution ocean general circulation models (GCM) is formulated and implemented using a residual-mean formalism. In that framework, mean buoyancy is advected by the residual velocity (the sum of the Eulerian and eddy-induced velocities) and modified by a residual flux which accounts for the diabatic effects of mesoscale eddies. The residual velocity is obtained by stepping forward a residual-mean momentum equation in which eddy stresses appear as forcing terms. Study of the spatial distribution of eddy stresses, derived by using them as control parameters to ‘‘fit’’ the residual-mean model to observations, supports the idea that eddy stresses can be likened to a vertical down-gradient flux of momentum with a coefficient which is constant in the vertical. The residual eddy flux is set to zero in the ocean interior, where mesoscale eddies are assumed to be quasi-adiabatic, but is parameterized by a horizontal down-gradient diffusivity near the surface where eddies develop a diabatic component as they stir properties horizontally across steep isopycnals. The residual-mean model is implemented and tested in the MIT general circulation model. It is shown that the resulting model (1) has a climatology that is superior to that obtained using the Gent and McWilliams parameterization scheme with a spatially uniform diffusivity and (2) allows one to significantly reduce the (spurious) horizontal viscosity used in coarse resolution GCMs.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Assessment of the effect of time and temperature on the availability of residual phosphate in a glasshouse study of four soils using the Olsen method

The Olsen method is an indicator of plant-available phosphorus (P). The effect of time and temperature on residual phosphate in soils was measured using the Olsen method in a pot experiment. Four soils were investigated: two from Pakistan and one each from England (calcareous) and Colombia (acidic). Two levels of residual phosphate were developed in each soil after addition of phosphate by incubation at either 10degreesC or 45degreesC. The amount of phosphate added was based on the P maximum of each soil, calculated using the Langmuir equation. Rvegrass was used as the test crop. The pooled data for the four soils incubated at 10degreesC showed good correlation between Olsen P and dry matter yield or P uptake (r(2) = 0.85 and 0.77, respectively), whereas at 45 degreesC, each soil had its own relationship and pooled data did not show correlation of Olsen P with dry matter yield or P uptake. When the data at both temperatures were pooled, Olsen P was a good indicator of yield and uptake for the English soil. For the Pakistani soils, Olsen P after 45 degreesC treatment was an underestimate relative to the 10 degreesC data and for the Colombian soil it was an overestimate. The reasons for these differences need to be explored further before high temperature incubation can be used to simulate long-term changes in the field.

Comparing sampling needs for variograms of soil properties computed by the method of moments and residual maximum likelihood

It has been generally accepted that the method of moments (MoM) variogram, which has been widely applied in soil science, requires about 100 sites at an appropriate interval apart to describe the variation adequately. This sample size is often larger than can be afforded for soil surveys of agricultural fields or contaminated sites. Furthermore, it might be a much larger sample size than is needed where the scale of variation is large. A possible alternative in such situations is the residual maximum likelihood (REML) variogram because fewer data appear to be required. The REML method is parametric and is considered reliable where there is trend in the data because it is based on generalized increments that filter trend out and only the covariance parameters are estimated. Previous research has suggested that fewer data are needed to compute a reliable variogram using a maximum likelihood approach such as REML, however, the results can vary according to the nature of the spatial variation. There remain issues to examine: how many fewer data can be used, how should the sampling sites be distributed over the site of interest, and how do different degrees of spatial variation affect the data requirements? The soil of four field sites of different size, physiography, parent material and soil type was sampled intensively, and MoM and REML variograms were calculated for clay content. The data were then sub-sampled to give different sample sizes and distributions of sites and the variograms were computed again. The model parameters for the sets of variograms for each site were used for cross-validation. Predictions based on REML variograms were generally more accurate than those from MoM variograms with fewer than 100 sampling sites. A sample size of around 50 sites at an appropriate distance apart, possibly determined from variograms of ancillary data, appears adequate to compute REML variograms for kriging soil properties for precision agriculture and contaminated sites. (C) 2007 Elsevier B.V. All rights reserved.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

A critical assessment of unbalanced surface stresses: Some complementary considerations

The wide-ranging survey of twisted growth in polymers by Lotz and Cheng cites extensive evidence consistent with the relief of surface stress being the underlying cause. This complementary note contributes to the discussion by making three main points. First, it is necessary to go further and explain the key issue of how a consistent twist is maintained when, as commonly, this habit has a lower symmetry than the crystallographic lattice. Detailed study has shown that, in polyethylene, this occurs by reorganization of the initial fold surfaces. Second, the suggested explanation by Keith and Padden that. in polyethylene, the asymmetric habit derives from molecules adding to lamellae with inclined fold surfaces is invalid being doubly inconsistent with observation. Third, twisting has now been linked to faster growth by study of row structures in polyethylene. This produces inherently rough fold surfaces in Regime II whose internal stresses drive reorganization and twisting. For slower (Regime I) growth, fold surfaces form with and maintain ordered packing so providing no basis for twisting. These new insights radically alter the context of twisted growth and provide a firm factual basis for further work. (c) 2005 Elsevier Ltd. All rights reserved.

Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture

Maize silage nutritive quality is routinely determined by near infrared reflectance spectroscopy (NIRS). However, little is known about the impact of sample preparation on the accuracy of the calibration to predict biological traits. A sample population of 48 maize silages representing a wide range of physiological maturities was used in a study to determine the impact of different sample preparation procedures (i.e., drying regimes; the presence or absence of residual moisture; the degree of particle comminution) on resultant NIR prediction statistics. All silages were scanned using a total of 12 combinations of sample pre-treatments. Each sample preparation combination was subjected to three multivariate regression techniques to give a total of 36 predictions per biological trait. Increased sample preparations procedure, relative to scanning the unprocessed whole plant (WP) material, always resulted in a numerical minimisation of model statistics. However, the ability of each of the treatments to significantly minimise the model statistics differed. Particle comminution was the most important factor, oven-drying regime was intermediate, and residual moisture presence was the least important. Models to predict various biological parameters of maize silage will be improved if material is subjected to a high degree of particle comminution (i.e., having been passed through a 1 mm screen) and developed on plant material previously dried at 60 degrees C. The extra effort in terms of time and cost required to remove sample residual moisture cannot be justified. (c) 2005 Elsevier B.V. All rights reserved.

Evidence for a residual postglacial founder effect in a highly dispersive freshwater invertebrate

In the northern hemisphere, glacial periods have had profound and lasting effects on the population genetics of numerous species, with founder effects often persisting for many generations in formerly glaciated regions. We found an unusual example of this in the freshwater bryozoan Cristatella mucedo, which showed regional differences in haplotype diversity with relatively low levels of haplotype diversity in northern Europe compared to central/southern Europe despite previous evidence for frequent dispersal between C. mucedo populations. Such contradictions between high dispersal and low gene flow have now been reported in several other freshwater taxa and may be attributed to persistent founder effects following colonization of sites by a few individuals whose efficient reproduction leads to rapid population growth. Alternatively, selection may determine which genotypes can thrive in northerly locations, or it may be that C. mucedo has undergone cryptic speciation. Future work on adaptive genomic regions is required before we can understand how gene flow, local adaptation, and speciation influence the current distribution patterns of bryozoans and other freshwater invertebrates.

Effect of fluid mechanical stresses and plasma constituents on aggregation of LDL

LDL aggregates when exposed to even moderate fluid mechanical stresses in the laboratory, yet its half-life in the circulation is 2-3 days, implying that little aggregation occurs. LDL may be protected from aggregation in vivo by components of plasma, or by a qualitative difference in flows. Previous studies have shown that HDL and albumin inhibit the aggregation induced by vortexing. Using a more reproducible method of inducing aggregation and assessing aggregation both spectrophotometrically and by sedimentation techniques, we showed that at physiological concentrations, albumin is the more effective inhibitor, and that aggregation is substantially but not completely inhibited in plasma. Heat denatured and fatty-acid-stripped albumin were more effective inhibitors than normal albumin, supporting the idea that hydrophobic interactions are involved. Aggregation of LDL in a model reproducing several aspects of flow in the circulation was 200-fold slower, but was still inhibited by HDL and albumin, suggesting similar mechanisms are involved. Within the sensitivity of our technique, LDL aggregation did not occur in plasma exposed to these flows.jlr Thus, as a result of the characteristics of blood flow and the inhibitory effects of plasma components, particularly albumin, LDL aggregation is unlikely to occur within the circulation.

Quantifying the residual creep life of polyester mooring ropes

This paper assesses the ARELIS (Assured Residual Life Span) method for estimating residual creep life of polyester rope used in deepwater mooring lines. A statistical model has been developed to quantify the uncertainties in the method, such as the scatter in creep rupture test data and load sharing between sub-ropes. This model can be used to determine the required test load, duration and number of ARELIS tests, in order to guarantee a minimum creep life for a mooring line at its service load. Creep rupture tests have been performed to provide input for the statistical model.

High hydrostatic pressure resistance of Campylobacter jejuni after different sublethal stresses

Aims: To study the development of resistance responses in Campylobacter jejuni to High Hydrostatic Pressure (HHP) treatments after the exposure to different stressful conditions that may be encountered in food processing environments, such as acid pH, elevated temperatures and cold storage. Methods and Results: C. jejuni cells in exponential and stationary growth phase were exposed to different sublethal stresses (acid, heat and cold shocks) prior to evaluate the development of resistance responses to HHP. For exponential-phase cells, neither of the conditions tested increased nor decreased HHP resistance of C. jejuni. For stationary-phase cells, acid and heat adaptation sensitized C. jejuni cells to the subsequent pressure treatment. On the contrary, cold-adapted stationary-phase cells developed resistance to HHP. Conclusions: Whereas C. jejuni can be classified as a stress sensitive microorganism, our findings have demonstrated that it can develop resistance responses under different stressing conditions. The resistance of stationary phase C. jejuni to HHP was increased after cells were exposed to cold temperatures. Significance and Impact of the Study: The results of this study contribute to a better knowledge of the physiology of C. jejuni and its survival to food preservation agents. Results here presented may help in the design of combined processes for food preservation based on HHP technology.