High resolution quantitative computed tomography-based assessment of trabecular microstructure and strength estimates by finite-element analysis of the spine, but not DXA, reflects vertebral fracture status in men with glucocorticoid-induced osteoporosis

High-resolution quantitative computed tomography (HRQCT)-based analysis of spinal bone density and microstructure, finite element analysis (FEA), and DXA were used to investigate the vertebral bone status of men with glucocorticoid-induced osteoporosis (GIO). DXA of L1–L3 and total hip, QCT of L1–L3, and HRQCT of T12 were available for 73 men (54.6±14.0years) with GIO. Prevalent vertebral fracture status was evaluated on radiographs using a semi-quantitative (SQ) score (normal=0 to severe fracture=3), and the spinal deformity index (SDI) score (sum of SQ scores of T4 to L4 vertebrae). Thirty-one (42.4%) subjects had prevalent vertebral fractures. Cortical BMD (Ct.BMD) and thickness (Ct.Th), trabecular BMD (Tb.BMD), apparent trabecular bone volume fraction (app.BV/TV), and apparent trabecular separation (app.Tb.Sp) were analyzed by HRQCT. Stiffness and strength of T12 were computed by HRQCT-based nonlinear FEA for axial compression, anterior bending and axial torsion. In logistic regressions adjusted for age, glucocorticoid dose and osteoporosis treatment, Tb.BMD was most closely associated with vertebral fracture status (standardized odds ratio [sOR]: Tb.BMD T12: 4.05 [95% CI: 1.8–9.0], Tb.BMD L1–L3: 3.95 [1.8–8.9]). Strength divided by cross-sectional area for axial compression showed the most significant association with spine fracture status among FEA variables (2.56 [1.29–5.07]). SDI was best predicted by a microstructural model using Ct.Th and app.Tb.Sp (r2=0.57, p<0.001). Spinal or hip DXA measurements did not show significant associations with fracture status or severity. In this cross-sectional study of males with GIO, QCT, HRQCT-based measurements and FEA variables were superior to DXA in discriminating between patients of differing prevalent vertebral fracture status. A microstructural model combining aspects of cortical and trabecular bone reflected fracture severity most accurately.

Pressure-temperature estimates of the lizardite/antigorite transition in high pressure serpentinites

Serpentine minerals in natural samples are dominated by lizardite and antigorite. In spite of numerous laboratory experiments, the stability fields of these species remain poorly constrained. This paper presents petrological observations and the Raman spectroscopy and XRD analyses of natural serpentinites from the Alpine paleo-accretionary wedge. Serpentine varieties were identified from a range of metamorphic pressure and temperature conditions from sub-greenschist (P < 4 kbar, T ~ 200–300 °C) to eclogite facies conditions (P > 20 kbar, T > 460 °C) along a subduction geothermal gradient. We use the observed mineral assemblage in natural serpentinite along with the Tmax estimated by Raman spectroscopy of the carbonaceous matter in associated metasediments to constrain the temperature of the lizardite to antigorite transition at high pressures. We show that below 300 °C, lizardite and locally chrysotile are the dominant species in the mesh texture. Between 320 and 390 °C, lizardite is progressively replaced by antigorite at the grain boundaries through dissolution–precipitation processes in the presence of SiO2 enriched fluids and in the cores of the lizardite mesh. Above 390 °C, under high-grade blueschist to eclogite facies conditions, antigorite is the sole stable serpentine mineral until the onset of secondary olivine crystallization at 460 °C.

Plotting regression coefficients and other estimates in Stata

Graphical presentation of regression results has become increasingly popular in the scientific literature, as graphs are much easier to read than tables in many cases. In Stata such plots can be produced by the -marginsplot- command. However, while -marginsplot- is very versatile and flexible, it has two major limitations: it can only process results left behind by -margins- and it can only handle one set of results at the time. In this article I introduce a new command called -coefplot- that overcomes these limitations. It plots results from any estimation command and combines results from several models into a single graph. The default behavior of -coefplot- is to plot markers for coefficients and horizontal spikes for confidence intervals. However, -coefplot- can also produce various other types of graphs. The capabilities of -coefplot- are illustrated in this article using a series of examples.

Evaluation of the accuracy of multilevel analysis parameter estimates for intra-cluster correlation in correlated binary data

Many studies in biostatistics deal with binary data. Some of these studies involve correlated observations, which can complicate the analysis of the resulting data. Studies of this kind typically arise when a high degree of commonality exists between test subjects. If there exists a natural hierarchy in the data, multilevel analysis is an appropriate tool for the analysis. Two examples are the measurements on identical twins, or the study of symmetrical organs or appendages such as in the case of ophthalmic studies. Although this type of matching appears ideal for the purposes of comparison, analysis of the resulting data while ignoring the effect of intra-cluster correlation has been shown to produce biased results.^ This paper will explore the use of multilevel modeling of simulated binary data with predetermined levels of correlation. Data will be generated using the Beta-Binomial method with varying degrees of correlation between the lower level observations. The data will be analyzed using the multilevel software package MlwiN (Woodhouse, et al, 1995). Comparisons between the specified intra-cluster correlation of these data and the estimated correlations, using multilevel analysis, will be used to examine the accuracy of this technique in analyzing this type of data. ^

Robust estimates of climate-induced hydrological change in a temperate mountainous region

A sustainable water resources management depends on sound information about the impacts of climate change. This information is, however, not easily derived because natural runoff variability interferes with the climate change signal. This study presents a procedure that leads to robust estimates of magnitude and Time Of Emergence (TOE) of climate-induced hydrological change that also account for the natural variability contained in the time series. Firstly, natural variability of 189 mesoscale catchments in Switzerland is sampled for 10 ENSEMBLES scenarios for the control (1984–2005) and two scenario periods (near future: 2025–2046, far future: 2074–2095) applying a bootstrap procedure. Then, the sampling distributions of mean monthly runoff are tested for significant differences with the Wilcoxon-Mann–Whitney test and for effect size with Cliff’s delta d. Finally, the TOE of a climate change induced hydrological change is determined when at least eight out of the ten hydrological projections significantly differ from natural variability. The results show that the TOE occurs in the near future period except for high-elevated catchments in late summer. The significant hydrological projections in the near future correspond, however, to only minor runoff changes. In the far future, hydrological change is statistically significant and runoff changes are substantial. Temperature change is the most important factor determining hydrological change in this mountainous region. Therefore, hydrological change depends strongly on a catchment’s mean elevation. Considering that the hydrological changes are predicted to be robust in the near future highlights the importance of accounting for these changes in water resources planning.

Model-Based Estimates of Calanus Finmarchicus Abundance in the Gulf of Maine

Ocean observing systems and satellites routinely collect a wealth of information on physical conditions in the ocean. With few exceptions, such as chlorophyll concentrations, information on biological properties is harder to measure autonomously. Here, we present a system to produce estimates of the distribution and abundance of the copepod Calanus finmarchicus in the Gulf of Maine. Our system uses satellite-based measurements of sea surface temperature and chlorophyll concentration to determine the developmental and reproductive rates of C. finmarchicus. The rate information then drives a population dynamics model of C. finmarchicus that is embedded in a 2-dimensional circulation field. The first generation of this system produces realistic information on interannual variability in C. finmarchicus distribution and abundance during the winter and spring. The model can also be used to identify key drivers of interannual variability in C. finmarchicus. Experiments with the model suggest that changes in initial conditions are overwhelmed by variability in growth rates after approximately 50 d. Temperature has the largest effect on growth rate. Elevated chlorophyll during the late winter can lead to increased C. finmarchicus abundance during the spring, but the effect of variations in chlorophyll concentrations is secondary to the other inputs. Our system could be used to provide real-time estimates or even forecasts of C. finmarchicus distribution. These estimates could then be used to support management of copepod predators such as herring and right whales.

Model-Based Estimates of Right Whale Habitat Use in the Gulf of Maine

Balancing human uses of the marine environment with the recovery of protected species requires accurate information on when and where species of interest are likely to be present. Here, we describe a system that can produce useful estimates of right whale Eubalaena glacialis presence and abundance on their feeding grounds in the Gulf of Maine. The foundation of our system is a coupled physical-biological model of the copepod Calan us finmarchicus, the preferred prey of right whales. From the modeled prey densities, we can estimate when whales will appear in the Great South Channel feeding ground. Based on our experience with the system, we consider how the relationship between right whales and copepods changes across spatial scales. The scale-dependent relationship between whales and copepods provides insight into how to improve future estimates of the distribution of right whales and other pelagic predators.

Tree size and fecundity influence ballistic seed dispersal of two dominant mast-fruiting species in a tropical rain forest

Seed production, seed dispersal, and seedling recruitment are integral to forest dynamics, especially in masting species. Often these are studied separately, yet scarcely ever for species with ballistic dispersal even though this mode of dispersal is common in legume trees of tropical African rain forests. Here, we studied two dominant main-canopy tree species, Microberlinia bisulcata and Tetraberlinia bifoliolata (Caesalpinioideae), in 25 ha of primary rain forest at Korup, Cameroon, during two successive masting events (2007/2010). In the vicinity of c. 100 and 130 trees of each species, 476/580 traps caught dispersed seeds and beneath their crowns c. 57,000 pod valves per species were inspected to estimate tree-level fecundity. Seed production of trees increased non-linearly and asymptotically with increasing stem diameters. It was unequal within the two species’ populations, and differed strongly between years to foster both spatial and temporal patchiness in seed rain. The M. bisulcata trees could begin seeding at 42–44 cm diameter: at a much larger size than could T. bifoliolata (25 cm). Nevertheless, per capita life-time reproductive capacity was c. five times greater in M. bisulcata than T. bifoliolata owing to former’s larger adult stature, lower mortality rate (despite a shorter life-time) and smaller seed mass. The two species displayed strong differences in their dispersal capabilities. Inverse modelling (IM) revealed that dispersal of M. bisulcata was best described by a lognormal kernel. Most seeds landed at 10–15 m from stems, with 1% of them going beyond 80 m (<100 m). The direct estimates of fecundity significantly improved the models fitted. The lognormal also described well the seedling recruitment distribution of this species in 121 ground plots. By contrast, the lower intensity of masting and more limited dispersal of the heavier-seeded T. bifoliolata prevented reliable IM. For this species, seed density as function of distance to traps suggested a maximum dispersal distance of 40–50 m, and a correspondingly more aggregated seedling recruitment pattern ensued than for M. bisulcata. From this integrated field study, we conclude that the reproductive traits of M. bisulcata give it a considerable advantage over T. bifoliolata by better dispersing more seeds per capita to reach more suitable establishment sites, and combined with other key traits they explain its local dominance in the forest. Understanding the linkages between size at onset of maturity, individual fecundity, and dispersal capability can better inform the life-history strategies, and hence management, of co-occurring tree species in tropical forests.

Plotting regression coefficients and other estimates

Graphical display of regression results has become increasingly popular in presentations and in scientific literature because graphs are often much easier to read than tables. Such plots can be produced in Stata by the marginsplot command (see [R] marginsplot). However, while marginsplot is versatile and flexible, it has two major limitations: it can only process results left behind by margins (see [R] margins), and it can handle only one set of results at a time. In this article, I introduce a new command called coefplot that overcomes these limitations. It plots results from any estimation command and combines results from several models into one graph. The default behavior of coefplot is to plot markers for coefficients and horizontal spikes for confidence intervals. However, coefplot can also produce other types of graphs. I illustrate the capabilities of coefplot by using a series of examples.

Eigenvalue estimates for non-selfadjoint Dirac operators on the real line

We show that the non-embedded eigenvalues of the Dirac operator on the real line with complex mass and non-Hermitian potential V lie in the disjoint union of two disks, provided that the L1-norm of V is bounded from above by the speed of light times the reduced Planck constant. The result is sharp; moreover, the analogous sharp result for the Schrödinger operator, originally proved by Abramov, Aslanyan and Davies, emerges in the nonrelativistic limit. For massless Dirac operators, the condition on V implies the absence of non-real eigenvalues. Our results are further generalized to potentials with slower decay at infinity. As an application, we determine bounds on resonances and embedded eigenvalues of Dirac operators with Hermitian dilation-analytic potentials.

Making regression tables from stored estimates

Organizing and archiving statistical results and processing a subset of those results for publication are important and often underestimated issues in conducting statistical analyses. Because automation of these tasks is often poor, processing results produced by statistical packages is quite laborious and vulnerable to error. I will therefore present a new package called estout that facilitates and automates some of these tasks. This new command can be used to produce regression tables for use with spreadsheets, LaTeX, HTML, or word processors. For example, the results for multiple models can be organized in spreadsheets and can thus be archived in an orderly manner. Alternatively, the results can be directly saved as a publication-ready table for inclusion in, for example, a LaTeX document. estout is implemented as a wrapper for estimates table but has many additional features, such as support for mfx. However, despite its flexibility, estout is—I believe—still very straightforward and easy to use. Furthermore, estout can be customized via so-called defaults files. A tool to make available supplementary statistics called estadd is also provided.

Time Variable Gravity: Contributions of GOCE Satellite Data to Monthly and Bi-monthly GRACE Gravity Estimates

A feasibility study by Pail et al. (Can GOCE help to improve temporal gravity field estimates? In: Ouwehand L (ed) Proceedings of the 4th International GOCE User Workshop, ESA Publication SP-696, 2011b) shows that GOCE (‘Gravity field and steady-state Ocean Circulation Explorer’) satellite gravity gradiometer (SGG) data in combination with GPS derived orbit data (satellite-to-satellite tracking: SST-hl) can be used to stabilize and reduce the striping pattern of a bi-monthly GRACE (‘Gravity Recovery and Climate Experiment’) gravity field estimate. In this study several monthly (and bi-monthly) combinations of GRACE with GOCE SGG and GOCE SST-hl data on the basis of normal equations are investigated. Our aim is to assess the role of the gradients (solely) in the combination and whether already one month of GOCE observations provides sufficient data for having an impact in the combination. The estimation of clean and stable monthly GOCE SGG normal equations at high resolution ( >  d/o 150) is found to be difficult, and the SGG component, solely, does not show significant added value to monthly and bi-monthly GRACE gravity fields. Comparisons of GRACE-only and combined monthly and bi-monthly solutions show that the striping pattern can only be reduced when using both GOCE observation types (SGG, SST-hl), and mainly between d/o 45 and 60.

Pollen dispersal properties of Poaceae and Cyperaceae: First estimates of their absolute pollen productivities

Pollen-trap results from the Swiss Alps 1996–2009 were used to assess the pollen dispersal–deposition properties of Poaceae (grasses) and Cyperaceae (sedges). Dispersal parameter values were investigated for a modified version of the Prentice–Sugita pollen dispersal–deposition model. Appropriate values (i.e. realistic in the field and allowing realistic modelling results) for wind speed are suggested to be in the range of 3–7 m s− 1 and for pollen an injection height of 0.03–0.1 m above the ground. The appropriate range of pollen injection height values for grasses and sedges differs from that of trees in the same area, suggesting different pollen dispersal properties between herbs and trees. In addition, logarithmic weighting of the vegetation was tested as an alternative to the modified Prentice–Sugita model. This yielded very similar results, suggesting that the use of such much simpler approximations of the pollen–vegetation relationship is a plausible alternative. Based on the modified Prentice–Sugita model, absolute pollen productivity for Poaceae was estimated to 7300 ± 400 grains cm− 2 year− 1 (1 SE). The data basis for Cyperaceae is smaller than for Poaceae, but the dispersal parameter values determined as appropriate for Poaceae yield good results. Absolute pollen productivity for Cyperaceae was estimated to 6300 ± 1100 grains cm− 2 year− 1 (1 SE).