Meta-studies in land use science: Current coverage and prospects

Land use science has traditionally used case-study approaches for in-depth investigation of land use change processes and impacts. Meta-studies synthesize findings across case-study evidence to identify general patterns. In this paper, we provide a review of meta-studies in land use science. Various meta-studies have been conducted, which synthesize deforestation and agricultural land use change processes, while other important changes, such as urbanization, wetland conversion, and grassland dynamics have hardly been addressed. Meta-studies of land use change impacts focus mostly on biodiversity and biogeochemical cycles, while meta-studies of socioeconomic consequences are rare. Land use change processes and land use change impacts are generally addressed in isolation, while only few studies considered trajectories of drivers through changes to their impacts and their potential feedbacks. We provide a conceptual framework for linking meta-studies of land use change processes and impacts for the analysis of coupled human–environmental systems. Moreover, we provide suggestions for combining meta-studies of different land use change processes to develop a more integrated theory of land use change, and for combining meta-studies of land use change impacts to identify tradeoffs between different impacts. Land use science can benefit from an improved conceptualization of land use change processes and their impacts, and from new methods that combine meta-study findings to advance our understanding of human–environmental systems.

First continuous ground-based observations of long period oscillations in strato-/mesospheric wind profiles

Direct measurements of middle-atmospheric wind oscillations with periods between 5 and 50 days in the altitude range between mid-stratosphere (5 hPa) and upper mesosphere (0.02 hPa) have been made using a novel ground-based Doppler wind radiometer. The oscillations were not inferred from measurements of tracers, as the radiometer offers the unique capability of near-continuous horizontal wind profile measurements. Observations from four campaigns at high, mid and low latitudes with an average duration of 10 months have been analyzed. The dominant oscillation has mostly been found to lie in the extra-long period range (20–40 days), while the well-known atmospheric normal modes around 5, 10 and 16 days have also been observed. Comparisons of our results with ECMWF operational analysis model data revealed remarkably good agreement below 0.3 hPa but discrepancies above.

A changing climate of skepticism: The factors shaping climate change coverage in the US press

Skepticism toward climate change has a long tradition in the United States. We focus on mass media as the conveyors of the image of climate change and ask: Is climate change skepticism still a characteristic of US print media coverage? If so, to what degree and in what form? And which factors might pave the way for skeptics entering mass media debates? We conducted a quantitative content analysis of US print media during one year (1 June 2012 to 31 May 2013). Our results show that the debate has changed: fundamental forms of climate change skepticism (such as denial of anthropogenic causes) have been abandoned in the coverage, being replaced by more subtle forms (such as the goal to avoid binding regulations). We find no evidence for the norm of journalistic balance, nor do our data support the idea that it is the conservative press that boosts skepticism.

Comparison of 2.5D and 3D Quantification of Femoral Head Coverage in Normal Control Subjects and Patients with Hip Dysplasia.

Hip dysplasia is characterized by insufficient femoral head coverage (FHC). Quantification of FHC is of importance as the underlying goal of the surgery to treat hip dysplasia is to restore a normal acetabular morphology and thereby to improve FHC. Unlike a pure 2D X-ray radiograph-based measurement method or a pure 3D CT-based measurement method, previously we presented a 2.5D method to quantify FHC from a single anteriorposterior (AP) pelvic radiograph. In this study, we first quantified and compared 3D FHC between a normal control group and a patient group using a CT-based measurement method. Taking the CT-based 3D measurements of FHC as the gold standard, we further quantified the bias, precision and correlation between the 2.5D measurements and the 3D measurements on both the control group and the patient group. Based on digitally reconstructed radiographs (DRRs), we investigated the influence of the pelvic tilt on the 2.5D measurements of FHC. The intraclass correlation coefficients (ICCs) for absolute agreement was used to quantify interobserver reliability and intraobserver reproducibility of the 2.5D measurement technique. The Pearson correlation coefficient, r, was used to determine the strength of the linear association between the 2.5D and the 3D measurements. Student's t-test was used to determine whether the differences between different measurements were statistically significant. Our experimental results demonstrated that both the interobserver reliability and the intraobserver reproducibility of the 2.5D measurement technique were very good (ICCs > 0.8). Regression analysis indicated that the correlation was very strong between the 2.5D and the 3D measurements (r = 0.89, p < 0.001). Student's t-test showed that there were no statistically significant differences between the 2.5D and the 3D measurements of FHC on the patient group (p > 0.05). The results of this study provided convincing evidence demonstrating the validity of the 2.5D measurements of FHC from a single AP pelvic radiograph and proved that it could serve as a surrogate for 3D CT-based measurements. Thus it may be possible to use this method to avoid a CT scan for the purpose of estimating 3D FHC in diagnosis and post-operative treatment evaluation of patients with hip dysplasia.

Computational Comparison of Continuous and Discontinuous Galerkin Time-Stepping Methods for Nonlinear Initial Value Problems

This article centers on the computational performance of the continuous and discontinuous Galerkin time stepping schemes for general first-order initial value problems in R n , with continuous nonlinearities. We briefly review a recent existence result for discrete solutions from [6], and provide a numerical comparison of the two time discretization methods.

Structural Organization of the Corpus Callosum Predicts Attentional Shifts after Continuous Theta Burst Stimulation

Repetitive transcranial magnetic stimulation (rTMS) applied over the right posterior parietal cortex (PPC) in healthy participants has been shown to trigger a significant rightward shift in the spatial allocation of visual attention, temporarily mimicking spatial deficits observed in neglect. In contrast, rTMS applied over the left PPC triggers a weaker or null attentional shift. However, large interindividual differences in responses to rTMS have been reported. Studies measuring changes in brain activation suggest that the effects of rTMS may depend on both interhemispheric and intrahemispheric interactions between cortical loci controlling visual attention. Here, we investigated whether variability in the structural organization of human white matter pathways subserving visual attention, as assessed by diffusion magnetic resonance imaging and tractography, could explain interindividual differences in the effects of rTMS. Most participants showed a rightward shift in the allocation of spatial attention after rTMS over the right intraparietal sulcus (IPS), but the size of this effect varied largely across participants. Conversely, rTMS over the left IPS resulted in strikingly opposed individual responses, with some participants responding with rightward and some with leftward attentional shifts. We demonstrate that microstructural and macrostructural variability within the corpus callosum, consistent with differential effects on cross-hemispheric interactions, predicts both the extent and the direction of the response to rTMS. Together, our findings suggest that the corpus callosum may have a dual inhibitory and excitatory function in maintaining the interhemispheric dynamics that underlie the allocation of spatial attention. SIGNIFICANCE STATEMENT: The posterior parietal cortex (PPC) controls allocation of attention across left versus right visual fields. Damage to this area results in neglect, characterized by a lack of spatial awareness of the side of space contralateral to the brain injury. Transcranial magnetic stimulation over the PPC is used to study cognitive mechanisms of spatial attention and to examine the potential of this technique to treat neglect. However, large individual differences in behavioral responses to stimulation have been reported. We demonstrate that the variability in the structural organization of the corpus callosum accounts for these differences. Our findings suggest novel dual mechanism of the corpus callosum function in spatial attention and have broader implications for the use of stimulation in neglect rehabilitation.

Accuracy of continuous glucose monitoring during differing exercise conditions.

AIM Depending on intensity, exercise may induce a strong hormonal and metabolic response, including acid-base imbalances and changes in microcirculation, potentially interfering with the accuracy of continuous glucose monitoring (CGM). The present study aimed at comparing the accuracy of the Dexcom G4 Platinum (DG4P) CGM during continuous moderate and intermittent high-intensity exercise (IHE) in adults with type 1 diabetes (T1DM). METHODS Ten male individuals with well-controlled T1DM (HbA1c 7.0±0.6% [54±6mmol/mol]) inserted the DG4P sensor 2 days prior to a 90min cycling session (50% VO2peak) either with (IHE) or without (CONT) a 10s all-out sprint every 10min. Venous blood samples for reference glucose measurement were drawn every 10min and euglycemia (target 7mmol/l) was maintained using an oral glucose solution. Additionally, lactate and venous blood gas variables were determined. RESULTS Mean reference blood glucose was 7.6±0.2mmol/l during IHE and 6.7±0.2mmol/l during CONT (p<0.001). IHE resulted in significantly higher levels of lactate (7.3±0.5mmol/l vs. 2.6±0.3mmol/l, p<0.001), while pH values were significantly lower in the IHE group (7.27 vs. 7.38, p=0.001). Mean absolute relative difference (MARD) was 13.3±2.2% for IHE and 13.6±2.8% for CONT suggesting comparable accuracy (p=0.90). Using Clarke Error Grid Analysis, 100% of CGM values during both IHE and CONT were in zones A and B (IHE: 77% and 23%; CONT: 78% and 22%). CONCLUSIONS The present study revealed good and comparable accuracy of the DG4P CGM system during intermittent high intensity and continuous moderate intensity exercise, despite marked differences in metabolic conditions. This corroborates the clinical robustness of CGM under differing exercise conditions. CLINICAL TRIAL REGISTRATION NUMBER ClinicalTrials.gov NCT02068638.

Cerebral Gaseous Microemboli are Detectable During Continuous Venovenous Hemodialysis in Critically Ill Patients: An Observational Pilot Study

BACKGROUND Continuous venovenous hemodialysis (CVVHD) may generate microemboli that cross the pulmonary circulation and reach the brain. The aim of the present study was to quantify (load per time interval) and qualify (gaseous vs. solid) cerebral microemboli (CME), detected as high-intensity transient signals, using transcranial Doppler ultrasound. MATERIALS AND METHODS Twenty intensive care unit (ICU group) patients requiring CVVHD were examined. CME were recorded in both middle cerebral arteries for 30 minutes during CVVHD and a CVVHD-free interval. Twenty additional patients, hospitalized for orthopedic surgery, served as a non-ICU control group. Statistical analyses were performed using the Mann-Whitney U test or the Wilcoxon matched-pairs signed-rank test, followed by Bonferroni corrections for multiple comparisons. RESULTS In the non-ICU group, 48 (14.5-169.5) (median [range]) gaseous CME were detected. In the ICU group, the 67.5 (14.5-588.5) gaseous CME detected during the CVVHD-free interval increased 5-fold to 344.5 (59-1019) during CVVHD (P<0.001). The number of solid CME was low in all groups (non-ICU group: 2 [0-5.5]; ICU group CVVHD-free interval: 1.5 [0-14.25]; ICU group during CVVHD: 7 [3-27.75]). CONCLUSIONS This observational pilot study shows that CVVHD was associated with a higher gaseous but not solid CME burden in critically ill patients. Although the differentiation between gaseous and solid CME remains challenging, our finding may support the hypothesis of microbubble generation in the CVVHD circuit and its transpulmonary translocation toward the intracranial circulation. Importantly, the impact of gaseous and solid CME generated during CVVHD on brain integrity of critically ill patients currently remains unknown and is highly debated.

Metabolic and hormonal response to intermittent high-intensity and continuous moderate intensity exercise in individuals with type 1 diabetes: a randomised crossover study.

AIMS/HYPOTHESIS To investigate exercise-related fuel metabolism in intermittent high-intensity (IHE) and continuous moderate intensity (CONT) exercise in individuals with type 1 diabetes mellitus. METHODS In a prospective randomised open-label cross-over trial twelve male individuals with well-controlled type 1 diabetes underwent a 90 min iso-energetic cycling session at 50% maximal oxygen consumption ([Formula: see text]), with (IHE) or without (CONT) interspersed 10 s sprints every 10 min without insulin adaptation. Euglycaemia was maintained using oral (13)C-labelled glucose. (13)C Magnetic resonance spectroscopy (MRS) served to quantify hepatocellular and intramyocellular glycogen. Measurements of glucose kinetics (stable isotopes), hormones and metabolites complemented the investigation. RESULTS Glucose and insulin levels were comparable between interventions. Exogenous glucose requirements during the last 30 min of exercise were significantly lower in IHE (p = 0.02). Hepatic glucose output did not differ significantly between interventions, but glucose disposal was significantly lower in IHE (p < 0.05). There was no significant difference in glycogen consumption. Growth hormone, catecholamine and lactate levels were significantly higher in IHE (p < 0.05). CONCLUSIONS/INTERPRETATION IHE in individuals with type 1 diabetes without insulin adaptation reduced exogenous glucose requirements compared with CONT. The difference was not related to increased hepatic glucose output, nor to enhanced muscle glycogen utilisation, but to decreased glucose uptake. The lower glucose disposal in IHE implies a shift towards consumption of alternative substrates. These findings indicate a high flexibility of exercise-related fuel metabolism in type 1 diabetes, and point towards a novel and potentially beneficial role of IHE in these individuals. TRIAL REGISTRATION ClinicalTrials.gov NCT02068638 FUNDING: Swiss National Science Foundation (grant number 320030_149321/) and R&A Scherbarth Foundation (Switzerland).

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

Validation of a Spatially Continuous EDEN Water-Surface Model for the Everglades, Florida

The Everglades Depth Estimation Network (EDEN) is an integrated network of realtime water-level monitoring, ground-elevation modeling, and water-surface modeling that provides scientists and managers with current (2000-present), online water-stage and water-depth information for the entire freshwater portion of the Greater Everglades. Continuous daily spatial interpolations of the EDEN network stage data are presented on grid with 400-square-meter spacing. EDEN offers a consistent and documented dataset that can be used by scientists and managers to: (1) guide large-scale field operations, (2) integrate hydrologic and ecological responses, and (3) support biological and ecological assessments that measure ecosystem responses to the implementation of the Comprehensive Everglades Restoration Plan (CERP) (U.S. Army Corps of Engineers, 1999). The target users are biologists and ecologists examining trophic level responses to hydrodynamic changes in the Everglades. The first objective of this report is to validate the spatially continuous EDEN water-surface model for the Everglades, Florida developed by Pearlstine et al. (2007) by using an independent field-measured data-set. The second objective is to demonstrate two applications of the EDEN water-surface model: to estimate site-specific ground elevation by using the validated EDEN water-surface model and observed water depth data; and to create water-depth hydrographs for tree islands. We found that there are no statistically significant differences between model-predicted and field-observed water-stage data in both southern Water Conservation Area (WCA) 3A and WCA 3B. Tree island elevations were derived by subtracting field water-depth measurements from the predicted EDEN water-surface. Water-depth hydrographs were then computed by subtracting tree island elevations from the EDEN water stage. Overall, the model is reliable by a root mean square error (RMSE) of 3.31 cm. By region, the RMSE is 2.49 cm and 7.77 cm in WCA 3A and 3B, respectively. This new landscape-scale hydrological model has wide applications for ongoing research and management efforts that are vital to restoration of the Florida Everglades. The accurate, high-resolution hydrological data, generated over broad spatial and temporal scales by the EDEN model, provides a previously missing key to understanding the habitat requirements and linkages among native and invasive populations, including fish, wildlife, wading birds, and plants. The EDEN model is a powerful tool that could be adapted for other ecosystem-scale restoration and management programs worldwide.

The Aggregate Demand for Private Health Insurance Coverage in the U.S.

This paper estimates the aggregate demand for private health insurance coverage in the U.S. using an error-correction model and by recognizing that people are without private health insurance for voluntary, structural, frictional, and cyclical reasons and because of public alternatives. Insurance coverage is measured both by the percentage of the population enrolled in private health insurance plans and the completeness of the insurance coverage. Annual data for the period 1966-1999 are used and both short and long run price and income elasticities of demand are estimated. The empirical findings indicate that both private insurance enrollment and completeness are relatively inelastic with respect to changes in price and income in the short and long run. Moreover, private health insurance enrollment is found to be inversely related to the poverty rate, particularly in the short-run. Finally, our results suggest that an increase in the number cyclically uninsured generates less of a welfare loss than an increase in the structurally uninsured.