Climate change amplified the 2009 extreme landslide event in Austria.

Landslides are an important natural hazard in mountainous regions. Given the triggering and preconditioning by meteorological conditions, it is known that landslide risk may change in a warming climate, but whether climate change has already affected individual landslide events is still an open question, partly owing to landslide data limitations and methodological challenges in climate impact attribution. Here, we demonstrate the substantial influence of anthropogenic climate change on a severe event in the southeastern Alpine forelands with some estimated 952 individual landslides in June 2009. Our study is based on conditional event attribution complemented by an assessment of changes in atmospheric circulation. Using this approach, we simulate the meteorological event under observed and a range of counterfactual conditions of no climate change and explicitly predict the landslide occurrence probability for these conditions. We find that up to 10%, i.e., 95 landslides, can be attributed to climate change.

Central Mongolian lake sediments reveal new insights on climate change and equestrian empires in the Eastern Steppes.

The repeated expansion of East Asian steppe cultures was a key driver of Eurasian history, forging new social, economic, and biological links across the continent. Climate has been suggested as important driver of these poorly understood cultural expansions, but paleoclimate records from the Mongolian Plateau often suffer from poor age control or ambiguous proxy interpretation. Here, we use a combination of geochemical analyses and comprehensive radiocarbon dating to establish the first robust and detailed record of paleohydrological conditions for Lake Telmen, Mongolia, covering the past ~ 4000 years. Our record shows that humid conditions coincided with solar minima, and hydrological modeling confirms the high sensitivity of the lake to paleoclimate changes. Careful comparisons with archaeological and historical records suggest that in the vast semi-arid grasslands of eastern Eurasia, solar minima led to reduced temperatures, less evaporation, and high biomass production, expanding the power base for pastoral economies and horse cavalry. Our findings suggest a crucial link between temperature dynamics in the Eastern Steppe and key social developments, such as the emergence of pastoral empires, and fuel concerns that global warming enhances water scarcity in the semi-arid regions of interior Eurasia.

Estimating error rates in the classification of paired organs.

Clinical data from paired organs present a dependence structure that has to be considered when making statistical inference or evaluating classification rules with resampling-based techniques (bootstrap, cross-validation). We introduce a paired cross-validation approach for the estimation of misclassification error rates in the classification of data from paired organs. The dependence structure of the sample is honored by subject-level cross-validation. Theoretical considerations as well as a case-control study on glaucoma diagnosis and a simulation study show that the variance of the paired cross-validation estimator is considerably lower than in traditional cross-validation error estimation on one randomly selected eye per subject. The actual variance reduction is mainly controlled by the contribution of differential misclassification between both eyes to the overall error rate. By contrast, 'ad hoc' cross-validation ignoring the autocorrelation of paired organs leads to biased error estimates. Using the double-bagging technique, we also show that classification accuracy can be improved by using information from both eyes in training machine-learning classifiers. In glaucoma detection, the reduction in misclassification error rates by training data from both eyes is equivalent to an increase in the sample size by one-third to one-half, which is an important achievement in clinical studies.

Glaucoma detection with frequency doubling perimetry and short-wavelength perimetry.

PURPOSE: The aim of this analysis was to evaluate the diagnostic usefulness of frequency doubling technology (FDT) perimetry and short-wavelength perimetry (SWAP). Moreover, to study a combination of both methods using the machine-learning technique double-bagging, which was recently established in glaucoma research. METHODS: Forty-three patients with "preperimetric" open-angle glaucoma (glaucomatous optic disc atrophy and no visual field defect in standard perimetry), 26 patients with "perimetric" open angle glaucoma (glaucomatous optic disc atrophy and visual field defect in standard perimetry), and 40 control subjects had FDT screening (protocol: C-20-5) and SWAP (Octopus 101, G2). Criteria for exclusion were color vision abnormalities, media opacities, and an age below 31 years or above 63 years. Data of 1 eye of each patient and control subject entered the statistical evaluation. A point wise evaluation of the diagnostic power of SWAP values was performed to derive spatial patterns of visual field loss. A double-bagging machine-learning algorithm was used to train classification rules on the basis of a combination of FDT scores and nerve fiber related visual field losses in SWAP. The diagnostic power of the classifiers was compared regarding their misclassification error rates and area under the receiver-operating characteristic curve. RESULTS: The combination of FDT perimetry and SWAP yielded better diagnostic results compared with FDT or SWAP separately. The overall estimated misclassification error rate of the combined classifier was 24% compared with 28% for both SWAP and FDT perimetry. Regarding the estimated performance of classifier at high specificities (>80%) in control eyes as measured by the partial area under the receiver-operating characteristic curve, the combination of both instruments is also superior to the individual instruments. CONCLUSIONS: A combination of SWAP and FDT perimetry, each targeting different neuronal pathways, may improve early glaucoma detection.

Pupillographic measurements with pattern stimulation: the pupil's response in normal subjects and first measurements in glaucoma patients.

PURPOSE: This study was undertaken to characterize the influence of contrast, luminance, and spatial frequency of a pattern stimulus on the pupil reaction of healthy subjects. First measurements with this technique in patients with glaucoma were compared with those in a control group. METHOD: Grating patterns were presented using a Maxwellian-view system to study series of contrast, luminance, and spatial frequency in three healthy subjects. The best two stimulus conditions were determined and were then used to examine 19 patients with open-angle glaucoma and 16 control subjects. RESULTS: In healthy subjects, an increasing contrast led to an increase in amplitude and a decrease in latency of the pupil reflex. Increasing luminance also resulted in an increase in the amplitude. The offset component of the pupil reflex was most pronounced at low spatial frequencies and the onset component at high spatial frequencies. When healthy subjects were compared with patients with glaucoma, control subjects generally had higher amplitudes, velocity, and acceleration of pupil constriction than did the patients with glaucoma. These differences were significant when the test was performed with a spatial frequency of 6.25 cyc/deg. CONCLUSIONS: Best stimulus conditions to elicit a pupil response to a pattern grating stimulus are 100% contrast and 55 cd/m(2) mean luminance. The choice of the spatial frequency determines which component of the pupil reflex is more pronounced. Differences between patients with glaucoma and healthy control subjects are demonstrable.