Remote thermal detection of exfoliation sheet deformation.

A growing body of research indicates that rock slope failures, particularly from exfoliating cliffs, are promoted by rock deformations induced by daily temperature cycles. Although previous research has described how these deformations occur, full three-dimensional monitoring of both the deformations and the associated temperature changes has not yet been performed. Here we use integrated terrestrial laser scanning (TLS) and infrared thermography (IRT) techniques to monitor daily deformations of two granitic exfoliating cliffs in Yosemite National Park (CA, USA). At one cliff, we employed TLS and IRT in conjunction with in situ instrumentation to confirm previously documented behavior of an exfoliated rock sheet, which experiences daily closing and opening of the exfoliation fracture during rock cooling and heating, respectively, with a few hours delay from the minimum and maximum temperatures. The most deformed portion of the sheet coincides with the area where both the fracture aperture and the temperature variations are greatest. With the general deformation and temperature relations established, we then employed IRT at a second cliff, where we remotely detected and identified 11 exfoliation sheets that displayed those general thermal relations. TLS measurements then subsequently confirmed the deformation patterns of these sheets showing that sheets with larger apertures are more likely to display larger thermal-related deformations. Our high-frequency monitoring shows how coupled TLS and IRT allows for remote detection of thermally induced deformations and, importantly, how IRT could potentially be used on its own to identify partially detached exfoliation sheets capable of large-scale deformation. These results offer a new and efficient approach for investigating potential rockfall sources on exfoliating cliffs.

The three-stage rock failure dynamics of the Drus (Mont Blanc massif, France) since the June 2005 large event.

Since the end of the Little Ice Age, the west face of the Drus (Mont Blanc massif, France) has been affected by a retrogressive erosion dynamic marked by large rockfall events. From the 1950s onwards, the rock failure frequency gradually increased until the large rockfall event (292,680 m3) of June 2005, which made the Bonatti Pillar disappear. Aiming to characterize the rock failure activity following this major event, which may be related to permafrost warming, the granitic rock face was scanned each autumn between October 2005 and September 2016 using medium- and long-range terrestrial laser scanners. All the point clouds were successively compared to establish a rockfall source inventory and determine a volume-frequency relationship. Eleven years of monitoring revealed a phase of rock failure activity decay until September 2008, a destabilization phase between September 2008 and November 2011, and a new phase of rock failure activity decay from November 2011 to September 2016. The destabilization phase was marked by three major rockfall events covering a total volume of 61,494 m3, resulting in the progressive collapse of a new pillar located in the northern part of the June 2005 rockfall scar. In the same way as for the Bonatti Pillar, rock failure instability propagated upward with increasing volumes. In addition to these major events, 304 rockfall sources ranging from 0.002 to 476 m3 were detected between 2005 and 2016. The temporal evolution of rock failure activity reveals that after a major event, the number of rockfall sources and the eroded volume both follow a rapid decrease. The rock failure activity is characterized by an exponential decay during the period following the major event and by a power-law decay for the eroded volume. The power law describing the distribution of the source volumes detected between 2005 and 2016 indicates an exponent of 0.48 and an average rock failure activity larger of more than six events larger than 1 m3 per year. Over the 1905-2016 period, a total of 426,611 m3 of rock collapsed from the Drus west face, indicating a very high rock wall retreat rate of 14.4 mm year-1 over a surface of 266,700 m2. Averaged over a time window of 1000 years, the long-term retreat rate derived from the frequency density integration of rock failure volumes is 2.9 mm year-1. Despite difficulty in accessing and monitoring the site, our study demonstrates that long-term surveys of high-elevation rock faces are possible and provide valuable information that helps improve our understanding of landscape evolution in mountainous settings subject to permafrost warming.

Toward community predictions: Multi-scale modelling of mountain breeding birds' habitat suitability, landscape preferences, and environmental drivers.

Across a large mountain area of the western Swiss Alps, we used occurrence data (presence-only points) of bird species to find suitable modelling solutions and build reliable distribution maps to deal with biodiversity and conservation necessities of bird species at finer scales. We have performed a multi-scale method of modelling, which uses distance, climatic, and focal variables at different scales (neighboring window sizes), to estimate the efficient scale of each environmental predictor and enhance our knowledge on how birds interact with their complex environment. To identify the best radius for each focal variable and the most efficient impact scale of each predictor, we have fitted univariate models per species. In the last step, the final set of variables were subsequently employed to build ensemble of small models (ESMs) at a fine spatial resolution of 100 m and generate species distribution maps as tools of conservation. We could build useful habitat suitability models for the three groups of species in the national red list. Our results indicate that, in general, the most important variables were in the group of bioclimatic variables including "Bio11" (Mean Temperature of Coldest Quarter), and "Bio 4" (Temperature Seasonality), then in the focal variables including "Forest", "Orchard", and "Agriculture area" as potential foraging, feeding and nesting sites. Our distribution maps are useful for identifying the most threatened species and their habitat and also for improving conservation effort to locate bird hotspots. It is a powerful strategy to improve the ecological understanding of the distribution of bird species in a dynamic heterogeneous environment.

Detection of rock bridges by infrared thermal imaging and modeling.

Characterization of rock discontinuities and rock bridges is required to define stability conditions of fractured rock masses in both natural and engineered environments. Although remote sensing methods for mapping discontinuities have improved in recent years, remote detection of intact rock bridges on cliff faces remains challenging, with their existence typically confirmed only after failure. In steep exfoliating cliffs, such as El Capitan in Yosemite Valley (California, USA), rockfalls mainly occur along cliff-parallel exfoliation joints, with rock bridges playing a key role in the stability of partially detached exfoliation sheets. We employed infrared thermal imaging (i.e., thermography) as a new means of detecting intact rock bridges prior to failure. An infrared thermal panorama of El Capitan revealed cold thermal signatures for the surfaces of two granitic exfoliation sheets, consistent with the expectation that air circulation cools the back of the partially detached sheets. However, we also noted small areas of warm thermal anomalies on these same sheets, even during periods of nocturnal rock cooling. Rock attachment via rock bridges is the likely cause for the warm anomalies in the thermal data. 2-D model simulations of the thermal behavior of one of  the monitored sheets reproduce the observed anomalies and explain the temperature differences detected in the rock bridge area. Based on combined thermal and ground-based lidar imaging, and using geometric and rock fracture mechanics analysis, we are able to quantify the stability of both sheets. Our analysis demonstrates that thermography can remotely detect intact rock bridges and thereby greatly improve rockfall hazard assessment.

Cratering response during droplet impacts on granular beds.

This experimental work focuses on the cratering response of granular layers induced by liquid droplet impacts. A droplet impact results in severe granular layer deformation, crater formation and deposits in the vicinity of the impact center. High-precision three-dimensional imaging of the granular layer surface revealed important characteristics of liquid impacts on granular matter, such as singular asymmetric deformations of the layer. Our analysis also demonstrated that the impact energy and the granular packing, and its inherent compressibility, are not the unique parameters controlling the bed response, for which granular fraction heterogeneities may induce strong variations. Such heterogeneous conditions primarily influence the magnitude but not the dynamics of liquid impacts on granular layers. Finally, a general equation can be used to relate the enery released during cratering to both the impact energy and the compressibility of the granular matter. However, our results do not support any transition triggered by the compaction-dilation regime. Hence, higly detailed numerical simulations could provide considerable insights regarding the remaining questions related to heterogeneous packing conditions and its influence over the bulk compressibility and the compaction-dilation phase transition.

Low number of fixed somatic mutations in a long-lived oak tree.

Because plants do not possess a defined germline, deleterious somatic mutations can be passed to gametes, and a large number of cell divisions separating zygote from gamete formation may lead to many mutations in long-lived plants. We sequenced the genome of two terminal branches of a 234-year-old oak tree and found several fixed somatic single-nucleotide variants whose sequential appearance in the tree could be traced along nested sectors of younger branches. Our data suggest that stem cells of shoot meristems in trees are robustly protected from the accumulation of mutations.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland.

PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

Major influencing factors of indoor radon concentrations in Switzerland.

PURPOSE: In Switzerland, nationwide large-scale radon surveys have been conducted since the early 1980s to establish the distribution of indoor radon concentrations (IRC). The aim of this work was to study the factors influencing IRC in Switzerland using univariate analyses that take into account biases caused by spatial irregularities of sampling. METHODS: About 212,000 IRC measurements carried out in more than 136,000 dwellings were available for this study. A probability map to assess risk of exceeding an IRC of 300 Bq/m(3) was produced using basic geostatistical techniques. Univariate analyses of IRC for different variables, namely the type of radon detector, various building characteristics such as foundation type, year of construction and building type, as well as the altitude, the average outdoor temperature during measurement and the lithology, were performed comparing 95% confidence intervals among classes of each variable. Furthermore, a map showing the spatial aggregation of the number of measurements was generated for each class of variable in order to assess biases due to spatially irregular sampling. RESULTS: IRC measurements carried out with electret detectors were 35% higher than measurements performed with track detectors. Regarding building characteristics, the IRC of apartments are significantly lower than individual houses. Furthermore, buildings with concrete foundations have the lowest IRC. A significant decrease in IRC was found in buildings constructed after 1900 and again after 1970. Moreover, IRC decreases at higher outdoor temperatures. There is also a tendency to have higher IRC with altitude. Regarding lithology, carbonate rock in the Jura Mountains produces significantly higher IRC, almost by a factor of 2, than carbonate rock in the Alps. Sedimentary rock and sediment produce the lowest IRC while carbonate rock from the Jura Mountains and igneous rock produce the highest IRC. Potential biases due to spatially unbalanced sampling of measurements were identified for several influencing factors. CONCLUSIONS: Significant associations were found between IRC and all variables under study. However, we showed that the spatial distribution of samples strongly affected the relevance of those associations. Therefore, future methods to estimate local radon hazards should take the multidimensionality of the process of IRC into account.