Empirical species distribution models (SDMs) constitute often the tool of choice for the assessment of rapid climate change effects on species vulnerability. Conclusions regarding extinction risks might be misleading, however, because SDMs do not explicitly incorporate dispersal or other demographic processes. Here, we supplement SDMs with a dynamic population model 1) to predict climate-induced range dynamics for black grouse in Switzerland, 2) to compare direct and indirect measures of extinction risks, and 3) to quantify uncertainty in predictions as well as the sources of that uncertainty. To this end, we linked models of habitat suitability to a spatially explicit, individual-based model. In an extensive sensitivity analysis, we quantified uncertainty in various model outputs introduced by different SDM algorithms, by different climate scenarios and by demographic model parameters. Potentially suitable habitats were predicted to shift uphill and eastwards. By the end of the 21st century, abrupt habitat losses were predicted in the western Prealps for some climate scenarios. In contrast, population size and occupied area were primarily controlled by currently negative population growth and gradually declined from the beginning of the century across all climate scenarios and SDM algorithms. However, predictions of population dynamic features were highly variable across simulations. Results indicate that inferring extinction probabilities simply from the quantity of suitable habitat may underestimate extinction risks because this may ignore important interactions between life history traits and available habitat. Also, in dynamic range predictions uncertainty in SDM algorithms and climate scenarios can become secondary to uncertainty in dynamic model components. Our study emphasises the need for principal evaluation tools like sensitivity analysis in order to assess uncertainty and robustness in dynamic range predictions. A more direct benefit of such robustness analysis is an improved mechanistic understanding of dynamic species responses to climate change.

The Lombok Island is part of the Lesser Sunda Islands (LSI) region – Indonesia, situated along the Sunda-Banda Arcs transition. It lies between zones characterized by the highest intensity geomagnetic anomalies of this region, remarkable as one of the eight most important features provided on the 1st edition of World Digital Magnetic Anomaly Map. The seismicity of this region during the last years is high, while the geological and tectonic structures of this region are still not known in detail. Some local magnetic surveys have been conducted previously during 2004–2005. However, due to the lower accuracy of the used equipment and a limited number of stations, the qualities of the previous measurements are questionable for more interpretations. Thus a more detailed study to better characterize the geomagnetic anomaly -spatially and temporally- over this region and to deeply explore the related regional geology, tectonic and seismicity is needed. The intriguing geomagnetic anomalies over this island region vis-à-vis the socio-cultural situations lead to a study with a special aim to contribute to the assessment of the potential of natural hazards (earthquakes) as well as a new natural resource of energy (geothermal potential). This study is intended to discuss several crucial questions, including: i. The real values and the general pattern of magnetic anomalies over the island, as well as their relation to the regional one. ii. Any temporal changes of regional anomalies over the recent time. iii. The relationships between the anomalies and the geology and tectonic of this region, especially new insights that can be gained from the geomagnetic observations. iv. The relationships between the anomalies and the high seismicity of this region, especially some possible links between their variations to the earthquake occurrence. First, all available geomagnetic data of this region and results of the previous measurements are evaluated. The new geomagnetic surveys carried out in 2006 and 2007/2008 are then presented in detail, followed by the general description of data processing and data quality evaluation. The new results show the general pattern of contiguous negative-positive anomalies, revealing an active arc related subduction region. They agree with earlier results obtained by satellite, aeromagnetic, and marine platforms; and provide a much more detailed picture of the strong anomalies on this island. The temporal characteristics of regional anomalies show a decreasing strength of the dipolar structure, where decreasing of the field intensities is faster than the regional secular variations as defined by the global model (the 10th generation of IGRF). However, some exceptions (increasing of anomalies) have to be noted and further analyzed for several locations. Thereafter, simultaneous magnetic anomalies and gravity models are generated and interpreted in detail. Three profiles are investigated, providing new insights into the tectonics and geological evolution of the Lombok Island. Geological structure of this island can be divided as two main parts with different consecutive ages: an old part (from late Oligocene to late Miocene) in the South and a younger one (from Pliocene to Holocene) in the North. A new subduction in the back arc region (the Flores Thrust zone) is considered mature and active, showing a tendency of progressive subduction during 2005–2008. Geothermal potential in the northern part of this island can be mapped in more detail using these geomagnetic regional survey data. The earlier estimates of reservoir depth can be confirmed further to a depth of about 800 m. Evaluation of temporal changes of the anomalies gives some possible explanations related to the evolution of the back arc region, large stress accumulations over the LSI region, a specific electrical characteristic of the crust of the Lombok Island region, and a structural discontinuity over this island. Based on the results, several possible advanced studies involving geomagnetic data and anomaly investigations over the Lombok Island region can be suggested for the future: i. Monitoring the subduction activity of the back arc region (the Flores Thrust zone) and the accumulated stress over the LSI, that could contribute to middle term hazard assessment with a special attention to the earthquake occurrence in this region. Continuous geomagnetic field measurements from a geomagnetic observatory which can be established in the northern part of the Lombok Island and systematic measurements at several repeat stations can be useful in this regards. ii. Investigating the specific electrical characteristic (high conductivity) of the crust, that is probably related to some aquifer layers or metal mineralization. It needs other complementary geophysical methods, such as magnetotelluric (MT) or preferably DC resistivity measurements. iii. Determining the existence of an active structural fault over the Lombok Island, that could be related to long term hazard assessment over the LSI region. This needs an extension of geomagnetic investigations over the neighbouring islands (the Bali Island in the West and the Sumbawa Island in the East; probably also the Sumba and the Flores islands). This seems possible because the regional magnetic lineations might be used to delineate some structural discontinuities, based on the modelling of contrasts in crustal magnetizations.

The study presents the first evidence of metamorphosed submarine ashes in the Edough Massif, in northeastern Algeria. It occurs below the greenschist-facies Tellian units that represent the thrusted Mesozoic to Eocene passive paleomargin of northern Africa deposited on thinned continental crust. The metamorphic complex consists of tectonically superposed units composed of gneisses (lower unit) and micaschists (upper unit). At the Cap de Garde, these units enclose an "intermediate unit" composed of micaschists and meter-thick layers of marbles, which are sometimes intercalated with amphibolites. The latter occur as discontinuous small lenses and layers. The amphibolites are parallel to the primary bedding of the marbles and the main foliation. Chemical markers and field observations indicate that they are metamorphic equivalents of basic igneous rocks. The lenticular character, low thickness and multiple intercalations with marine sediments and the unusual high lithium concentrations suggest subaqueous near-source basaltic ash-fall deposits in a marine environment. (C) 2014 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

What is the most appropriate sampling scheme to estimate event-based average throughfall? A satisfactory answer to this seemingly simple question has yet to be found, a failure which we attribute to previous efforts' dependence on empirical studies. Here we try to answer this question by simulating stochastic throughfall fields based on parameters for statistical models of large monitoring data sets. We subsequently sampled these fields with different sampling designs and variable sample supports. We evaluated the performance of a particular sampling scheme with respect to the uncertainty of possible estimated means of throughfall volumes. Even for a relative error limit of 20%, an impractically large number of small, funnel-type collectors would be required to estimate mean throughfall, particularly for small events. While stratification of the target area is not superior to simple random sampling, cluster random sampling involves the risk of being less efficient. A larger sample support, e.g., the use of trough-type collectors, considerably reduces the necessary sample sizes and eliminates the sensitivity of the mean to outliers. Since the gain in time associated with the manual handling of troughs versus funnels depends on the local precipitation regime, the employment of automatically recording clusters of long troughs emerges as the most promising sampling scheme. Even so, a relative error of less than 5% appears out of reach for throughfall under heterogeneous canopies. We therefore suspect a considerable uncertainty of input parameters for interception models derived from measured throughfall, in particular, for those requiring data of small throughfall events.

Numerous studies investigated the influence of abiotic (meteorological conditions) and biotic factors (tree characteristics) on stemflow generation. Although these studies identified the variables that influence stemflow volumes in simply structured forests, the combination of tree characteristics that allows a robust prediction of stemflow volumes in species-rich forests is not well known. Many hydrological applications, however, require at least a rough estimate of stemflow volumes based on the characteristics of a forest stand. The need for robust predictions of stemflow motivated us to investigate the relationships between tree characteristics and stemflow volumes in a species-rich tropical forest located in central Panama. Based on a sampling setup consisting of ten rainfall collectors, 300 throughfall samplers and 60 stemflow collectors and cumulated data comprising 26 rain events, we derive three main findings. Firstly, stemflow represents a minor hydrological component in the studied 1-ha forest patch (1.0% of cumulated rainfall). Secondly, in the studied species-rich forest, single tree characteristics are only weakly related to stemflow volumes. The influence of multiple tree parameters (e.g. crown diameter, presence of large epiphytes and inclination of branches) and the dependencies among these parameters require a multivariate approach to understand the generation of stemflow. Thirdly, predicting stemflow in species-rich forests based on tree parameters is a difficult task. Although our best model can capture the variation in stemflow to some degree, a critical validation reveals that the model cannot provide robust predictions of stemflow. A reanalysis of data from previous studies in species-rich forests corroborates this finding. Based on these results and considering that for most hydrological applications, stemflow is only one parameter among others to estimate, we advocate using the base model, i.e. the mean of the stemflow data, to quantify stemflow volumes for a given study area. Studies in species-rich forests that wish to obtain predictions of stemflow based on tree parameters probably need to conduct a much more extensive sampling than currently implemented by most studies. Copyright (c) 2015 John Wiley & Sons, Ltd.