62 resultados para SPATIO-TEMPORAL DISTRIBUTION


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The water budget approach is applied to an atmospheric box above Switzerland (hereafter referred to as the “Swiss box”) to quantify the atmospheric water vapour flux using ECMWF ERA-Interim reanalyses. The results confirm that the water vapour flux through the Swiss box is highly temporally variable, ranging from 1 to 5 · 107 kg/s during settled anticyclonic weather, but increasing in size by a factor of ten or more during high speed currents of water vapour. Overall, Switzerland and the Swiss box “import” more water vapour than it “exports”, but the amount gained remains only a small fraction (1% to 5%) of the total available water vapour passing by. High inward water vapour fluxes are not necessarily linked to high precipitation episodes. The water vapour flux during the August 2005 floods, which caused severe damage in central Switzerland, is examined and an assessment is made of the computed water vapour fluxes compared to high spatio-temporal rain gauge and radar observations. About 25% of the incoming water vapour flux was stored in Switzerland. The computed water vapour fluxes from ECMWF data compare well with the mean rain gauge observations and the combined rain-gauge radar precipitation products.

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The ground-based radiometer GROMOS, stationed in Bern (47.95° N, 7.44° E), Switzerland, has a unique dataset: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equal quality during night- and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 yr of GROMOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The diurnal ozone cycle from GROMOS is compared to two models: The Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized Atmosphere (HAMMONIA). Aura Microwave Limb Sounder (Aura/MLS) ozone data, from night- and daytime overpasses over Bern, have also been included in the comparison. Generally, observation and models show good qualitative agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25% less than nighttime ozone (reference is 22:30–01:30). In the stratosphere, ozone reaches its maximum in the afternoon showing values several percent larger than the midnight value. It is important that diurnal ozone variations of this order are taken into account when merging different data sets for the derivation of long-term ozone trends in the stratosphere. Further, GROMOS and models indicate a seasonal behavior of daily ozone variations in the stratosphere with a larger afternoon maximum during daytime in summer than in winter. At 0.35 hPa, observations from GROMOS and Aura/MLS show a seasonal pattern in diurnal ozone variations with larger relative amplitudes during daytime in winter (−25 ± 5%) than in summer (−18 ± 4%) (compared to mean values around midnight). For the first time, a time series of the diurnal variations in ozone is presented: 17 yr of GROMOS data show strong interannual variations in the diurnal ozone cycle for both the stratosphere and the mesosphere. There are some indications that strong temperature tides can suppress the diurnal variation of stratospheric ozone via the anticorrelation of temperature and ozone. That means the spatio-temporal variability of solar thermal tides seems to affect the diurnal cycle of stratospheric ozone.

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The ground-based radiometer GROMOS, stationed in Bern (47.95° N, 7.44° E), Switzerland, has a unique dataset: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equal quality during night- and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 yr of GROMOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The diurnal ozone cycle from GROMOS is compared to two models: The Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized Atmosphere (HAMMONIA). Aura Microwave Limb Sounder (Aura/MLS) ozone data, from night- and daytime overpasses over Bern, have also been included in the comparison. Generally, observation and models show good qualitative agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25% less than nighttime ozone (reference is 22:30–01:30). In the stratosphere, ozone reaches its maximum in the afternoon showing values several percent larger than the midnight value. It is important that diurnal ozone variations of this order are taken into account when merging different data sets for the derivation of long-term ozone trends in the stratosphere. Further, GROMOS and models indicate a seasonal behavior of daily ozone variations in the stratosphere with a larger afternoon maximum during daytime in summer than in winter. At 0.35 hPa, observations from GROMOS and Aura/MLS show a seasonal pattern in diurnal ozone variations with larger relative amplitudes during daytime in winter (−25 ± 5%) than in summer (−18 ± 4%) (compared to mean values around midnight). For the first time, a time series of the diurnal variations in ozone is presented: 17 yr of GROMOS data show strong interannual variations in the diurnal ozone cycle for both the stratosphere and the mesosphere. There are some indications that strong temperature tides can suppress the diurnal variation of stratospheric ozone via the anticorrelation of temperature and ozone. That means the spatio-temporal variability of solar thermal tides seems to affect the diurnal cycle of stratospheric ozone.

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In a network of competing species, a competitive intransitivity occurs when the ranking of competitive abilities does not follow a linear hierarchy (A > B > C but C > A). A variety of mathematical models suggests that intransitive networks can prevent or slow down competitive exclusion and maintain biodiversity by enhancing species coexistence. However, it has been difficult to assess empirically the relative importance of intransitive competition because a large number of pairwise species competition experiments are needed to construct a competition matrix that is used to parameterize existing models. Here we introduce a statistical framework for evaluating the contribution of intransitivity to community structure using species abundance matrices that are commonly generated from replicated sampling of species assemblages. We provide metrics and analytical methods for using abundance matrices to estimate species competition and patch transition matrices by using reverse-engineering and a colonization-competition model. These matrices provide complementary metrics to estimate the degree of intransitivity in the competition network of the sampled communities. Benchmark tests reveal that the proposed methods could successfully detect intransitive competition networks, even in the absence of direct measures of pairwise competitive strength. To illustrate the approach, we analyzed patterns of abundance and biomass of five species of necrophagous Diptera and eight species of their hymenopteran parasitoids that co-occur in beech forests in Germany. We found evidence for a strong competitive hierarchy within communities of flies and parasitoids. However, for parasitoids, there was a tendency towards increasing intransitivity in higher weight classes, which represented larger resource patches. These tests provide novel methods for empirically estimating the degree of intransitivity in competitive networks from observational datasets. They can be applied to experimental measures of pairwise species interactions, as well as to spatio-temporal samples of assemblages in homogenous environments or environmental gradients.

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Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity.

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We propose a method to acquire 3D light fields using a hand-held camera, and describe several computational photography applications facilitated by our approach. As our input we take an image sequence from a camera translating along an approximately linear path with limited camera rotations. Users can acquire such data easily in a few seconds by moving a hand-held camera. We include a novel approach to resample the input into regularly sampled 3D light fields by aligning them in the spatio-temporal domain, and a technique for high-quality disparity estimation from light fields. We show applications including digital refocusing and synthetic aperture blur, foreground removal, selective colorization, and others.

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Bees are a key component of biodiversity as they ensure a crucial ecosystem service: pollination. This ecosystem service is nowadays threatened, because bees suffer from agricultural intensification. Yet, bees rarely benefit from the measures established to promote biodiversity in farmland, such as agri-environment schemes (AES). We experimentally tested if the spatio-temporal modification of mowing regimes within extensively managed hay meadows, a widespread AES, can promote bees. We applied a randomized block design, replicated 12 times across the Swiss lowlands, that consisted of three different mowing treatments: 1) first cut not before 15 June (conventional regime for meadows within Swiss AES); 2) first cut not before 15 June, as treatment 1 but with 15% of area left uncut serving as a refuge; 3) first cut not before 15 July. Bees were collected with pan traps, twice during the vegetation season (before and after mowing). Wild bee abundance and species richness significantly increased in meadows where uncut refuges were left, in comparison to meadows without refuges: there was both an immediate (within year) and cumulative (from one year to the following) positive effect of the uncut refuge treatment. An immediate positive effect of delayed mowing was also evidenced in both wild bees and honey bees. Conventional AES could easily accommodate such a simple management prescription that promotes farmland biodiversity and is likely to enhance pollination services.

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The blood-brain barrier (BBB) is essential for maintaining homeostasis within the central nervous system (CNS) and is a prerequisite for proper neuronal function. The BBB is localized to microvascular endothelial cells that strictly control the passage of metabolites into and out of the CNS. Complex and continuous tight junctions and lack of fenestrae combined with low pinocytotic activity make the BBB endothelium a tight barrier for water soluble moleucles. In combination with its expression of specific enzymes and transport molecules, the BBB endothelium is unique and distinguishable from all other endothelial cells in the body. During embryonic development, the CNS is vascularized by angiogenic sprouting from vascular networks originating outside of the CNS in a precise spatio-temporal manner. The particular barrier characteristics of BBB endothelial cells are induced during CNS angiogenesis by cross-talk with cellular and acellular elements within the developing CNS. In this review, we summarize the currently known cellular and molecular mechanisms mediating brain angiogenesis and introduce more recently discovered CNS-specific pathways (Wnt/β-catenin, Norrin/Frizzled4 and hedgehog) and molecules (GPR124) that are crucial in BBB differentiation and maturation. Finally, based on observations that BBB dysfunction is associated with many human diseases such as multiple sclerosis, stroke and brain tumors, we discuss recent insights into the molecular mechanisms involved in maintaining barrier characteristics in the mature BBB endothelium.

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We study the spatial and temporal distribution of hydrogen energetic neutral atoms (ENAs) from the heliosheath observed with the IBEX-Lo sensor of the Interstellar Boundary EXplorer (IBEX) from solar wind energies down to the lowest available energy (15 eV). All available IBEX-Lo data from 2009 January until 2013 June were included. The sky regions imaged when the spacecraft was outside of Earth's magnetosphere and when the Earth was moving toward the direction of observation offer a sufficient signal-to-noise ratio even at very low energies. We find that the ENA ribbon—a 20° wide region of high ENA intensities—is most prominent at solar wind energies whereas it fades at lower energies. The maximum emission in the ribbon is located near the poles for 2 keV and closer to the ecliptic plane for energies below 1 keV. This shift is an evidence that the ENA ribbon originates from the solar wind. Below 0.1 keV, the ribbon can no longer be identified against the globally distributed ENA signal. The ENA measurements in the downwind direction are affected by magnetospheric contamination below 0.5 keV, but a region of very low ENA intensities can be identified from 0.1 keV to 2 keV. The energy spectra of heliospheric ENAs follow a uniform power law down to 0.1 keV. Below this energy, they seem to become flatter, which is consistent with predictions. Due to the subtraction of local background, the ENA intensities measured with IBEX agree with the upper limit derived from Lyα observations.

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The capacity to perceive and respond is integral to biological immune systems, but to what extent can plants specifically recognize and respond to insects? Recent findings suggest that plants possess surveillance systems that are able to detect general patterns of cellular damage as well as highly specific herbivore-associated cues. The jasmonate (JA) pathway has emerged as the major signaling cassette that integrates information perceived at the plant–insect interface into broad-spectrum defense responses. Specificity can be achieved via JA-independent processes and spatio-temporal changes of JA-modulating hormones, including ethylene (ET), salicylic acid (SA), abscisic acid (ABA), auxin, cytokinins (CK), brassinosteroids (BR) and gibberellins (GB). The identification of receptors and ligands and an integrative view of hormone-mediated response systems are crucial to understand specificity in plant immunity to herbivores.

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This thesis covers a broad part of the field of computational photography, including video stabilization and image warping techniques, introductions to light field photography and the conversion of monocular images and videos into stereoscopic 3D content. We present a user assisted technique for stereoscopic 3D conversion from 2D images. Our approach exploits the geometric structure of perspective images including vanishing points. We allow a user to indicate lines, planes, and vanishing points in the input image, and directly employ these as guides of an image warp that produces a stereo image pair. Our method is most suitable for scenes with large scale structures such as buildings and is able to skip the step of constructing a depth map. Further, we propose a method to acquire 3D light fields using a hand-held camera, and describe several computational photography applications facilitated by our approach. As the input we take an image sequence from a camera translating along an approximately linear path with limited camera rotations. Users can acquire such data easily in a few seconds by moving a hand-held camera. We convert the input into a regularly sampled 3D light field by resampling and aligning them in the spatio-temporal domain. We also present a novel technique for high-quality disparity estimation from light fields. Finally, we show applications including digital refocusing and synthetic aperture blur, foreground removal, selective colorization, and others.

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Soils are fundamental to ensuring water, energy and food security. Within the context of sus- tainable food production, it is important to share knowledge on existing and emerging tech- nologies that support land and soil monitoring. Technologies, such as remote sensing, mobile soil testing, and digital soil mapping, have the potential to identify degraded and non- /little-responsive soils, and may also provide a basis for programmes targeting the protection and rehabilitation of soils. In the absence of such information, crop production assessments are often not based on the spatio-temporal variability in soil characteristics. In addition, uncertain- ties in soil information systems are notable and build up when predictions are used for monitor- ing soil properties or biophysical modelling. Consequently, interpretations of model-based results have to be done cautiously. As such they provide a scientific, but not always manage- able, basis for farmers and/or policymakers. In general, the key incentives for stakeholders to aim for sustainable management of soils and more resilient food systems are complex at farm as well as higher levels. The same is true of drivers of soil degradation. The decision- making process aimed at sustainable soil management, be that at farm or higher level, also in- volves other goals and objectives valued by stakeholders, e.g. land governance, improved envi- ronmental quality, climate change adaptation and mitigation etc. In this dialogue session we will share ideas on recent developments in the discourse on soils, their functions and the role of soil and land information in enhancing food system resilience.

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Regime shifts, defined as a radical and persistent reconfiguration of an ecosystem following a disturbance, have been acknowledged by scientists as a very important aspect of the dynamic of ecosystems. However, their consideration in land management planning remains marginal and limited to specific processes and systems. Current research focuses on mathematical modeling and statistical analysis of spatio-temporal data for specific environmental variables. These methods do not fulfill the needs of land managers, who are confronted with a multitude of processes and pressure types and require clear and simple strategies to prevent regime shift or to increase the resilience of their environment. The EU-FP7 CASCADE project is looking at regime shifts of dryland ecosystems in southern Europe and specifically focuses on rangeland and forest systems which are prone to various land degradation threats. One of the aims of the project is to evaluate the impact of different management practices on the dynamic of the environment in a participatory manner, including a multi-stakeholder evaluation of the state of the environment and of the management potential. To achieve this objective we have organized several stakeholder meetings and we have compiled a review of management practices using the WOCAT methodology, which enables merging scientific and land users knowledge. We highlight here the main challenges we have encountered in applying the notion of regime shift to real world socio-ecological systems and in translating related concepts such as tipping points, stable states, hysteresis and resilience to land managers, using concrete examples from CASCADE study sites. Secondly, we explore the advantages of including land users’ knowledge in the scientific understanding of regime shifts. Moreover, we discuss useful alternative concepts and lessons learnt that will allow us to build a participatory method for the assessment of resilient management practices in specific socio-ecological systems and to foster adaptive dryland management.

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The spatial context is critical when assessing present-day climate anomalies, attributing them to potential forcings and making statements regarding their frequency and severity in a long-term perspective. Recent international initiatives have expanded the number of high-quality proxy-records and developed new statistical reconstruction methods. These advances allow more rigorous regional past temperature reconstructions and, in turn, the possibility of evaluating climate models on policy-relevant, spatio-temporal scales. Here we provide a new proxy-based, annually-resolved, spatial reconstruction of the European summer (June–August) temperature fields back to 755 CE based on Bayesian hierarchical modelling (BHM), together with estimates of the European mean temperature variation since 138 BCE based on BHM and composite-plus-scaling (CPS). Our reconstructions compare well with independent instrumental and proxy-based temperature estimates, but suggest a larger amplitude in summer temperature variability than previously reported. Both CPS and BHM reconstructions indicate that the mean 20th century European summer temperature was not significantly different from some earlier centuries, including the 1st, 2nd, 8th and 10th centuries CE. The 1st century (in BHM also the 10th century) may even have been slightly warmer than the 20th century, but the difference is not statistically significant. Comparing each 50 yr period with the 1951–2000 period reveals a similar pattern. Recent summers, however, have been unusually warm in the context of the last two millennia and there are no 30 yr periods in either reconstruction that exceed the mean average European summer temperature of the last 3 decades (1986–2015 CE). A comparison with an ensemble of climate model simulations suggests that the reconstructed European summer temperature variability over the period 850–2000 CE reflects changes in both internal variability and external forcing on multi-decadal time-scales. For pan-European temperatures we find slightly better agreement between the reconstruction and the model simulations with high-end estimates for total solar irradiance. Temperature differences between the medieval period, the recent period and the Little Ice Age are larger in the reconstructions than the simulations. This may indicate inflated variability of the reconstructions, a lack of sensitivity and processes to changes in external forcing on the simulated European climate and/or an underestimation of internal variability on centennial and longer time scales.

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Syndromic surveillance (SyS) systems currently exploit various sources of health-related data, most of which are collected for purposes other than surveillance (e.g. economic). Several European SyS systems use data collected during meat inspection for syndromic surveillance of animal health, as some diseases may be more easily detected post-mortem than at their point of origin or during the ante-mortem inspection upon arrival at the slaughterhouse. In this paper we use simulation to evaluate the performance of a quasi-Poisson regression (also known as an improved Farrington) algorithm for the detection of disease outbreaks during post-mortem inspection of slaughtered animals. When parameterizing the algorithm based on the retrospective analyses of 6 years of historic data, the probability of detection was satisfactory for large (range 83-445 cases) outbreaks but poor for small (range 20-177 cases) outbreaks. Varying the amount of historical data used to fit the algorithm can help increasing the probability of detection for small outbreaks. However, while the use of a 0·975 quantile generated a low false-positive rate, in most cases, more than 50% of outbreak cases had already occurred at the time of detection. High variance observed in the whole carcass condemnations time-series, and lack of flexibility in terms of the temporal distribution of simulated outbreaks resulting from low reporting frequency (monthly), constitute major challenges for early detection of outbreaks in the livestock population based on meat inspection data. Reporting frequency should be increased in the future to improve timeliness of the SyS system while increased sensitivity may be achieved by integrating meat inspection data into a multivariate system simultaneously evaluating multiple sources of data on livestock health.