861 resultados para Nino Warming Event


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The Spanish Government has established post-market environmental monitoring (PMEM) as mandatory for genetically modified (GM) crop varieties cultivated in Spain. In order to comply with this regulation, effects of Bt maize varieties derived from the event MON810 on the predatory fauna were monitored for two years in northeast and central Spain. The study was carried out with a randomized block design in maize fields of 3-4 ha on which the abundance of plant-dwelling predators and the activity-density of soil-dwelling predators in Bt vs. non-Bt near-isogenic varieties were compared. To this end, the plots were sampled by visual inspection of a certain number of plants and pitfall traps 6 or 7 times throughout two seasons. No significant differences in predator densities on plants were found between Bt and non-Bt varieties. In the pitfall traps, significant differences between the two types of maize were found only in Staphylinidae, in which trap catches in non-Bt maize were higher than in Bt maize in central Spain. Based on the statistical power of the assays, surrogate arthropods for PMEM purposes are proposed; Orius spp. and Araneae for visual sampling and Carabidae, Araneae, and Staphylinidae for pitfall trapping. The other predator groups recorded in the study, Nabis sp. and Coccinellidae in visual sampling and Dermaptera in pitfall trapping, gave very poor power results. To help to establish a standardized protocol for PMEM of genetically modified crops, the effect-detecting capacity with a power of 0.8 of each predator group is given.

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SEPServer is a three-year collaborative project funded by the seventh framework programme (FP7-SPACE) of the European Union. The objective of the project is to provide access to state-of-the-art observations and analysis tools for the scientific community on solar energetic particle (SEP) events and related electromagnetic (EM) emissions. The project will eventually lead to better understanding of the particle acceleration and transport processes at the Sun and in the inner heliosphere. These processes lead to SEP events that form one of the key elements of space weather. In this paper we present the first results from the systematic analysis work performed on the following datasets: SOHO/ERNE, SOHO/EPHIN, ACE/EPAM, Wind/WAVES and GOES X-rays. A catalogue of SEP events at 1 AU, with complete coverage over solar cycle 23, based on high-energy (~68-MeV) protons from SOHO/ERNE and electron recordings of the events by SOHO/EPHIN and ACE/EPAM are presented. A total of 115 energetic particle events have been identified and analysed using velocity dispersion analysis (VDA) for protons and time-shifting analysis (TSA) for electrons and protons in order to infer the SEP release times at the Sun. EM observations during the times of the SEP event onset have been gathered and compared to the release time estimates of particles. Data from those events that occurred during the European day-time, i.e., those that also have observations from ground-based observatories included in SEPServer, are listed and a preliminary analysis of their associations is presented. We find that VDA results for protons can be a useful tool for the analysis of proton release times, but if the derived proton path length is out of a range of 1 AU < s[3 AU, the result of the analysis may be compromised, as indicated by the anti-correlation of the derived path length and release time delay from the asso ciated X-ray flare. The average path length derived from VDA is about 1.9 times the nominal length of the spiral magnetic field line. This implies that the path length of first-arriving MeV to deka-MeV protons is affected by interplanetary scattering. TSA of near-relativistic electrons results in a release time that shows significant scatter with respect to the EM emissions but with a trend of being delayed more with increasing distance between the flare and the nominal footpoint of the Earth-connected field line.

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Main concepts : The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) approach defines quality of evidence as confidence in effect estimates; this conceptualization can readily be applied to bodies of evidence estimating the risk of future of events (that is, prognosis) in broadly defined populations In the field of prognosis, a body of observational evidence (including single arms of randomized controlled trials) begins as high quality evidence. The five domains GRADE considers in rating down confidence in estimates of treatment effect-that is, risk of bias, imprecision, inconsistency, indirectness, and publication bias-as well as the GRADE criteria for rating up quality, also apply to estimates of the risk of future of events from a body of prognostic studies Applying these concepts to systematic reviews of prognostic studies provides a ful approach to determine confidence in estimates of overall prognosis in broad populations.

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This study presents an innovative methodology for forensic science image analysis for event reconstruction. The methodology is based on experiences from real cases. It provides real added value to technical guidelines such as standard operating procedures (SOPs) and enriches the community of practices at stake in this field. This bottom-up solution outlines the many facets of analysis and the complexity of the decision-making process. Additionally, the methodology provides a backbone for articulating more detailed and technical procedures and SOPs. It emerged from a grounded theory approach; data from individual and collective interviews with eight Swiss and nine European forensic image analysis experts were collected and interpreted in a continuous, circular and reflexive manner. Throughout the process of conducting interviews and panel discussions, similarities and discrepancies were discussed in detail to provide a comprehensive picture of practices and points of view and to ultimately formalise shared know-how. Our contribution sheds light on the complexity of the choices, actions and interactions along the path of data collection and analysis, enhancing both the researchers' and participants' reflexivity.

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Magical ideation and belief in the paranormal is considered to represent a trait-like character; people either believe in it or not. Yet, anecdotes indicate that exposure to an anomalous event can turn skeptics into believers. This transformation is likely to be accompanied by altered cognitive functioning such as impaired judgments of event likelihood. Here, we investigated whether the exposure to an anomalous event changes individuals' explicit traditional (religious) and non-traditional (e.g., paranormal) beliefs as well as cognitive biases that have previously been associated with non-traditional beliefs, e.g., repetition avoidance when producing random numbers in a mental dice task. In a classroom, 91 students saw a magic demonstration after their psychology lecture. Before the demonstration, half of the students were told that the performance was done respectively by a conjuror (magician group) or a psychic (psychic group). The instruction influenced participants' explanations of the anomalous event. Participants in the magician, as compared to the psychic group, were more likely to explain the event through conjuring abilities while the reverse was true for psychic abilities. Moreover, these explanations correlated positively with their prior traditional and non-traditional beliefs. Finally, we observed that the psychic group showed more repetition avoidance than the magician group, and this effect remained the same regardless of whether assessed before or after the magic demonstration. We conclude that pre-existing beliefs and contextual suggestions both influence people's interpretations of anomalous events and associated cognitive biases. Beliefs and associated cognitive biases are likely flexible well into adulthood and change with actual life events.

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Crops and forests are already responding to rising atmospheric carbon dioxide and air temperatures. Increasing atmospheric CO2 concentrations are expected to enhance plant photosynthesis. Nevertheless, after long-term exposure, plants acclimate and show a reduction in photosynthetic activity (i.e. down-regulation). If in the future the Earth"s temperature is allowed to rise further, plant ecosystems and food security will both face significant threats. The scientific community has recognized that an increase in global temperatures should remain below 2°C in order to combat climate change. All this evidence suggests that, in parallel with reductions in CO2 emissions, a more direct approach to mitigate global warming should be considered. We propose here that global warming could be partially mitigated directly through local bio-geoengineering approaches. For example, this could be done through the management of solar radiation at surface level, i.e. by increasing global albedo. Such an effect has been documented in the south-eastern part of Spain, where a significant surface air temperature trend of -0.3°C per decade has been observed due to a dramatic expansion of greenhouse horticulture.

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This thesis describes the development of a software requirements specification for a user-centric event management system. The system is set to satisfy three goals: adding value for the event attendees, adding value for the event organizer, and reducing the costs of arranging and running an event. The requirements are identified by researching the prescriptive traits of event business and the current state of the case company and its environment. First the professional and human needs for events are scrutinized. Second, some recent reports about the current trends in the event business are reviewed. Then the event life cycle is presented using the model of new service development, and online promotion of events and especially word-of-mouth marketing receive special attention. Events are also regarded from the perspective of social networks and social media. The case company’s current state and its competitors are reviewed to formulate the needs which the system should fulfil. Then the currently available solutions for social media oriented event management are reviewed. The result is a set of functional and non-functional requirements. The functional requirements are categorized into social media, social networking, event personalization, event management, and system administration features. The specified features and non-functional requirements satisfy the three goals set for the system.

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From 6 to 8 November 1982 one of the most catastrophic flash-flood events was recorded in the Eastern Pyrenees affecting Andorra and also France and Spain with rainfall accumulations exceeding 400 mm in 24 h, 44 fatalities and widespread damage. This paper aims to exhaustively document this heavy precipitation event and examines mesoscale simulations performed by the French Meso-NH non-hydrostatic atmospheric model. Large-scale simulations show the slow-evolving synoptic environment favourable for the development of a deep Atlantic cyclone which induced a strong southerly flow over the Eastern Pyrenees. From the evolution of the synoptic pattern four distinct phases have been identified during the event. The mesoscale analysis presents the second and the third phase as the most intense in terms of rainfall accumulations and highlights the interaction of the moist and conditionally unstable flows with the mountains. The presence of a SW low level jet (30 m s-1) around 1500 m also had a crucial role on focusing the precipitation over the exposed south slopes of the Eastern Pyrenees. Backward trajectories based on Eulerian on-line passive tracers indicate that the orographic uplift was the main forcing mechanism which triggered and maintained the precipitating systems more than 30 h over the Pyrenees. The moisture of the feeding flow mainly came from the Atlantic Ocean (7-9 g kg-1) and the role of the Mediterranean as a local moisture source was very limited (2-3 g kg-1) due to the high initial water vapour content of the parcels and the rapid passage over the basin along the Spanish Mediterranean coast (less than 12 h).

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Mountain regions worldwide are particularly sensitive to on-going climate change. Specifically in the Alps in Switzerland, the temperature has increased twice as fast than in the rest of the Northern hemisphere. Water temperature closely follows the annual air temperature cycle, severely impacting streams and freshwater ecosystems. In the last 20 years, brown trout (Salmo trutta L) catch has declined by approximately 40-50% in many rivers in Switzerland. Increasing water temperature has been suggested as one of the most likely cause of this decline. Temperature has a direct effect on trout population dynamics through developmental and disease control but can also indirectly impact dynamics via food-web interactions such as resource availability. We developed a spatially explicit modelling framework that allows spatial and temporal projections of trout biomass using the Aare river catchment as a model system, in order to assess the spatial and seasonal patterns of trout biomass variation. Given that biomass has a seasonal variation depending on trout life history stage, we developed seasonal biomass variation models for three periods of the year (Autumn-Winter, Spring and Summer). Because stream water temperature is a critical parameter for brown trout development, we first calibrated a model to predict water temperature as a function of air temperature to be able to further apply climate change scenarios. We then built a model of trout biomass variation by linking water temperature to trout biomass measurements collected by electro-fishing in 21 stations from 2009 to 2011. The different modelling components of our framework had overall a good predictive ability and we could show a seasonal effect of water temperature affecting trout biomass variation. Our statistical framework uses a minimum set of input variables that make it easily transferable to other study areas or fish species but could be improved by including effects of the biotic environment and the evolution of demographical parameters over time. However, our framework still remains informative to spatially highlight where potential changes of water temperature could affect trout biomass. (C) 2015 Elsevier B.V. All rights reserved.-

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Mass mortality events are increasing dramatically in all coastal marine environments. Determining the underlying causes of mass mortality events has proven difficult in the past because of the lack of prior quantitative data on populations and environmental variables. Four-year surveys of two shallow-water sponge species, Ircinia fasciculata and Sarcotragus spinosulum, were carried out in the western Mediterranean Sea. These surveys provided evidence of two severe sponge die-offs (total mortality ranging from 80 to 95% of specimens) occurring in the summers of 2008 and 2009. These events primarily affected I. fasciculata, which hosts both phototrophic and heterotrophic microsymbionts, while they did not affect S. spinosulum, which harbors only heterotrophic bacteria. We observed a significant positive correlation between the percentage of injured I. fasciculata specimens and exposure time to elevated temperature conditions in all populations, suggesting a key role of temperature in triggering mortality events. A comparative ultrastructural study of injured and healthy I. fasciculata specimens showed that cyanobacteria disappeared from injured specimens, which suggests that cyanobacterial decay could be involved in I. fasciculata mortality. A laboratory experiment confirmed that the cyanobacteria harbored by I. fasciculata displayed a significant reduction in photosynthetic efficiency in the highest temperature treatment. The sponge disease reported here led to a severe decrease in the abundance of the surveyed populations. It represents one of the most dramatic mass mortality events to date in the Mediterranean Sea

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Global warming mitigation has recently become a priority worldwide. A large body of literature dealing with energy related problems has focused on reducing greenhouse gases emissions at an engineering scale. In contrast, the minimization of climate change at a wider macroeconomic level has so far received much less attention. We investigate here the issue of how to mitigate global warming by performing changes in an economy. To this end, we make use of a systematic tool that combines three methods: linear programming, environmentally extended input output models, and life cycle assessment principles. The problem of identifying key economic sectors that contribute significantly to global warming is posed in mathematical terms as a bi criteria linear program that seeks to optimize simultaneously the total economic output and the total life cycle CO2 emissions. We have applied this approach to the European Union economy, finding that significant reductions in global warming potential can be attained by regulating specific economic sectors. Our tool is intended to aid policymakers in the design of more effective public policies for achieving the environmental and economic targets sought.