67 resultados para Fire intensity


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Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project - FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what essons may be learned from FireMIP.

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Animal models of acquired epilepsies aim to provide researchers with tools for use in understanding the processes underlying the acquisition, development and establishment of the disorder. Typically, following a systemic or local insult, vulnerable brain regions undergo a process leading to the development, over time, of spontaneous recurrent seizures. Many such models make use of a period of intense seizure activity or status epilepticus, and this may be associated with high mortality and/or global damage to large areas of the brain. These undesirable elements have driven improvements in the design of chronic epilepsy models, for example the lithium-pilocarpine epileptogenesis model. Here, we present an optimised model of chronic epilepsy that reduces mortality to 1% whilst retaining features of high epileptogenicity and development of spontaneous seizures. Using local field potential recordings from hippocampus in vitro as a probe, we show that the model does not result in significant loss of neuronal network function in area CA3 and, instead, subtle alterations in network dynamics appear during a process of epileptogenesis, which eventually leads to a chronic seizure state. The model’s features of very low mortality and high morbidity in the absence of global neuronal damage offer the chance to explore the processes underlying epileptogenesis in detail, in a population of animals not defined by their resistance to seizures, whilst acknowledging and being driven by the 3Rs (Replacement, Refinement and Reduction of animal use in scientific procedures) principles.

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South American seasonally-dry tropical forests (SDTF) are critically endangered, with only a small proportion of their original distribution remaining. This paper presents a 12,000 year reconstruction of climate change, fire and vegetation dynamics in the Bolivian Chiquitano SDTF, based upon pollen and charcoal analysis, to examine the resilience of this ecosystem to drought and fire. Our analysis demonstrates a complex relationship between climate, fire and floristic composition over multi-millennial time scales, and reveals that moisture variability is the dominant control upon community turnover in this ecosystem. Maximum drought during the early Holocene, consistent with regional drought reconstructions, correlates with a period of significant fire activity between 8,000 and 7,000 cal yr BP which resulted in a decrease in SDTF diversity. As fire activity declined, but severe regional droughts persisted through the mid-Holocene, SDTF, including Anadenanthera and Astronium, became firmly established in the Bolivian lowlands. The trend of decreasing fire activity during the last two millennia promotes the idea among forest ecologists that SDTF are threatened by fire. Our analysis shows that the Chiquitano seasonally dry biome has been more resilient to Holocene changes in climate and fire regime than previously assumed, but raises questions over whether this resilience will continue in the future under increased temperatures and drought coupled with a higher frequency anthropogenic fire regime.

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Fire-centred studies have recently been highlighted as powerful avenues for investigation of energy flows and relations between humans, materials, environments and other species. The aim in this paper is to evaluate this potential first by reviewing the diverse theories and methods that can be applied to investigate the ecological and social significance of anthropogenic fire, and second by applying these to new and existing data sets in archaeology. This paper examines how fire-centred approaches can inform on one of the most significant step-changes in human lifeways and inter-relations with environment and other species – the transition from mobile hunting-gathering to more sedentary agriculture in a key heartland of change, the Zagros region of Iraq and Iran, c. 12,000–8,000 BP. In the review and case studies multiple links are investigated between human fire use and environment, ecology, energy use, technology, the built environment, health, social roles and relations, cultural practices and catastrophic events

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Aerosol properties above clouds have been retrieved over the South East Atlantic Ocean during the fire season 2006 using satellite observations from POLDER (Polarization and Directionality of Earth Reflectances). From June to October, POLDER has observed a mean Above-Cloud Aerosol Optical Thickness (ACAOT) of 0.28 and a mean Above-Clouds Single Scattering Albedo (ACSSA) of 0.87 at 550 nm. These results have been used to evaluate the simulation of aerosols above clouds in 5 AeroCom (Aerosol Comparisons between Observations and Models) models (GOCART, HadGEM3, ECHAM5-HAM2, OsloCTM2 and SPRINTARS). Most models do not reproduce the observed large aerosol load episodes. The comparison highlights the importance of the injection height and the vertical transport parameterizations to simulate the large ACAOT observed by POLDER. Furthermore, POLDER ACSSA is best reproduced by models with a high imaginary part of black carbon refractive index, in accordance with recent recommendations.

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We have shown previously that particpants “at risk” of depression have decreased neural processing of reward suggesting this might be a neural biomarker for depression. However, how the neural signal related to subjective experiences of reward (wanting, liking, intensity) might differ as trait markers for depression, is as yet unknown. Using SPM8 parametric modulation analysis the neural signal related to the subjective report of wanting, liking and intensity was compared between 25 young people with a biological parent with depression (FH) and 25 age/gender matched controls. In a second study the neural signal related to the subjective report of wanting, liking and intensity was compared between 13 unmedicated recovered depressed (RD) patients and 14 healthy age/gender matched controls. The analysis revealed differences in the neural signal for wanting, liking and intensity ratings in the ventral striatum, dmPFC and caudate respectively in the RD group compared to controls . Despite no differences in the FH groups neural signal for wanting and liking there was a difference in the neural signal for intensity ratings in the dACC and anterior insula compared to controls. These results suggest that the neural substrates tracking the intensity but not the wanting or liking for rewards and punishers might be a trait marker for depression.