994 resultados para weather factors


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Dengue virus (DENV) transmission in Australia is driven by weather factors and imported dengue fever (DF) cases. However, uncertainty remains regarding the threshold effects of high-order interactions among weather factors and imported DF cases and the impact of these factors on autochthonous DF. A time-series regression tree model was used to assess the threshold effects of natural temporal variations of weekly weather factors and weekly imported DF cases in relation to incidence of weekly autochthonous DF from 1 January 2000 to 31 December 2009 in Townsville and Cairns, Australia. In Cairns, mean weekly autochthonous DF incidence increased 16.3-fold when the 3-week lagged moving average maximum temperature was <32 °C, the 4-week lagged moving average minimum temperature was ≥24 °C and the sum of imported DF cases in the previous 2 weeks was >0. When the 3-week lagged moving average maximum temperature was ≥32 °C and the other two conditions mentioned above remained the same, mean weekly autochthonous DF incidence only increased 4.6-fold. In Townsville, the mean weekly incidence of autochthonous DF increased 10-fold when 3-week lagged moving average rainfall was ≥27 mm, but it only increased 1.8-fold when rainfall was <27 mm during January to June. Thus, we found different responses of autochthonous DF incidence to weather factors and imported DF cases in Townsville and Cairns. Imported DF cases may also trigger and enhance local outbreaks under favorable climate conditions.

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Key weather factors determining the occurrence and severity of powdery mildew and yellow rust epidemics on winter wheat were identified. Empirical models were formulated to qualitatively predict a damaging epidemic (>5% severity) and quantitatively predict the disease severity given a damaging epidemic occurred. The disease data used was from field experiments at 12 locations in the UK covering the period from 1994 to 2002 with matching data from weather stations within a 5 km range. Wind in December to February was the most influential factor for a damaging epidemic of powdery mildew. Disease severity was best identified by a model with temperature, humidity, and rain in April to June. For yellow rust, the temperature in February to June was the most influential factor for a damaging epidemic as well as for disease severity. The qualitative models identified favorable circumstances for damaging epidemics, but damaging epidemics did not always occur in such circumstances, probably due to other factors such as the availability of initial inoculum and cultivar resistance.

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Foraging behavior in social wasps is important in the development of the colony and reflects an important ecological interaction between the colony and the environment. Although the social traits of the colony play a role in the foraging activities, the conditions that establish the space and time limits are mainly physical. Here, we evaluate colonies of Polybia paulista throughout one year in order to verify the foraging activities and the items collected, as well as the importance of temperature, relative humidity, and solar radiation on motivating foraging. Collection of liquids was always higher than that of solids; preys were collected all year long, and nests showed two annual episodic expansions. The linear mixed effects (LME) model used to analyze which weather factors influence the foraging showed temperature as the most influencing factor on the collection of materials. © 2011 Naila Cristina de Souza Canevazzi and Fernando Barbosa Noll.

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Thesis (Master's)--University of Washington, 2016-06

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Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. ----- ----- Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. ----- ----- Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models. ----- ----- Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.

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Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide.

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Distribution of soft sediment benthic fauna and the environmental factors affecting them were studied, to investigate changes across spatial and temporal scales. Investigations took place at Lough Hyne Marine Reserve using a range of methods. Data on the sedimentation rates of organic and inorganic matter were collected at monthly intervals for one year at a number of sites around the Lough, by use of vertical midwater-column sediment traps. Sedimentation of these two fractions were not coupled; inorganic matter sedimentation depended on hydrodynamic and weather factors, while the organic matter sedimentation was more complex, being dependent on biological and chemical processes in the water column. The effects of regular hypoxic episodes on benthic fauna due to a natural seasonal thermocline were studied in the deep Western Trough, using camera-equipped remotely-operated vehicle to follow transects, on a three-monthly basis over one year. In late summer, the area below the thermocline of the Western Trough was devoid of visible fauna. Decapod crustaceans were the first taxon to make use of ameliorating oxygen conditions in autumn, by darting below the thermocline depth, most likely to scavenge. This was indicated by tracks that they left on the surface of the Trough floor. Some species, most noticeably Fries’ goby Lesueurigobius friesii, migrated below the thermocline depth when conditions were normoxic and established semi-permanent burrows. Their population encompassed all size classes, indicating that this habitat was not limited to juveniles of this territorial species. Recolonisation by macrofauna and burrowing megafauna was studied during normoxic conditions, from November 2009 to May 2010. Macrofauna displayed a typical post-disturbance pattern of recolonisation with one species, the polychaete Scalibregma inflatum, occurring at high abundance levels in March 2010. In May, this population had become significantly reduced and a more diverse community was established. The abundance of burrowing infauna comprising decapods crabs and Fries’ gobies, was estimated by identifying and counting their distinctive burrow structures. While above the summer thermocline depth, burrow abundance increased in a linear fashion, below the thermocline depth a slight reduction of burrow abundance occurred in May, when oxygen conditions deteriorated again. The majority of the burrows occurring in May were made by Fries’ gobies, which are thought to encounter low oxygen concentrations in their burrows. Reduction in burrow abundance of burrowing shrimps Calocaris macandreae and Callianassa subterranea (based on descriptions of burrow structures from the literature), from March to May, might be related to their reduced activity in hypoxia, leading to loss of structural burrow maintenance. Spatial and temporal changes to macrofaunal assemblage structures were studied seasonally for one year across 5 sites in the Lough and subject to multivariate statistical analysis. Assemblage structures were significantly correlated with organic matter levels in the sediment, the amounts of organic matter settling out of the water column one month before macrofaunal sampling took place as well as current speed and temperature. This study was the first to investigate patterns and processes in the Lough soft sediment ecology across all 3 basins on a temporal and spatial scale. An investigation into the oceanographic aspects of the development, behaviour and break-down of the summer thermocline of Lough Hyne was performed in collaboration with researchers from other Irish institutions.

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Relationships between weather, agronomic factors and wheat disease abundance were examined to determine possible causes of variability on century time scales. In archived samples of wheat grain and leaves obtained from the Rothamsted Broadbalk experiment archive (1844-2003), amounts of wheat, Phaeosphaeria nodorum and Mycosphaerella graminicola DNA were determined by quantitative polymerase chain reaction (PCR). Relationships between amounts of pathogens and environmental and agronomic factors were examined by multiple regression. Wheat DNA decayed at approx. 1% yr(-1) in stored grain. No M. graminicola DNA was detected in grain samples. Fluctuations in amounts of P. nodorum in grain were related to changes in spring rainfall, summer temperature and national SO2 emission. Differences in amounts of P. nodorum between grain and leaf were related to summer temperature and spring rainfall. In leaves, annual variation in spring rainfall affected both pathogens similarly, but SO2 had opposite effects. Previous summer temperature had a highly significant effect on M. graminicola. Cultivar effects were significant only at P = 0.1. Long-term variation in P. nodorum and M. graminicola DNA in leaf and grain over the period 1844-2003 was dominated by factors related to national SO2 emissions. Annual variability was dominated by weather factors occurring over a period longer than the growing season.

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There was evaluated the phenology and arthropods as well as the effect of weather on copaiba (Copaifera langsdorffii Desf.) (Leguminoseae). The emission of new leaves and inflorescences as well as the opening of them occurred in the rainy period. There were observed the higher diversity and abundance of insects, principally galling insects.

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Estímulos ambientais exercem efeitos importantes na expressão de ritmos endógenos. Deslocamentos diários de grupos de psitacídeos em resposta ao ciclo claro/escuro têm sido estudados por alguns autores. Todavia, os fatores que influenciam a ritmicidade intrínseca deste comportamento não são bem conhecidos. Este estudo descreve como a periodicidade nictemeral/circadiana dos deslocamentos diários de dormitórios do Papagaio-do-mangue Amazona amazonica é modificada por fatores climatológicos. Os números de papagaios chegando ou deixando o dormitório Ilha dos Papagaios foram determinados de minuto a minuto. Um número significativamente maior de papagaios chegou ao dormitório após o ocaso, enquanto que um número significativamente maior de papagaios deixou o dormitório antes da aurora. O pico de saída dos papagaios ocorreu 23 ± 5,24 minutos antes da aurora, quando a média de intensidade de luz era de 1 lux. O pico de chegada de papagaios ocorreu 6 ± 6,1 minutos após o ocaso, quando a média de intensidade de luz era de 50 lux. Ao alterar a intensidade de luz do ambiente, as condições climatológicas influenciaram significativamente os horários de chegada e saída, com papagaios deixando o dormitório mais tarde ou chegando mais cedo em condições de nebulosidade alta.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Agronomia e Medicina Veterinária, Programa de Pós-Graduação em Agronegócios, 2016.

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The Doctoral thesis focuses on the factors that influence the weather and climate over Peninsular Indias. The first chapter provides a general introduction about the climatic features over peninsular India, various factors dealt in subsequent chapters, such as solar forcing on climate, SST variability in the northern Indian Ocean and its influence on Indian monsoon, moisture content of the atmosphere and its importance in the climate system, empirical formulation of regression forecast of climate and some aspects of regional climate modeling. Chapter 2 deals with the variability in the vertically integrated moisture (VIM) over Peninsular India on various time scales. The third Chapter discusses the influence of solar activity in the low frequency variability in the rainfall of Peninsular India. The study also investigates the influence of solar activity on the horizontal and vertical components of wind and the difference in the forcing before and after the so-called regime shift in the climate system before and after mid-1970s.In Chapter 4 on Peninsular Indian Rainfall and its association with meteorological and oceanic parameters over adjoining oceanic region, a linear regression model was developed and tested for the seasonal rainfall prediction of Peninsular India.

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The goal of this National Transportation Safety Board study was to better understand the risk factors associated with accidents that occur in weather conditions characterized by IMC or poor visibility ("weather-related accidents"). The study accomplished this goal using the case control methodology, which compared a group of accident flights to a matching group of nonaccident flights to identify patterns of variables that distinguished the two groups from each other. This methodology expands on previous Safety Board efforts that have typically concentrated on summaries of accident cases. For this study, Safety Board air safety investigators (ASI) collected data from 72 GA accidents that occurred between August 2003 and April 2004.