970 resultados para Rain and rainfall.


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Reproductive strategy is the set of adaptations that promote the most efficient way that the species will survive under the particular conditions of a determined environment. Understanding these adaptations is important and can help pinpoint populations indicator of environmental changes. Spermatogenesis is a measurable biological process of these adaptations in spatial and temporal scales. We analyzed the morphology of the testes and oviducts of the lizard species that comprise the genus Tropidurus, taking into account the geographical distribution and sympatric relations. For the analysis and the testes were removed from the middle part of the oviducts from Tropidurus etheridge, T oreadicus, T itambere, T spinulosus and T Guarani species, collected in different places in the Mato Grosso state, Brazil. The reproductive period is synchronous for males and females and occurs in September, October and November. Reproductive males were characterized. In the testes are seminiferous tubules with germ cells at different stages of spermatogenesis, with a high epithelium, at present light, free spermatozoa in the lumen and reduction of interstitial tissue. For females, the reproduction peak occurs when the oviduct epithelium is high with secretions and basal nucleus. These months are characterized in the sampled areas over a period of heavy rain and high temperatures. The decline of reproductive period was observed in both sexes, between April and August. Low reproduction in males is characterized by ample light, absence of sperm, only germ cells in the early stages of spermatogenesis are observed (a few spermatogonia and spermatocytes) and interstitial tissue wide. In females, the period of reproductive decline is marked by the absence of unicellular glands in the oviduct epithelium, with higher affinity with the dye. This period corresponds to low rainfall periods and lower temperatures. We propose an analysis of zoological samples; this is a proposal to facilitate the work of many researchers through access to the species, especially rare species.

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Rain acidity may be ascribed to emissions from power station stacks, as well as emissions from other industry, biomass burning, maritime influences, agricultural influences, etc. Rain quality data are available for 30 sites in the South African interior, some from as early as 1985 for up to 14 rainfall seasons, while others only have relatively short records. The article examines trends over time in the raw and volume weighted concentrations of the parameters measured, separately for each of the sites for which sufficient data are available. The main thrust, however, is to examine the inter-relationship structure between the concentrations within each rain event (unweighted data), separately for each site, and to examine whether these inter-relationships have changed over time. The rain events at individual sites can be characterized by approximately eight combinations of rainfall parameters (or rain composition signatures), and these are common to all sites. Some sites will have more events from one signature than another, but there appear to be no signatures unique to a single site. Analysis via factor and cluster analysis, with a correspondence analysis of the results, also aid interpretation of the patterns. This spatio-temporal analysis, performed by pooling all rain event data, irrespective of site or time period, results in nine combinations of rainfall parameters being sufficient to characterize the rain events. The sites and rainfall seasons show patterns in these combinations of parameters, with some combinations appearing more frequently during certain rainfall seasons. In particular, the presence of the combination of low acetate and formate with high magnesium appears to be increasing in the later rainfall seasons, as does this combination together with calcium, sodium, chloride, potassium and fluoride. As expected, sites close together exhibit similar signatures. Copyright © 2002 John Wiley & Sons, Ltd.

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In this work, we analyze the long term variability of rainfall and temperature (1912-2008) of Santa Maria (29 degrees S, 53 degrees W) and its possible connection with natural influences such as solar activity and ENSO. Temperature and rainfall present similar frequencies as revealed by spectral analyses. This analysis shows a large number of short periods between 2-8 years and periods of 11.8-12.3, 19.1-21.0, and 64.3-82.5 years. The cross correlation for rainfall and temperature versus Southern Oscillation Index (SOI) have higher cross-power around 2-8 yr. Rainfall and temperature versus sunspot number (Rz) showed higher cross-power around the 11-yr solar cycle period. A high and continuous cross correlation was observed for Rz-22 yr versus rainfall and temperature. Furthermore, the power between 22-yr solar cycle and meteorological parameters was higher than that obtained with the 11-yr solar cycle, suggesting that the effect of Hale cycle on climate may be stronger than the Schwabe cycle effect. These results indicate that the variability of rainfall and temperature is closely related to the variation of the Southern Oscillation Index and solar activity, and that the El Nino Southern Oscillation and solar activity probably play an important role in the climate system over Southern Brazil. (C) 2011 Elsevier Ltd. All rights reserved.

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A quality-controlled snow and meteorological dataset spanning the period 1 August 1993-31 July 2011 is presented, originating from the experimental station Col de Porte (1325 m altitude, Chartreuse range, France). Emphasis is placed on meteorological data relevant to the observation and modelling of the seasonal snowpack. In-situ driving data, at the hourly resolution, consist of measurements of air temperature, relative humidity, windspeed, incoming short-wave and long-wave radiation, precipitation rate partitioned between snow- and rainfall, with a focus on the snow-dominated season. Meteorological data for the three summer months (generally from 10 June to 20 September), when the continuity of the field record is not warranted, are taken from a local meteorological reanalysis (SAFRAN), in order to provide a continuous and consistent gap-free record. Data relevant to snowpack properties are provided at the daily (snow depth, snow water equivalent, runoff and albedo) and hourly (snow depth, albedo, runoff, surface temperature, soil temperature) time resolution. Internal snowpack information is provided from weekly manual snowpit observations (mostly consisting in penetration resistance, snow type, snow temperature and density profiles) and from a hourly record of temperature and height of vertically free ''settling'' disks. This dataset has been partially used in the past to assist in developing snowpack models and is presented here comprehensively for the purpose of multi-year model performance assessment. The data is placed on the PANGAEA repository (doi:10.1594/PANGAEA.774249) as well as on the public ftp server ftp://ftp-cnrm.meteo.fr/pub-cencdp/.

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Reuse of record except for individual research requires license from Congressional Information Service, Inc.

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The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (R-factor) of the (R)USLE model in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the R-factor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed that modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.

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Abstract The potential impacts of climate change and environmental variability are already evident in most parts of the world, which is witnessing increasing temperature rates and prolonged flood or drought conditions that affect agriculture activities and nature-dependent livelihoods. This study was conducted in Mwanga District in the Kilimanjaro region of Tanzania to assess the nature and impacts of climate change and environmental variability on agriculture-dependent livelihoods and the adaptation strategies adopted by small-scale rural farmers. To attain its objective, the study employed a mixed methods approach in which both qualitative and quantitative techniques were used. The study shows that farmers are highly aware of their local environment and are conscious of the ways environmental changes affect their livelihoods. Farmers perceived that changes in climatic variables such as rainfall and temperature had occurred in their area over the period of three decades, and associated these changes with climate change and environmental variability. Farmers’ perceptions were confirmed by the evidence from rainfall and temperature data obtained from local and national weather stations, which showed that temperature and rainfall in the study area had become more variable over the past three decades. Farmers’ knowledge and perceptions of climate change vary depending on the location, age and gender of the respondents. The findings show that the farmers have limited understanding of the causes of climatic conditions and environmental variability, as some respondents associated climate change and environmental variability with social, cultural and religious factors. This study suggests that, despite the changing climatic conditions and environmental variability, farmers have developed and implemented a number of agriculture adaptation strategies that enable them to reduce their vulnerability to the changing conditions. The findings show that agriculture adaptation strategies employ both planned and autonomous adaptation strategies. However, the study shows that increasing drought conditions, rainfall variability, declining soil fertility and use of cheap farming technology are among the challenges that limit effective implementation of agriculture adaptation strategies. This study recommends further research on the varieties of drought-resilient crops, the development of small-scale irrigation schemes to reduce dependence on rain-fed agriculture, and the improvement of crop production in a given plot of land. In respect of the development of adaptation strategies, the study recommends the involvement of the local farmers and consideration of their knowledge and experience in the farming activities as well as the conditions of their local environment. Thus, the findings of this study may be helpful at various levels of decision making with regard to the development of climate change and environmental variability policies and strategies towards reducing farmers’ vulnerability to current and expected future changes.

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El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

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Seasonal relationship between the Southern Annular Mode (SAM) and the spatial distribution of the cyclone systems over Southern Hemisphere is investigated for the period 1980 to 1999. In addition, seasonal frontogenesis and rainfall distribution over South America and South Atlantic Ocean during different SAM phases were also analyzed. It is observed that during negative SAM phases the cyclone trajectories move northward when compared to the positive one, and in the South America and South Atlantic sector there is intense frontogenetic activity and positive anomaly precipitation over the Southeast of the South America. In general, SAM positive phase shows opposite signals.

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Eucalyptus camaldulensis has great importance in Brazil because of their phenotypic plasticity for different environmental conditions, as soils, altitudes and rainfall. This study is an investigation of a base population of E. camaldulensis from Australia through a progeny test implanted in Selviria, MS. The trial was established in a randomized block design, with 25 families and 60 replications of single tree plots. Genetic parameters for anatomic traits and volume shrinkage were estimated, as well as their correlations with wood basic density. No significant differences among progenies were observed for the traits studied. The additive genetic variation coefficient at individual and among progeny levels ranged from low (0.26%) to high (16.98%). The narrow sense heritability at individual and family means levels also ranged from low (0.01) to high (0.87). This indicates that some traits are under strong genetic control and can be improved by selection. In the present situation, in order to attain the highest genetic gains, the sequential selection among and within progeny would be recommended.

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The area of private land suitable and available for growing hoop pine (Araucaria cunninghamii) on the Atherton Tablelands in North Queensland was modelled using a geographic information system (GIS). In Atherton, Eacham and Herberton shires, approximately 64,700 ha of privately owned land were identified as having a mean annual rainfall and soil type similar to Forestry Plantations Queensland (FPQ) hoop pine growth plots with an approximate growth rate of 20 m3 per annum. Land with slope of over 25° and land covered with native vegetation were excluded in the estimation. If land which is currently used for high-value agriculture is also excluded, the net area of land potentially suitable and available for expansion of hoop pine plantations is approximately 22,900 ha. Expert silvicultural advice emphasized the role of site preparation and weed control in affecting the long-term growth rate of hoop pine. Hence, sites with less than optimal fertility and rainfall may be considered as being potentially suitable for growing hoop pine at a lower growth rate. The datasets had been prepared at various scales and differing precision for their description of land attributes. Therefore, the results of this investigation have limited applicability for planning at the individual farm level but are useful at the regional level to target areas for plantation expansion.

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Recent El Nino events have stimulated interest in the development of modeling techniques to forecast extremes of climate and related health events. Previous studies have documented associations between specific climate variables (particularly temperature and rainfall) and outbreaks of arboviral disease. In some countries, such diseases are sensitive to Fl Nino. Here we describe a climate-based model for the prediction of Ross River virus epidemics in Australia. From a literature search and data on case notifications, we determined in which years there were epidemics of Ross River virus in southern Australia between 1928 and 1998. Predictor variables were monthly Southern Oscillation index values for the year of an epidemic or lagged by 1 year. We found that in southeastern states, epidemic years were well predicted by monthly Southern Oscillation index values in January and September in the previous year. The model forecasts that there is a high probability of epidemic Ross River virus in the southern states of Australia in 1999. We conclude that epidemics of arboviral disease can, at least in principle, be predicted on the basis of climate relationships.

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Slumping of hardsetting seedbeds upon wetting is likely to determine the shrinking and development of strength on drying. Different processes have been invoked, including aggregate disruption, material relocation, and compaction. To gain a better understanding of the role played by compaction compared with aggregate disruption in seedbed slumping and shrinking, mechanical analysis was combined with previous morphogenetical description. The global structural behavior of repacked seedbeds of a hardsetting sandy loam soil was studied after wetting and again after subsequent drying. Bulk density was measured in 5-mm-depth increments using gamma attenuation, and water content was determined at 10-mm-depth increments. Various wetting conditions were used to simulate a range of climatic and management conditions, including flood irrigation, furrow irrigation of a formed seedbed, drip irrigation, and rainfall. Aggregate coalescence under overburden pressure played the main role in slumping, even though microcracking enhanced coalescence. Most of the slumping occurred at calculated effective stress > 1.1 kPa. Intense aggregate breakdown at the top of seedbeds under fast wetting led to slight slumping because the resulting clogging of the initial interaggregate packing voids was balanced, in part, by the increase in microporosity resulting from aggregate disruption. However, aggregate coalescence induced by overburden pressure developing at the seedbed bottom often resulted in a strong decrease in total porosity. The effect of rainfall kinetic energy on crust bulk density was strong compared with the effect of fast wetting (bulk density increase of about 0.07 Mg m(-3) and 0.03 Mg m(-3), respectively) and could be ascribed to compaction rather than to aggregate breakdown. Shrinking on drying was related to the continuity of the microstructure resulting from wetting rather than to the intensity of slumping. Aggregate breakdown led to more shrinking than did aggregate coalescence.

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Soil erosion is a major environmental issue in Australia. It reduces land productivity and has off-site effects of decreased water quality. Broad-scale spatially distributed soil erosion estimation is essential for prioritising erosion control programs and as a component of broader assessments of natural resource condition. This paper describes spatial modelling methods and results that predict sheetwash and rill erosion over the Australian continent using the revised universal soil loss equation (RUSLE) and spatial data layers for each of the contributing environmental factors. The RUSLE has been used before in this way but here we advance the quality of estimation. We use time series of remote sensing imagery and daily rainfall to incorporate the effects of seasonally varying cover and rainfall intensity, and use new digital maps of soil and terrain properties. The results are compared with a compilation of Australian erosion plot data, revealing an acceptable consistency between predictions and observations. The modelling results show that: (1) the northern part of Australia has greater erosion potential than the south; (2) erosion potential differs significantly between summer and winter; (3) the average erosion rate is 4.1 t/ha. year over the continent and about 2.9 x 10(9) tonnes of soil is moved annually which represents 3.9% of global soil erosion from 5% of world land area; and (4) the erosion rate has increased from 4 to 33 times on average for agricultural lands compared with most natural vegetated lands.