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Meteorological Variables (meteorological + variable)
Selected AbstractsThe influence of mesoscale ocean processes on anchovy (Engraulis encrasicolus) recruitment in the Bay of Biscay estimated with a three-dimensional hydrodynamic modeFISHERIES OCEANOGRAPHY, Issue 2 2001G. Allain The relationship between anchovy (Engraulis encrasicolus) recruitment in the Bay of Biscay and environmental variables during their planktonic phase (March to July) was investigated from 1986 to 1997. Meteorological variables (wind and temperature) are forcing effects on the sea, but they are not thought to be processes that govern larval survival directly. Food-web dynamics are believed to be more closely linked to larval survival and are related to the physical vertical water column structure. Therefore, we used a three-dimensional (3D) hydrodynamic model to characterize three major physical mesoscale processes affecting vertical structure in south-east Biscay: stratification, upwelling and river plume extent. Indices were estimated from the model outputs to characterize and quantify the space/time evolution of these structures during the period March to July. A multiple linear regression analysis was then used to analyse hierarchy in the explanatory power of the physical indices. Coastal upwelling and shelf stratification breakdown indices were the most significant explanatory variables, with positive and negative effect on recruitment, respectively. A model with these two indices explains 75% of the recruitment variability of anchovy observed in the period 1987,96. [source] Potentialities of quantile regression to predict ozone concentrationsENVIRONMETRICS, Issue 2 2009S. I. V. Sousa Abstract This paper aims: (i) to analyse the influence of ozone precursors (both meteorological variables and pollutant concentrations) on ozone concentrations at different ozone levels; and (ii) to predict next day hourly ozone concentrations using a new approach based on quantile regression (QR). The performance of this model was compared with multiple linear regressions (MLR) for the three following periods: daylight, night time and all day. QR as proven to be an useful mathematical tool to evidence the heterogeneity of ozone predictor influences at different ozone levels. Such heterogeneity is generally hidden when an ordinary least square regression model is applied. The influence of previous concentrations of ozone and nitrogen monoxide on next day ozone concentrations was higher for lower quantiles. When QR was applied, the wind direction (WD) was found to be significant in the medium quantiles and the relative humidity (RH) in the higher quantiles. On the contrary, using the MLR models, both variables were not statistically significant. Moreover, QR allowed more efficient previsions of extreme values which are very useful once the forecasting of higher concentrations is fundamental to develop strategies for protecting the public health. Copyright © 2008 John Wiley & Sons, Ltd. [source] Spatial-temporal model for ambient air pollutants in the state of KuwaitENVIRONMETRICS, Issue 7 2006Fahimah A. Al-Awadhi Abstract In this paper we consider dynamic Bayesian models for four different pollutants: nitric oxide(NO), carbon monoxide(CO), sulphur dioxide(SO2) and non-methane hydrocarbon (NCH4) recorded daily in six different stations in Kuwait from 1999 to 2002. The structure of the models depends on time, space and pollutants dependencies. The approach strives to incorporate the uncertainty of the covariance structure into simulated models and final inference; therefore, hierarchical Bayesian model is applied. Association between level of pollutants and different meteorological variables, such as wind speed, wind directions, temperature and humidity are considered. The models will decompose into two main components: a deterministic part to represent the observed components term and a stochastic term to represent the unobservable components. Our analysis will start with basic model and gradually increase its complexity. At each stage the efficiency of the model will be measured. The resulting models subsequently are tested by comparing the output terms and by comparing and the predictions with the real observations. Copyright © 2006 John Wiley & Sons, Ltd. [source] Statistical analysis of temperature impact on daily hospital admissions: analysis of data from Udine, ItalyENVIRONMETRICS, Issue 1 2006Francesco Pauli Abstract This article is devoted to the analysis of the relationship between the health status of an urban population and meteorological variables. The analysis considers daily number of hospital admissions, not due to surgery, regarding the population resident in the Municipality of Udine, aged 75 and over. Hourly records on temperature, humidity, rain, atmospheric pressure, solar radiation, wind velocity and direction recorded at an observation site located near the center of Udine are considered. The study also considers hourly measures of pollutant concentrations collected by six monitoring stations. All data are relative to the summer periods of years 1995,2003. Generalized additive models (GAM) are used in which the response variable is the number of hospital admissions and is assumed to be distributed as a Poisson whose rate varies as a possibly non-linear function of the meteorological variables and variables allowing for calendar effects and pollutant concentrations. The subsequent part of the analysis explores the distribution of temperature conditional on the number of daily admissions through quantile regression. A non-linear (N-shaped) relationship between hospital admissions and temperature is estimated; temperature at 07:00 is selected as a covariate, revealing that nighttime temperature is more relevant than daytime. The quantile regression analysis points out, as expected, that the distribution of temperature on days with more admissions has higher q -quantiles with q near unity, while a clear-cut conclusion is not reached for q quantiles with q near 0. Copyright © 2005 John Wiley & Sons, Ltd. [source] Is there a connection between weather at departure sites, onset of migration and timing of soaring-bird autumn migration in Israel?GLOBAL ECOLOGY, Issue 6 2006Judy Shamoun-Baranes ABSTRACT Aims, Different aspects of soaring-bird migration are influenced by weather. However, the relationship between weather and the onset of soaring-bird migration, particularly in autumn, is not clear. Although long-term migration counts are often unavailable near the breeding areas of many soaring birds in the western Palaearctic, soaring-bird migration has been systematically monitored in Israel, a region where populations from large geographical areas converge. This study tests several fundamental hypotheses regarding the onset of migration and explores the connection between weather, migration onset and arrival at a distant site. Location, Globally gridded meteorological data from the breeding areas in north-eastern Europe were used as predictive variables in relation to the arrival of soaring migrants in Israel. Methods, Inverse modelling was used to study the temporal and spatial influence of weather on initiation of migration based on autumn soaring-bird migration counts in Israel. Numerous combinations of migration duration and temporal influence of meteorological variables (temperature, sea-level pressure and precipitable water) were tested with different models for meteorological sensitivity. Results, The day of arrival in Israel of white storks, honey buzzards, Levant sparrowhawks and lesser spotted eagles was significantly and strongly related to meteorological conditions in the breeding area days or even weeks before arrival in Israel. The cumulative number of days or cumulative value above or below a meteorological threshold performed significantly better than other models tested. Models provided reliable estimates of migration duration for each species. Main conclusions, The meteorological triggers of migration at the breeding grounds differed between species and were related to deteriorating living conditions and deteriorating migratory flight conditions. Soaring birds are sensitive to meteorological triggers at the same period every year and their temporal response to weather appears to be constrained by their annual routine. [source] Nutritional quality of semi-arid grassland in western Spain over a 10-year period: changes in chemical composition of grasses, legumes and forbsGRASS & FORAGE SCIENCE, Issue 3 2000Vázquez-de-Aldana From 1987 to 1996, the nutritional quality of the main botanical components (grasses, legumes and forbs) in semi-arid grasslands in the dehesa ecosystem in western Spain was analysed. Herbage samples were collected at the end of spring, in 30 locations, at two different topographic positions (upper and lower slope zones). Herbage mass over 2 cm and proportion of botanical components were estimated and samples were analysed for crude protein, neutral-detergent fibre (NDF), hemicellulose, cellulose, lignin and in vitro dry matter digestibility (DMD). Analysis of variance revealed a significant effect of sampling year on the herbage mass, proportion of botanical components and their nutritional quality. The three botanical groups, grasses, legumes and forbs, followed similar year-to-year trends in their crude protein, cellulose and lignin contents and in vitro DMD. Herbage mass was not significantly related to any meteorological variables, suggesting that interannual variation in biomass production of botanically complex pastures cannot be explained by a single factor. However, annual precipitation was significantly related to the proportion of the botanical group that was dominant at each slope zone: grasses in the lower zone and forbs in the upper zone. In the upper zone, spring precipitation explained part of the interannual variation in the NDF, cellulose, lignin contents and in vitro DMD of the botanical components. [source] Direct and indirect methods to simulate the actual evapotranspiration of an irrigated overhead table grape vineyard under Mediterranean conditionsHYDROLOGICAL PROCESSES, Issue 2 2008Gianfranco Rana Abstract Two methods, indirect and direct, for simulating the actual evapotranspiration (E) were applied to an irrigated overhead table grape vineyard during summer, situated in the Mediterranean region (south Italy), over two successive years. The first method, indirect but more practical, uses the crop coefficient (Kc) approach and requires determination of the reference evapotranspiration E0 (FAO (Food and Agriculture Organization) method). This method underestimated on average by 17% the daily values of the actual evapotranspiration E. The analysis in this paper shows that the values of Kc for the table grapes determined by the FAO method seem to not be valid in our experimental conditions. Similar conclusions can be found in the literature for the table grape cultivated under different experimental conditions and using different training systems. The second method, is a direct method for estimating the evapotranspiration. It requires development of a model for the overhead table grape vineyard E, following the Penman,Monteith one-step approach, and using standard meteorological variables as inputs for the determination of the canopy resistance. This method, which needs a particularly simple calibration, provided a better simulation of the hourly and daily evapotranspiration than the indirect method. In additon, the standard error of the daily values for the direct method ( ± 0 · 41 mm) was about 50% lower than that obtained for the indirect method, also when the indirect method used a locally calibrated coefficient Kc instead of a generic Kc. Both, for practical application and theoretical issues, the advantages and disadvantages linked to the use of each tested method are discussed in detail. Copyright © 2007 John Wiley & Sons, Ltd. [source] Application of the distributed hydrology soil vegetation model to Redfish Creek, British Columbia: model evaluation using internal catchment dataHYDROLOGICAL PROCESSES, Issue 2 2003Andrew Whitaker Abstract The Distributed Hydrology Soil Vegetation Model is applied to the Redfish Creek catchment to investigate the suitability of this model for simulation of forested mountainous watersheds in interior British Columbia and other high-latitude and high-altitude areas. On-site meteorological data and GIS information on terrain parameters, forest cover, and soil cover are used to specify model input. A stepwise approach is taken in calibrating the model, in which snow accumulation and melt parameters for clear-cut and forested areas were optimized independent of runoff production parameters. The calibrated model performs well in reproducing year-to-year variability in the outflow hydrograph, including peak flows. In the subsequent model performance evaluation for simulation of catchment processes, emphasis is put on elevation and temporal differences in snow accumulation and melt, spatial patterns of snowline retreat, water table depth, and internal runoff generation, using internal catchment data as much as possible. Although the overall model performance based on these criteria is found to be good, some issues regarding the simulation of internal catchment processes remain. These issues are related to the distribution of meteorological variables over the catchment and a lack of information on spatial variability in soil properties and soil saturation patterns. Present data limitations for testing internal model accuracy serve to guide future data collection at Redfish Creek. This study also illustrates the challenges that need to be overcome before distributed physically based hydrologic models can be used for simulating catchments with fewer data resources. Copyright © 2003 John Wiley & Sons, Ltd. [source] Quantifying random measurement errors in Voluntary Observing Ships' meteorological observationsINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 7 2005Elizabeth C. Kent Abstract Estimates of the random measurement error contained in surface meteorological observations from Voluntary Observing Ships (VOS) have been made on a 30° area grid each month for the period 1970 to 2002. Random measurement errors are calculated for all the basic meteorological variables: surface pressure, wind speed, air temperature, humidity and sea-surface temperature. The random errors vary with space and time, the quality assurance applied and the types of instrument used to make the observations. The estimates of random measurement error are compared with estimates of total observational error, which includes uncertainty due both to measurement errors and to observational sampling. In tropical regions the measurement error makes a significant contribution to the total observational error in a single observation, but in higher latitudes the sampling error can be much larger. Copyright © 2005 Royal Meteorological Society [source] Estimating Long-term Trends in Tropospheric Ozone LevelsINTERNATIONAL STATISTICAL REVIEW, Issue 1 2002Michael Smith Summary This paper develops Bayesian methodology for estimating long-term trends in the daily maxima of tropospheric ozone. The methods are then applied to study long-term trends in ozone at six monitoring sites in the state of Texas. The methodology controls for the effects of meteorological variables because it is known that variables such as temperature, wind speed and humidity substantially affect the formation of tropospheric ozone. A semiparametric regression model is estimated in which a nonparametric trivariate surface is used to model the relationship between ozone and these meteorological variables because, while it is known that the relatinship is a complex nonlinear one, its functional form is unknown. The model also allows for the effects of wind direction and seasonality. The errors are modeled as an autoregression, which is methodologically challenging because the observations are unequally spaced over time. Each function in the model is represented as a linear combination of basis functions located at all of the design points. We also estimate an appropriate data transformation simulataneously with the functions. The functions are estimated nonparametrically by a Bayesian hierarchical model that uses indicator variables to allow a non-zero probability that the coefficient of each basis term is zero. The entire model, including the nonparametric surfaces, data transformation and autoregression for the unequally spaced errors, is estimated using a Markov chain Monte Carlo sampling scheme with a computationally efficient transition kernel for generating the indicator variables. The empirical results indicate that key meteorological variables explain most of the variation in daily ozone maxima through a nonlinear interaction and that their effects are consistent across the six sites. However, the estimated trends vary considerably from site to site, even within the same city. [source] Climate change may account for the decline in British ring ouzels Turdus torquatusJOURNAL OF ANIMAL ECOLOGY, Issue 3 2006COLIN M. BEALE Summary 1Climate change is already affecting biodiversity, but the number of species for which reliable models relate weather and climate to demographic parameters is low. 2We modelled the effect of temperature and rainfall on the breeding success and territory occupancy of ring ouzels Turdus torquatus (L.) in northern Britain, using data from a range of study areas, including one where there was a long-term decline in ring ouzel abundance. 3Timing of breeding was significantly related to meteorological variables affecting birds in the early spring, though there was no evidence that laying dates had advanced. Breeding success was not significantly related to weather variables; instead, over 90% of annual variation in this parameter could be explained by density dependence. 4Annual change in territory occupancy was linked to rainfall and temperature the preceding summer, after the main breeding season and to rainfall in the wintering grounds 24 months previously, coincident with the period of juniper Juniperus sp. (L.) flowering. High temperature in late summer, intermediate levels of late summer rainfall, and high spring rainfall in Morocco 24 months previously all had negative impacts on territory occupancy the following year. 5All three weather variables have changed over recent decades, with a significant increase in summer temperature, a significant decrease in summer rainfall, and a nonsignificant decline in Moroccan spring rainfall. A model based on these trends alone predicted an annual decline in occupancy of 3·6% (compared with an observed decline of 1·2%), and suggested that increased summer temperatures may underlie declines in the British ring ouzel population. 6Changes in summer temperature after the main breeding period could affect the survival rates of adult and/or juvenile birds. An improved understanding of the post-breeding ecology of ring ouzels is required to elucidate the mechanisms and causes of this relationship. Such knowledge might allow management aimed at buffering the impacts of climate change on ring ouzels. [source] Effect of autumn and winter meteorological variables on spring aphid populations in the Po valley, Northern ItalyJOURNAL OF APPLIED ENTOMOLOGY, Issue 8 2001D. Rongai Prediction of aphid populations is crucial to the successful application of control strategies. In previous studies clear relationships between aphid catches and meteorological variables were highlighted. The primary objective of this study was to quantify the effects of autumn and winter meteorological variables on the aphid species populations the following spring. The data on all the species caught at two Italian sites (Ozzano Emilia and Budrio) up to 31 May from 1992 to 1999 were used for this study. Different models were found according to the aphid biological cycle (i.e. holocycle, anholocycle, holo-anholocycle). A fourth group of minor species, designated as ,others', was properly modelled as holo-anholocycle species. A satisfactory fit was observed when holocycle species were plotted against minimum temperature and precipitation in October, anholocycle species against minimum temperature and precipitation in December,January, holo-anholocycle species and ,others' against wind speed and number of frosty days in November, and minimum temperature and precipitation in December,January. Model response was more consistent at Budrio (open flat site) than at Ozzano Emilia (flat site delimited by a hill). A coherent pattern was found with an overall comparison of the estimates against observations. The possibility offered by these empirical models for forecasting spring aphid populations of all species at a given site is clearly of interest. This first study encouraged further investigation aimed at validating models before applying them in practice. [source] Layers of nocturnal insect migrants at high-altitude: the influence of atmospheric conditions on their formationAGRICULTURAL AND FOREST ENTOMOLOGY, Issue 1 2010Curtis R. Wood 1Radar studies of nocturnal insect migration have often found that the migrants tend to form well-defined horizontal layers at a particular altitude. 2In previous short-term studies, nocturnal layers were usually observed to occur at the same altitude as certain meteorological features, most notably at the altitudes of temperature inversion tops or nocturnal wind jets. 3Statistical analyses are presented of 4 years of data that compared the presence, sharpness and duration of nocturnal layer profiles, observed using continuously-operating entomological radar, with meteorological variables at typical layer altitudes over the U.K. 4Analysis of these large datasets demonstrated that temperature was the foremost meteorological factor that was persistently associated with the presence and formation of longer-lasting and sharper layers of migrating insects over southern U.K. [source] A new algorithm to estimate aircraft icing in the HIRLAM modelMETEOROLOGICAL APPLICATIONS, Issue 2 2003Bernt Olofsson A new index to estimate aircraft icing in clouds from operational meteorological models has been developed by Swedish meteorologists. Although rather simple it takes into account, directly or indirectly, all the principal meteorological variables for icing. The index has been evaluated during three winter seasons and is now operational in the Swedish HIRLAM model. A graphical representation of the index is presented. Copyright © 2003 Royal Meteorological Society [source] Slipperiness on roads ,an expert system classificationMETEOROLOGICAL APPLICATIONS, Issue 1 2000Jonas Norrman A method for classifying different types of slipperiness on roads in Sweden is described. Using this method it is possible to survey road conditions in different areas and between different years to optimise winter road maintenance. Winter road maintenance in Sweden is generally undertaken by the national road administration to improve winter-time road conditions, thereby keeping up the traffic flow and decreasing the accident rate. As a number of different types of slipperiness may develop on roads in winter, each due to a specific set of meteorological variables, maintenance work can be a complicated task. With the proposed classification method it becomes easier for the winter maintenance personnel to analyse information on road conditions and survey the distribution of road slipperiness in a region. The classification is performed with an expert system using meteorological data from the Swedish Road Weather Information System. The road condition is classified as good or as one out of ten different types of slipperiness on roads. Road conditions during three different winter periods are analysed. The results show that variations in climate produce substantial differences in annual road condition characteristics. The output from the expert system classifying road slipperiness is compared with recorded winter road maintenance reports. Maintenance action took place on 49% of all occasions when road conditions were classified as slippery. Copyright © 2000 Royal Meteorological Society [source] Predicting moisture dynamics of fine understory fuels in a moist tropical rainforest system: results of a pilot study undertaken to identify proxy variables useful for rating fire dangerNEW PHYTOLOGIST, Issue 3 2010David Ray Summary ,The use of fire as a land management tool in the moist tropics often has the unintended consequence of degrading adjacent forest, particularly during severe droughts. Reliable models of fire danger are needed to help mitigate these impacts. ,Here, we studied the moisture dynamics of fine understory fuels in the east-central Brazilian Amazon during the 2003 dry season. Drying stations established under varying amounts of canopy cover (leaf area index (LAI) = 0 , 5.3) were subjected to a range of water inputs (5,15 mm) and models were developed to forecast litter moisture content (LMC). Predictions were then compared with independent field data. ,A multiple linear regression relating litter moisture content to forest structure (LAI), ambient vapor pressure deficit (VPDM) and an index of elapsed time since a precipitation event (d,1) was identified as the best-fit model (adjusted R2 = 0.89). Relative to the independent observations, model predictions were relatively unbiased when the LMC was , 50%, but consistently underestimated the LMC when the observed values were higher. ,The approach to predicting fire danger based on forest structure and meteorological variables is promising; however, additional information to the LAI, for example forest biomass, may be required to accurately capture the influence of forest structure on understory microclimate. [source] Sensitivity analyses for four pesticide leaching modelsPEST MANAGEMENT SCIENCE (FORMERLY: PESTICIDE SCIENCE), Issue 9 2003Igor G Dubus Abstract Sensitivity analyses using a one-at-a-time approach were carried out for leaching models which have been widely used for pesticide registration in Europe (PELMO, PRZM, PESTLA and MACRO). Four scenarios were considered for simulation of the leaching of two theoretical pesticides in a sandy loam and a clay loam soil, each with a broad distribution across Europe. Input parameters were varied within bounds reflecting their uncertainty and the influence of these variations on model predictions was investigated for accumulated percolation at 1-m depth and pesticide loading in leachate. Predictions for the base-case scenarios differed between chromatographic models and the preferential flow model MACRO for which large but transient pesticide losses were predicted in the clay loam. Volumes of percolated water predicted by the four models were affected by a small number of input parameters and to a small extent only, suggesting that meteorological variables will be the main drivers of water balance predictions. In contrast to percolation, predictions for pesticide loss were found to be sensitive to a large number of input parameters and to a much greater extent. Parameters which had the largest influence on the prediction of pesticide loss were generally those related to chemical sorption (Freundlich exponent nf and distribution coefficient Kf) and degradation (either degradation rates or DT50, QTEN value). Nevertheless, a significant influence of soil properties (field capacity, bulk density or parameters defining the boundary between flow domains in MACRO) was also noted in at least one scenario for all models. Large sensitivities were reported for all models, especially PELMO and PRZM, and sensitivity was greater where only limited leaching was simulated. Uncertainty should be addressed in risk assessment procedures for crop-protection products. Copyright © 2003 Society of Chemical Industry [source] Human birth seasonality and sunshineAMERICAN JOURNAL OF HUMAN BIOLOGY, Issue 3 2010David R. CummingsArticle first published online: 20 OCT 200 The environmental light intensity/photoperiod (ELI/PP) hypothesis proposes that the seasonality of human births is primarily associated with seasonal changes in ambient atmospheric luminosity or ELI. This study tests for the presence of increased ELI during the 1 or 2-month period preceding the conceptual month. Monthly birth data for Helsinki, Finland; Kiev, Ukraine; Hanoi, Vietnam; Matlab, Bangladesh; Nashville, Tennessee; Los Angeles, California; Dallas, Texas; Denver, Colorado and Pretoria, South Africa, are correlated (Pearsonian r) to corresponding monthly meteorological data. With the exception of Matlab, birth data are adjusted for conception date, 31-day months, leap years and monthly deviation from an annual mean. Meteorological data are adjusted for a 1,2-month exposure to ELI before conception. From these correlations, Helsinki r = 0.82, Kiev r = 0.80, Hanoi r = 0.93, Matlab r = 0.91, Nashville r = 0.84, Los Angeles r = 0.71, Dallas r = 0.86, Denver r = 0.53, and Pretoria r = ,82. Weakness and strengths of the ELI/PP hypothesis are reviewed using the criteria developed by AB Hill. Substituting meteorological variables for ELI may be a weakness, whereas the specificity of ELI/PP predictions may be a strength. Increased periods of ELI precede increased periods of conceptions. Increased ELI may influence seasonality for chimpanzee, baboon, and humans. Atmospheric pollution may alter the onset of seasonality. Increased ELI may be the initial, but not the singular variable to affect seasonality. Am. J. Hum. Biol., 2010. © 2009 Wiley-Liss, Inc. [source] The importance of weather and agronomic factors for the overwinter survival of yellow rust (Puccinia striiformis) and subsequent disease risk in commercial wheat crops in EnglandANNALS OF APPLIED BIOLOGY, Issue 3 2007P. Gladders Abstract Disease survey data from 4475 randomly selected crops of wheat from England and Wales during 1985,2000 showed that yellow rust was most prevalent in 1988, 1989, 1990, 1998 and 1999. Disease severity on the upper two leaves was low as >95% crops had received foliar fungicides. Factors affecting the presence or absence (incidence) of yellow rust were investigated using random effects logistic regression (general linear mixed model). This enabled crop management (risk) variables for individual crops to be combined with meteorological variables measured at the county level. Two models are presented that analysed the effect of host genotype on incidence either solely through yellow rust resistance rating (Model 1) or by including both resistance rating (fixed effect) and cultivar (fitted as a random term) (Model 2). In both models, the percentage of crops with yellow rust decreased with cultivar disease resistance ratings ,3, the occurrence of severe frosts (<,5°C), use of systemic seed treatment and application of foliar fungicide sprays. There were no significant effects (P < 0.05) of timing of fungicide sprays, previous cropping or summer weather. The use of risk variables associated with overwintering survival may help adjust fungicide inputs to seasonal risk. [source] Exposure to low outdoor temperature in the midtrimester is associated with low birth weightAUSTRALIAN AND NEW ZEALAND JOURNAL OF OBSTETRICS AND GYNAECOLOGY, Issue 6 2004Koray ELTER Abstract Background: Although seasonal variation of birth weight has been reported previously, contributing factors such as the meteorological factor and its specific period of exposure remain unclear. Aim: To investigate the effect of season on birth weight and to determine the meteorological factor and its specific period of exposure which can contribute to any seasonal variation in birth weight. Methods: Retrospective analysis of 3333 singleton live births after 36 completed weeks of pregnancy. Maternal age, parity, route of delivery, sex and individual meteorological variables for the first, second, and third trimesters of each pregnancy were analysed using multiple regression analysis with the birth weight as the dependent variable. Results: A seasonal pattern was observed with lowest birth weights in women who had their last menstrual periods in summer and autumn. Upon multiple regression analysis, sex, parity, mode of delivery, and the temperature which the mother was exposed to in the second trimester were the independent determinants of birth weight. Conclusion: Exposure to low outdoor ambient temperature in the midtrimester can be associated with low birth weight. [source] The role of inter-specific, micro-habitat and climatic factors on the carbon isotope (,13C) variability of a modern leaf assemblage from northern Scandinavia: implications for climate reconstructionBOREAS, Issue 2 2006NEIL J. LOADER To provide a basis for the interpretation of past climatic conditions from Quaternary leaf records, leaf carbon isotope (,13C) results are presented for 12 northern European dwarf-shrub, shrub and tree species growing across a network of 18 sites in northern Scandinavia. The role of micro-habitat (hummock/hollow) on carbon isotope trends is explored in addition to a comparison of the carbon isotope composition of both cellulose and wholeleaf material. The data are also examined against local meteorological variables (temperature, precipitation and vapour pressure deficit) at both species and genus levels. Results exhibit only modest coherence between selected plant species and low-order correlations with external climate forcings consistent with accepted models for carbon isotope fractionation. Potential for the analysis and interpretation of stable isotopic time series may still be identified; however, factors such as inter-plant variability, senescence, diagenesis and homogeneity need to be thoroughly addressed before such an approach may be used for palaeoenvironmental reconstructions. These findings highlight the complexities and limitations of spatial calibration methods. [source] Factors affecting pollination ecology of Quercus anemophilous species in north-west SpainBOTANICAL JOURNAL OF THE LINNEAN SOCIETY, Issue 3 2005F. J. RODRÍGUEZ-RAJO Pollination ecology of Quercus is influenced by meteorological, biotic and genetic factors. This study was undertaken to ascertain the effect induced by these factors on pollen production, release and dispersion. Aerobiological data have been used in recent years as phenological information, because the presence of pollen in the air is the result of flowering across a wide area. The onset of the Quercus pollen season and the atmospheric pollen concentrations during the pollination period in two localities of north-west Spain (Ourense and Santiago) were determined from 1993 to 2001. There were important variations in total annual pollen as a result of meteorological conditions, lenticular galls produced by Neuropterus on catkins and biennial genetic rhythms of pollen production. In order to determine the beginning of flowering, a thermal time model has been used. Chill requirements were around 800 chilling hours (CH) and heat requirements were 953 growth degree days (GDD in °C) in Santiago and 586 GDD in Ourense. Pollen in the air show positive correlation (99% significance) with daily thermal oscillation, maximum and minimum temperatures, and hours of sunshine. Regression analysis with previous days' pollen concentrations explained the high percentage of pollen concentration variability, as meteorological variables do not, on their own, explain pollen production and release. © 2005 The Linnean Society of London, Botanical Journal of the Linnean Society, 2005, 149, 283,297. [source] | ||||||||||||||||||||||||||||