936 resultados para Temporal variability


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Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.

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It is well understood that that there is variation inherent in all testing techniques, and that all soil and rock materials also contain some degree of natural variability. Less consideration is normally given to variation associated with natural material heterogeneity within a site, or the relative condition of the material at the time of testing. This paper assesses the impact of spatial and temporal variability upon repeated insitu testing of a residual soil and rock profile present within a single residential site over a full calendar year, and thus range of seasonal conditions. From this repeated testing, the magnitude of spatial and temporal variation due to seasonal conditions has demonstrated that, depending on the selected location and moisture content of the subsurface at the time of testing, up to a 35% variation within the test results can be expected. The results have also demonstrated that the completed insitu test technique has a similarly large measurement and inherent variability error and, for the investigated site, up to a 60% variation in normalised results was observed. From these results, it is recommended that the frequency and timing of insitu tests should be considered when deriving geotechnical design parameters from a limited data set.

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Multi- and intralake datasets of fossil midge assemblages in surface sediments of small shallow lakes in Finland were studied to determine the most important environmental factors explaining trends in midge distribution and abundance. The aim was to develop palaeoenvironmental calibration models for the most important environmental variables for the purpose of reconstructing past environmental conditions. The developed models were applied to three high-resolution fossil midge stratigraphies from southern and eastern Finland to interpret environmental variability over the past 2000 years, with special focus on the Medieval Climate Anomaly (MCA), the Little Ice Age (LIA) and recent anthropogenic changes. The midge-based results were compared with physical properties of the sediment, historical evidence and environmental reconstructions based on diatoms (Bacillariophyta), cladocerans (Crustacea: Cladocera) and tree rings. The results showed that the most important environmental factor controlling midge distribution and abundance along a latitudinal gradient in Finland was the mean July air temperature (TJul). However, when the dataset was environmentally screened to include only pristine lakes, water depth at the sampling site became more important. Furthermore, when the dataset was geographically scaled to southern Finland, hypolimnetic oxygen conditions became the dominant environmental factor. The results from an intralake dataset from eastern Finland showed that the most important environmental factors controlling midge distribution within a lake basin were river contribution, water depth and submerged vegetation patterns. In addition, the results of the intralake dataset showed that the fossil midge assemblages represent fauna that lived in close proximity to the sampling sites, thus enabling the exploration of within-lake gradients in midge assemblages. Importantly, this within-lake heterogeneity in midge assemblages may have effects on midge-based temperature estimations, because samples taken from the deepest point of a lake basin may infer considerably colder temperatures than expected, as shown by the present test results. Therefore, it is suggested here that the samples in fossil midge studies involving shallow boreal lakes should be taken from the sublittoral, where the assemblages are most representative of the whole lake fauna. Transfer functions between midge assemblages and the environmental forcing factors that were significantly related with the assemblages, including mean air TJul, water depth, hypolimnetic oxygen, stream flow and distance to littoral vegetation, were developed using weighted averaging (WA) and weighted averaging-partial least squares (WA-PLS) techniques, which outperformed all the other tested numerical approaches. Application of the models in downcore studies showed mostly consistent trends. Based on the present results, which agreed with previous studies and historical evidence, the Medieval Climate Anomaly between ca. 800 and 1300 AD in eastern Finland was characterized by warm temperature conditions and dry summers, but probably humid winters. The Little Ice Age (LIA) prevailed in southern Finland from ca. 1550 to 1850 AD, with the coldest conditions occurring at ca. 1700 AD, whereas in eastern Finland the cold conditions prevailed over a longer time period, from ca. 1300 until 1900 AD. The recent climatic warming was clearly represented in all of the temperature reconstructions. In the terms of long-term climatology, the present results provide support for the concept that the North Atlantic Oscillation (NAO) index has a positive correlation with winter precipitation and annual temperature and a negative correlation with summer precipitation in eastern Finland. In general, the results indicate a relatively warm climate with dry summers but snowy winters during the MCA and a cool climate with rainy summers and dry winters during the LIA. The results of the present reconstructions and the forthcoming applications of the models can be used in assessments of long-term environmental dynamics to refine the understanding of past environmental reference conditions and natural variability required by environmental scientists, ecologists and policy makers to make decisions concerning the presently occurring global, regional and local changes. The developed midge-based models for temperature, hypolimnetic oxygen, water depth, littoral vegetation shift and stream flow, presented in this thesis, are open for scientific use on request.

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This thesis contains three subject areas concerning particulate matter in urban area air quality: 1) Analysis of the measured concentrations of particulate matter mass concentrations in the Helsinki Metropolitan Area (HMA) in different locations in relation to traffic sources, and at different times of year and day. 2) The evolution of traffic exhaust originated particulate matter number concentrations and sizes in local street scale are studied by a combination of a dispersion model and an aerosol process model. 3) Some situations of high particulate matter concentrations are analysed with regard to their meteorological origins, especially temperature inversion situations, in the HMA and three other European cities. The prediction of the occurrence of meteorological conditions conducive to elevated particulate matter concentrations in the studied cities is examined. The performance of current numerical weather forecasting models in the case of air pollution episode situations is considered. The study of the ambient measurements revealed clear diurnal variation of the PM10 concentrations in the HMA measurement sites, irrespective of the year and the season of the year. The diurnal variation of local vehicular traffic flows seemed to have no substantial correlation with the PM2.5 concentrations, indicating that the PM10 concentrations were originated mainly from local vehicular traffic (direct emissions and suspension), while the PM2.5 concentrations were mostly of regionally and long-range transported origin. The modelling study of traffic exhaust dispersion and transformation showed that the number concentrations of particles originating from street traffic exhaust undergo a substantial change during the first tens of seconds after being emitted from the vehicle tailpipe. The dilution process was shown to dominate total number concentrations. Minimal effect of both condensation and coagulation was seen in the Aitken mode number concentrations. The included air pollution episodes were chosen on the basis of occurrence in either winter or spring, and having at least partly local origin. In the HMA, air pollution episodes were shown to be linked to predominantly stable atmospheric conditions with high atmospheric pressure and low wind speeds in conjunction with relatively low ambient temperatures. For the other European cities studied, the best meteorological predictors for the elevated concentrations of PM10 were shown to be temporal (hourly) evolutions of temperature inversions, stable atmospheric stability and in some cases, wind speed. Concerning the weather prediction during particulate matter related air pollution episodes, the use of the studied models were found to overpredict pollutant dispersion, leading to underprediction of pollutant concentration levels.

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Long-term surveys of entire communities of species are needed to measure fluctuations in natural populations and elucidate the mechanisms driving population dynamics and community assembly. We analysed changes in abundance of over 4000 tree species in 12 forests across the world over periods of 6-28years. Abundance fluctuations in all forests are large and consistent with population dynamics models in which temporal environmental variance plays a central role. At some sites we identify clear environmental drivers, such as fire and drought, that could underlie these patterns, but at other sites there is a need for further research to identify drivers. In addition, cross-site comparisons showed that abundance fluctuations were smaller at species-rich sites, consistent with the idea that stable environmental conditions promote higher diversity. Much community ecology theory emphasises demographic variance and niche stabilisation; we encourage the development of theory in which temporal environmental variance plays a central role.

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Atlantic herring (Clupea harengus) is an ecologically and economically valuable species in many food webs, yet surprisingly little is known about the variation in the nutritional quality of these fish. Atlantic herring collected from 2005 through 2008 from the Bay of Fundy, Canada, were examined for variability in their nutritional quality by using total lipid content (n=889) and fatty acid composition (n=551) as proxies for nutritional value. A significant positive relationship was found between fish length and total lipid content. Atlantic herring also had significantly different fatty acid signatures by age. Fish from 2005 had significantly lower total lipid content than fish from 2006 through 2008, and all years had significantly different fatty acid signatures. Summer fish were significantly fatter than winter fish and had significantly different fatty acid signatures. For all comparisons (ontogenetic, annual, and seasonal) percent concentrations of omega-3, -6, and long-chain monounsaturated fatty acids were the most important for distinguishing between the fatty acid signatures of fish. This study underscores the importance of quantifying variation in prey quality synoptically with prey quantity in food webs over ontogenetic and temporal scales when evaluating the effect of prey nutritional quality on predators and on modeling trophic dynamics.

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King mackerel (Scomberomorus cavalla) are ecologically and economically important scombrids that inhabit U.S. waters of the Gulf of Mexico (GOM) and Atlantic Ocean (Atlantic). Separate migratory groups, or stocks, migrate from eastern GOM and southeastern U.S. Atlantic to south Florida waters where the stocks mix during winter. Currently, all winter landings from a management-defined south Florida mixing zone are attributed to the GOM stock. In this study, the stock composition of winter landings across three south Florida sampling zones was estimated by using stock-specific otolith morphological variables and Fourier harmonics. The mean accuracies of the jackknifed classifications from stepwise linear discriminant function analysis of otolith shape variables ranged from 66−76% for sex-specific models. Estimates of the contribution of the Atlantic stock to winter landings, derived from maximum likelihood stock mixing models, indicated the contribution was highest off southeastern Florida (as high as 82.8% for females in winter 2001−02) and lowest off southwestern Florida (as low as 14.5% for females in winter 2002−03). Overall, results provided evidence that the Atlantic stock contributes a certain, and perhaps a significant (i.e., ≥50%), percentage of landings taken in the management-defined winter mixing zone off south Florida, and the practice of assigning all winter mixing zone landings to the GOM stock should

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A survey of the larval and juvenile fishes associated with the pelagic Sargassum habitat in the South Atlantic Bight and adjacent western Atlantic Ocean was conducted from July 1991 through March 1993. Fishes representing 104 taxonomic categories were identified, including reef fishes, coastal demersal, coastal pelagic, epipelagic and mesopelagic species. The most important families were Balistidae and Carangidae, each represented by 15 species. Species composition, species diversity and abundance varied both seasonally and regionally. Diversity was highest during spring through fall over the outer continental shelf and in the Gulf Stream. Abundance decreased from spring through winter and from the continental shelf into offshore waters. The numbers of fishes and fish biomass were found to be positively correlated with the wet weight of algae in most cases examined. The results of this study will be useful to fisheries managers assessing the potential impacts of commercial Sargassum harvesting in the region.

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Extensive plankton collections were taken during seven September cruises (1990–93) along the inner continental shelf of the northcentral Gulf of Mexico (GOM). Despite the high productivity and availability of food during these cruises, significant small-scale spatial variability was found in larval growth rates for both Atlantic bumper (Chloroscombrus chrysurus, Carangidae) and vermilion snapper (Rhomboplites aurorubens, Lutjanidae). The observed variability in larval growth rates was not correlated with changes in water temperature or associated with conspicuous hydrographic features and suggested the existence of less-recognizable regions where conditions for growth vary. Cruise estimates of mortality coefficients (Z) for larval Atlantic bumper (n=32,241 larvae from six cruises) and vermilion snapper (n= 2581 larvae from four cruises) ranged from 0.20 to 0.37 and 0.19 to 0.29, respectively. Even in a subtropical climate like the GOM, where larval-stage durations may be as short as two weeks, observed variability in growth rates, particularly when combined with small changes in mortality rates, can cause order-of-magnitude differences in cumulative larval survival. To what extent the observed differences in growth rates at small spatial scales are fine-scale “noise” that ultimately is smoothed by larger-scale processes is not known. Future research is needed to further characterize the small-scale variability in growth rates of larvae, particularly with regard to microzooplankton patchiness and the temporal and spatial pattern of potential predators. Small-scale spatial variability in larval growth rates may in fact be the norm, and understanding the implications of this subtle mosaic may help us to better evaluate our ability to partition the causes of recruitment variability.