933 resultados para Spatial and Temporal Pattern
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A study of quantitative characteristics: phytoplankton photosynthesis (Ph), bacterial assimilation of CO2 (BA), total abundance of bacteria (TAB) and organic matter destruction (D) was carried out in waters the Tugur Bay (tidal level fluctuations up to 7 m) in July-August 1990. Calculations were made of integral indices in some parts: Ph -10-630, BA - 8-29, D - 280-1015 and of total primary production (TPP) - 18-652 mg C/(m2 day). According to obtained data and TAB the ecosystem of the Tugur Bay can be regarded as oligotrophic-mesotrophic one. Dependence on spatial and temporal inhomogeneity of primary productional processes on tide-ebb cycles was found. The role of bacterial relations in the ecosystem of the bay was shown. Portion of ?A in TPP varied from 4 to 44% reaching the maximum in desalinated water during the tide-ebb.
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Blue whiting (Micromesistius poutassou, http://www.marinespecies.org/aphia.php?p=taxdetails&id=126439) is a small mesopelagic planktivorous gadoid found throughout the North-East Atlantic. This data contains the results of a model-based analysis of larvae captured by the Continuous Plankton Recorder (CPR) during the period 1951-2005. The observations are analysed using Generalised Additive Models (GAMs) of the the spatial, seasonal and interannual variation in the occurrence of larvae. The best fitting model is chosen using the Aikaike Information Criteria (AIC). The probability of occurrence in the continous plankton recorder is then normalised and converted to a probability distribution function in space (UTM projection Zone 28) and season (day of year). The best fitting model splits the distribution into two separate spawning grounds north and south of a dividing line at 53 N. The probability distribution is therefore normalised in these two regions (ie the space-time integral over each of the two regions is 1). The modelled outputs are on a UTM Zone 28 grid: however, for convenience, the latitude ("lat") and longitude ("lon") of each of these grid points are also included as a variable in the NetCDF file. The assignment of each grid point to either the Northern or Southern component (defined here as north/south of 53 N), is also included as a further variable ("component"). Finally, the day of year ("doy") is stored as the number of days elapsed from and included January 1 (ie doy=1 on January 1) - the year is thereafter divided into 180 grid points.
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Studies of spatial and temporal changes in modern and past sea-ice occurrence may help to understand the processes controlling the recent decrease in Arctic sea-ice cover. Here, we determined concentrations of IP25, a novel biomarker proxy for sea ice developed in recent years, phytoplankton-derived biomarkers (brassicasterol and dinosterol) and terrigenous biomarkers (campesterol and ß-sitosterol) in the surface sediments from the Kara and Laptev seas to estimate modern spatial (seasonal) sea-ice variability and organic-matter sources. C25-HBI dienes and trienes were determined as additional paleoenvironmental proxies in the study area. Furthermore, a combined phytoplankton-IP25 biomarker approach (PIP25 index) is used to reconstruct the modern sea-ice distribution more quantitatively. The terrigenous biomarkers reach maximum concentrations in the coastal zones and estuaries, reflecting the huge discharge by the major rivers Ob, Yenisei and Lena. Maxima in phytoplankton biomarkers indicating increased primary productivity were found in the seasonally ice-free central part of the Kara and Laptev seas. Neither IP25 nor PIP25, however, show a clear and simple correlation with satellite sea-ice distribution in our study area due to the complex environmental conditions in our study area and the transportation process of sea-ice diatom in the water column. Differences in the diene/IP25 and triene/IP25 ratios point to different sources of these HBIs and different environmental conditions. The diene/IP25 ratio seems to correlate positively with sea-surface temperature, while negatively with salinity distributions.
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Signed at end: Theourgos.
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Climatic changes are most pronounced in northern high latitude regions. Yet, there is a paucity of observational data, both spatially and temporally, such that regional-scale dynamics are not fully captured, limiting our ability to make reliable projections. In this study, a group of dynamical downscaling products were created for the period 1950 to 2100 to better understand climate change and its impacts on hydrology, permafrost, and ecosystems at a resolution suitable for northern Alaska. An ERA-interim reanalysis dataset and the Community Earth System Model (CESM) served as the forcing mechanisms in this dynamical downscaling framework, and the Weather Research & Forecast (WRF) model, embedded with an optimization for the Arctic (Polar WRF), served as the Regional Climate Model (RCM). This downscaled output consists of multiple climatic variables (precipitation, temperature, wind speed, dew point temperature, and surface air pressure) for a 10 km grid spacing at three-hour intervals. The modeling products were evaluated and calibrated using a bias-correction approach. The ERA-interim forced WRF (ERA-WRF) produced reasonable climatic variables as a result, yielding a more closely correlated temperature field than precipitation field when long-term monthly climatology was compared with its forcing and observational data. A linear scaling method then further corrected the bias, based on ERA-interim monthly climatology, and bias-corrected ERA-WRF fields were applied as a reference for calibration of both the historical and the projected CESM forced WRF (CESM-WRF) products. Biases, such as, a cold temperature bias during summer and a warm temperature bias during winter as well as a wet bias for annual precipitation that CESM holds over northern Alaska persisted in CESM-WRF runs. The linear scaling of CESM-WRF eventually produced high-resolution downscaling products for the Alaskan North Slope for hydrological and ecological research, together with the calibrated ERA-WRF run, and its capability extends far beyond that. Other climatic research has been proposed, including exploration of historical and projected climatic extreme events and their possible connections to low-frequency sea-atmospheric oscillations, as well as near-surface permafrost degradation and ice regime shifts of lakes. These dynamically downscaled, bias corrected climatic datasets provide improved spatial and temporal resolution data necessary for ongoing modeling efforts in northern Alaska focused on reconstructing and projecting hydrologic changes, ecosystem processes and responses, and permafrost thermal regimes. The dynamical downscaling methods presented in this study can also be used to create more suitable model input datasets for other sub-regions of the Arctic.
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Senior thesis written for Oceanography 445
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-05
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Thesis (Ph.D.)--University of Washington, 2016-06
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Adopting a social identity perspective, the research was designed to examine the interplay between premerger group status and integration pattern in the prediction of responses to a merger. The research employed a 2 (status: high versus low) x 3 (integration pattern: assimilation versus integrational equality versus transformation) between-participants factorial design. We predicted that integration pattern and group status would interact such that the responses of the members of high status group would be most positive under conditions of an assimilation pattern, whereas members of low status groups were expected to favour an integration-equality pattern. After working on a task in small groups, group status was manipulated and the groups worked on a second task. The merger was then announced and the integration pattern was manipulated (e.g., in terms of the logo, location, and decision rules). The main dependent variables were assessed after the merged groups had worked together on a third task. As expected, there was evidence that the effects of group status on responses to the merger were moderated by integration pattern. Field data also indicated that both premerger status and perceived integration pattern influenced employee responses to an organisational merger.
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This study investigated the spatial distribution patterns of three shrimp species, Periclimenes holthuisi, P. brevicarpalis, and Thor amboinensis on the sea anemone Stichodactyla haddoni in the laboratory. Anemones were partitioned into five zones (mouth, inner tentacle, outer tentacle, upper column, and lower column), and shrimp distribution on these zones was determined. Regardless of species, significantly higher numbers of shrimps chose outer tentacles (>40%) over other zones during daytime. Such distribution might be attributed to their feeding practices as these crustaceans clipped and ate parts of the outer tentacles. Periclimenes holthuisi also showed varying temporal distribution patterns on their hosts. At night when anemones contracted their tentacles, shrimp moved in significant numbers from the outer tentacle region either to the column or off the anemones. Shrimps returned to the tentacles during daytime when anemones expanded their tentacles. Thus, spatial and temporal distribution of shrimps depend upon their feeding activities and degree of anemone expansion.
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Hitting a moving target demands that movement is both spatially and temporally accurate. Recent experiments have begun to reveal how performance of such actions depends on the spatial and temporal accuracy requirements of the task. The results suggest a simple strategy for achieving spatiotemporal accuracy using brief, high-speed movements.
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The growth dynamics of green sea turtles resident in four separate foraging grounds of the southern Great Barrier Reef genetic stock were assessed using a nonparametric regression modeling approach. Juveniles recruit to these grounds at the same size, but grow at foraging-ground-dependent rates that result in significant differences in expected size- or age-at-maturity. Mean age-at-maturity was estimated to vary from 25-50 years depending on the ground. This stock comprises mainly the same mtDNA haplotype, so geographic variability might be due to local environmental conditions rather than genetic factors, although the variability was not a function of latitudinal variation in environmental conditions or whether the food stock was seagrass or algae. Temporal variability in growth rates was evident in response to local environmental stochasticity, so geographic variability might be due to local food stock dynamics. Despite such variability, the expected size-specific growth rate function at all grounds displayed a similar nonmonotonic growth pattern with a juvenile growth spurt at 60-70 cm curved carapace length, (CCL) or 15-20 years of age. Sex-specific growth differences were also evident with females tending to grow faster than similar-sized males after the Juvenile growth spurt. It is clear that slow sex-specific growth displaying both spatial and temporal variability and a juvenile growth spurt are distinct growth behaviors of green turtles from this stock.
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Typically linear optical quantum computing (LOQC) models assume that all input photons are completely indistinguishable. In practice there will inevitably be nonidealities associated with the photons and the experimental setup which will introduce a degree of distinguishability between photons. We consider a nondeterministic optical controlled-NOT gate, a fundamental LOQC gate, and examine the effect of temporal and spectral distinguishability on its operation. We also consider the effect of utilizing nonideal photon counters, which have finite bandwidth and time response.