13 resultados para Fish populations -- Data processing
em University of Queensland eSpace - Australia
Resumo:
The World Health Organization (WHO) MONICA Project is a 10-year study monitoring trends and determinants of cardiovascular disease in geographically defined populations. Data were collected from over 100 000 randomly selected participants in two risk factor surveys conducted approximately 5 years apart in 38 populations using standardized protocols. The net effects of changes in the risk factor levels were estimated using risk scores derived from longitudinal studies in the Nordic countries. The prevalence of cigarette smoking decreased among men in most populations, but the trends for women varied. The prevalence of hypertension declined in two-thirds of the populations. Changes in the prevalence of raised total cholesterol were small but highly correlated between the genders (r = 0.8). The prevalence of obesity increased in three-quarters of the populations for men and in more than half of the populations for women. In almost half of the populations there were statistically significant declines in the estimated coronary risk for both men and women, although for Beijing the risk score increased significantly for both genders. The net effect of the changes in the risk factor levels in the 1980s in most of the study populations of the WHO MONICA Project is that the rates of coronary disease are predicted to decline in the 1990s.
Resumo:
Background and purpose Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. Methods and results In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. Conclusions Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.
Resumo:
The colors of 51 species of Hawaiian reef fish have been measured using a spectrometer and therefore can be described in objective terms that are not influenced by the human visual experience. In common with other known reef fish populations, the colors of Hawaiian reef fish occupy spectral positions from 300-800nm; yellow or orange with blue, yellow with black, and black with white are the most frequently combined colors; and there is no link between possession of ultraviolet (UV) reflectance and UV visual sensitivity or the potential for UV visual sensitivity. In contrast to other reef systems, blue, yellow, and orange appear more frequently in Hawaiian reef fish. Based on spectral quality of reflections from fish skin, trends in fish colors can be seen that are indicative of both visually driven selective pressures and chemical or physical constraints on the design of colors. UV-reflecting colors can function as semiprivate communication signals. White or yellow with black form highly contrasting patterns that transmit well through clear water. Labroid fishes display uniquely complex colors but lack the ability to see the UV component that is common in their pigments. Step-shaped spectral curves are usually long-wavelength colors such as yellow or red, and colors with a peak-shaped spectral curves are green, blue, violet, and UV.
Resumo:
There are very few data on trichodinids of freshwater fishes in Australia. 2003 fishes were surveyed across Eastern Australia to investigate the diversity of trichodinids present, to determine which species have been introduced with exotic fishes and to determine the extent to which these species have crossed into native fish Populations. Twenty-one putative trichodinid species were recovered from the 33 fish species examined. Trichodina heterodentata, T. mutabilis and T. reticulata were the exotic species recovered regularly; a single specimen matched a fourth exotic species, T acuta. All four exotic species are redescribed from Australian material. Trichodina heterodentata was recorded from 17 species of fishes, 15 of which were new host records; this species is identified as one of emerging importance in fish parasitology and a list of its known hosts is presented. Two new native species are also described based on silver stained specimens: T cribbi sp. n. from Hypseleotris galii, H. klunzingeri, and Hypseleotris sp. 5; and T. bassonae sp. n. from Selenotoca multifasciata. Trichodina cribbi is characterised by a large circular central inclusion and approximately 28 denticles, which have a blade length slightly greater than the ray length. Trichodina bassonae is characterised by a small, round, central inclusion and approximately 25 denticles, which have straight, non tapering rays that are in line with the leading edge of the denticle blade. It is estimated that the Australian trichodinid fauna may include up to 150 as yet undescribed species and represents a major source of unexplored biodiversity.
Resumo:
The schema of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. Obtaining quickly the appropriate data increases the likelihood that an organization will make good decisions and respond adeptly to challenges. This research presents and validates a methodology for evaluating, ex ante, the relative desirability of alternative instantiations of a model of data. In contrast to prior research, each instantiation is based on a different formal theory. This research theorizes that the instantiation that yields the lowest weighted average query complexity for a representative sample of information requests is the most desirable instantiation for end-user queries. The theory was validated by an experiment that compared end-user performance using an instantiation of a data structure based on the relational model of data with performance using the corresponding instantiation of the data structure based on the object-relational model of data. Complexity was measured using three different Halstead metrics: program length, difficulty, and effort. For a representative sample of queries, the average complexity using each instantiation was calculated. As theorized, end users querying the instantiation with the lower average complexity made fewer semantic errors, i.e., were more effective at composing queries. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
The speculation that climate change may impact on sustainable fish production suggests a need to understand how these effects influence fish catch on a broad scale. With a gross annual value of A$ 2.2 billion, the fishing industry is a significant primary industry in Australia. Many commercially important fish species use estuarine habitats such as mangroves, tidal flats and seagrass beds as nurseries or breeding grounds and have lifecycles correlated to rainfall and temperature patterns. Correlation of catches of mullet (e.g. Mugil cephalus) and barramundi (Lates calcarifer) with rainfall suggests that fisheries may be sensitive to effects of climate change. This work reviews key commercial fish and crustacean species and their link to estuaries and climate parameters. A conceptual model demonstrates ecological and biophysical links of estuarine habitats that influences capture fisheries production. The difficulty involved in explaining the effect of climate change on fisheries arising from the lack of ecological knowledge may be overcome by relating climate parameters with long-term fish catch data. Catch per unit effort (CPUE), rainfall, the Southern Oscillation Index (SOI) and catch time series for specific combinations of climate seasons and regions have been explored and surplus production models applied to Queensland's commercial fish catch data with the program CLIMPROD. Results indicate that up to 30% of Queensland's total fish catch and up to 80% of the barramundi catch variation for specific regions can be explained by rainfall often with a lagged response to rainfall events. Our approach allows an evaluation of the economic consequences of climate parameters on estuarine fisheries. thus highlighting the need to develop forecast models and manage estuaries for future climate chan e impact by adjusting the quota for climate change sensitive species. Different modelling approaches are discussed with respect to their forecast ability. (c) 2006 Elsevier Ltd. All rights reserved.
Resumo:
Although managers consider accurate, timely, and relevant information as critical to the quality of their decisions, evidence of large variations in data quality abounds. Over a period of twelve months, the action research project reported herein attempted to investigate and track data quality initiatives undertaken by the participating organisation. The investigation focused on two types of errors: transaction input errors and processing errors. Whenever the action research initiative identified non-trivial errors, the participating organisation introduced actions to correct the errors and prevent similar errors in the future. Data quality metrics were taken quarterly to measure improvements resulting from the activities undertaken during the action research project. The action research project results indicated that for a mission-critical database to ensure and maintain data quality, commitment to continuous data quality improvement is necessary. Also, communication among all stakeholders is required to ensure common understanding of data quality improvement goals. The action research project found that to further substantially improve data quality, structural changes within the organisation and to the information systems are sometimes necessary. The major goal of the action research study is to increase the level of data quality awareness within all organisations and to motivate them to examine the importance of achieving and maintaining high-quality data.
Resumo:
Even when data repositories exhibit near perfect data quality, users may formulate queries that do not correspond to the information requested. Users’ poor information retrieval performance may arise from either problems understanding of the data models that represent the real world systems, or their query skills. This research focuses on users’ understanding of the data structures, i.e., their ability to map the information request and the data model. The Bunge-Wand-Weber ontology was used to formulate three sets of hypotheses. Two laboratory experiments (one using a small data model and one using a larger data model) tested the effect of ontological clarity on users’ performance when undertaking component, record, and aggregate level tasks. The results indicate for the hypotheses associated with different representations but equivalent semantics that parsimonious data model participants performed better for component level tasks but that ontologically clearer data model participants performed better for record and aggregate level tasks.