998 resultados para Seashore ecology.


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Cover title.

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Sandy shores are known to be extreme ecosystems where the vegetation has evolved many morphological and physiological adaptations for its survival. With the aim of identify possible relationships between the vegetation´s functional diversity with abiotic factors and its corresponding quantification, we collected data on the abundance and richness of the sandy coast vegetation complex in Grande, Anclitas and Caguamas keys. Its flora is largely characterized by the dominance of hemicryptophytes and chamaephytes plants with nanophyllous leaves and displaying dispersal syndromes such as zoochory and anemochory. However, the functional groups´ richness, in the present study, varies from one key to another. Functional diversity is similar between the wet and dry seasons, and its spatial variation is influenced by the interplay of the set of abiotic factors herein studied.

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Mode of access: Internet.

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1. Ecological data sets often use clustered measurements or use repeated sampling in a longitudinal design. Choosing the correct covariance structure is an important step in the analysis of such data, as the covariance describes the degree of similarity among the repeated observations. 2. Three methods for choosing the covariance are: the Akaike information criterion (AIC), the quasi-information criterion (QIC), and the deviance information criterion (DIC). We compared the methods using a simulation study and using a data set that explored effects of forest fragmentation on avian species richness over 15 years. 3. The overall success was 80.6% for the AIC, 29.4% for the QIC and 81.6% for the DIC. For the forest fragmentation study the AIC and DIC selected the unstructured covariance, whereas the QIC selected the simpler autoregressive covariance. Graphical diagnostics suggested that the unstructured covariance was probably correct. 4. We recommend using DIC for selecting the correct covariance structure.

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Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited, or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modeling, assessing detectability or eradication, ecological condition assessments, risk analysis, and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible, and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.

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Bioprospecting is the exploration of biodiversity for new resources of social and commercial value. It is carried out by a wide range of established industries such as pharmaceuticals, manufacturing and agriculture as well as a wide range of comparatively new ones such as aquaculture, bioremediation, biomining, biomimetic engineering and nanotechnology. The benefits of bioprospecting have emerged from such a wide range of organisms and environments worldwide that it is not possible to predict what species or habitats will be critical to society, or industry, in the future. The benefits include an unexpected variety of products that include chemicals, genes, metabolic pathways, structures, materials and behaviours. These may provide physical blueprints or inspiration for new designs. Criticism aimed at bioprospecting has been addressed, in part, by international treaties and legal agreements aimed at stopping biopiracy and many activities are now funded by agencies that require capacity-building and economic benefits in host countries. Thus, much contemporary bioprospecting has multiple goals, including the conservation of biodiversity, the sustainable management of natural resources and economic development. Ecologists are involved in three vital ways: first, applying ecological principles to the discovery of new resources. In this context, natural history becomes a vast economic database. Second, carrying out field studies, most of them demographic, to help regulate the harvest of wild species. Third, emphasizing the profound importance of millions of mostly microscopic species to the global economy.

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The studies in the thesis were derived from a program of research focused on centre-based child care in Australia. The studies constituted an ecological analysis as they examined proximal and distal factors which have the potential to affect children's developmental opportunities (Bronfenbrenner, 1979). The project was conducted in thirty-two child care centres located in south-east Queensland. Participants in the research included staff members at the centres, families using the centres and their children. The first study described the personal and professional characteristics of one hundred and forty-four child care workers, as well as their job satisfaction and job commitment. Factors impinging on the stability of care afforded to children were examined, specifically child care workers' intentions to leave their current position and actual staff turnover at a twelve month follow-up. This is an ecosystem analysis (Bronfenbrenner & Crouter, 1983), as it examined the world of work for carers; a setting not directly involving the developing child, but which has implications for children's experiences. Staff job satisfaction was focused on working with children and other adults, including parents and colleagues. Involvement with children was reported as being the most rewarding aspect of the work. This intrinsic satisfaction was enough to sustain caregivers' efforts to maintain their employment in child care programs. It was found that, while improving working conditions may help to reduce turnover, it is likely that moderate turnover rates will remain as child care staff work in relatively small centres and they leave in order to improve career prospects. Departure from a child care job appeared to be as much about improving career opportunities or changing personal circumstances, as it was about poor wages and working conditions. In the second study, factors that influence maternal satisfaction with child care arrangements were examined. The focus included examination of the nature and qualities of parental interaction with staff. This was a mesosystem analysis (Bronfenbrenner & Crouter, 1983), as it considered the links between family and child care settings. Two hundred and twenty-two questionnaires were returned from mothers whose children were enrolled in the participating centres. It was found that maternal satisfaction with child care encompassed the domains of child-centred and parent-centred satisfaction. The nature and range of responses in the quantitative and qualitative data indicated that these parents were genuinely satisfied with their children's care. In the prediction of maternal satisfaction with child care, single parents, mothers with high role satisfaction, and mothers who were satisfied with the frequency of staff contact and degree of supportive communication had higher levels of satisfaction with their child care arrangements. The third study described the structural and process variations within child care programs and examined program differences for compliance with regulations and differences by profit status of the centre, as a microsystem analysis (Bronfenbrenner, 1979). Observations were made in eighty-three programs which served children from two to five years. The results of the study affirmed beliefs that nonprofit centres are superior in the quality of care provided, although this was not to a level which meant that the care in for-profit centres was inadequate. Regulation of structural features of child care programs, per se, did not guarantee higher quality child care as measured by global or process indicators. The final study represented an integration of a range of influences in child care and family settings which may impact on development. Features of child care programs which predict children's social and cognitive development, while taking into account child and family characteristics, were identified. Results were consistent with other research findings which show that child and family characteristics and child care quality predict children's development. Child care quality was more important to the prediction of social development, while family factors appeared to be more predictive of cognitive/language development. An influential variable predictive of development was the period of time which the child had been in the centre. This highlighted the importance of the stability of child care arrangements. Child care quality features which had most influence were global ratings of the qualities of the program environment. However, results need to be interpreted cautiously as the explained variance in the predictive models developed was low. The results of these studies are discussed in terms of the implications for practice and future research. Considerations for an expanded view of ecological approaches to child care research are outlined. Issues discussed include the need to generate child care research which is relevant to social policy development, the implications of market driven policies for child care services, professionalism and professionalisation of child care work, and the need to reconceptualise child care research when the goal is to develop greater theoretical understanding about child care environments and developmental processes.