4 resultados para high rainfall areas

em SAPIENTIA - Universidade do Algarve - Portugal


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Tese de doutoramento, Ciências do Mar, da Terra e do Ambiente, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

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The Selvagens Islands are located in the northeastern Atlantic between the Canary Islands and Madeira Island. As a result of their small size, remote location and harsh sea conditions only a few studies have been conducted to describe their marine species diversity. We were able to identify 29 new coastal fish species, an increase of 33% in the ichthyofauna described for these islands (n = 88). There is a prevalence of species with tropical affinities and only 2.3% (n = 2) are endemic to Macaronesia. Considered a stepping-stone colonization vector from the nearest continental shore, as proposed by other authors for this region, the Selvagens Islands host 34.1% of the ichthyofauna described for the much larger Canary Islands (nspecies = 258, submerged area nSelvagensIs. = 2.3%) and 47.3% of the ichthyofauna described for the more distantly located Madeira Island (nspecies = 186, submerged area nSelvagensIs. = 17.9%). Interestingly, 6.8% (n = 6) of the species failed to bridge the gap between the Selvagens Islands and Madeira Island. Data collected so far showed no trend toward an increasing number of species with high dispersal capability. The Selvagens Islands are an example of a high coastal species diversity occurring even in very small areas of the northeastern Atlantic Ocean.

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The high level of unemployment is one of the major problems in most European countries nowadays. Hence, the demand for small area labor market statistics has rapidly increased over the past few years. The Labour Force Survey (LFS) conducted by the Portuguese Statistical Office is the main source of official statistics on the labour market at the macro level (e.g. NUTS2 and national level). However, the LFS was not designed to produce reliable statistics at the micro level (e.g. NUTS3, municipalities or further disaggregate level) due to small sample sizes. Consequently, traditional design-based estimators are not appropriate. A solution to this problem is to consider model-based estimators that "borrow information" from related areas or past samples by using auxiliary information. This paper reviews, under the model-based approach, Best Linear Unbiased Predictors and an estimator based on the posterior predictive distribution of a Hierarchical Bayesian model. The goal of this paper is to analyze the possibility to produce accurate unemployment rate statistics at micro level from the Portuguese LFS using these kinds of stimators. This paper discusses the advantages of using each approach and the viability of its implementation.

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Dissertação de mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015