11 resultados para evolutionary conservation
em SAPIENTIA - Universidade do Algarve - Portugal
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Tese dout., Ciências e Tecnologias das Pescas, Universidade do Algarve, 2007
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Dissertação mest., Gestão da Água e da Costa, Universidade do Algarve, 2008
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Dissertação de mest., Gestão da Água e da Costa, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2010
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One of the crucial problems of fuzzy rule modeling is how to find an optimal or at least a quasi-optimal rule base fro a certain system. In most applications there is no human expert available, or, the result of a human expert's decision is too much subjective and is not reproducible, thus some automatic method to determine the fuzzy rule base must be deployed.
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Dissertação de mest., Aquacultura e Pescas (Pescas), Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2011
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Understanding the genetic composition and mating systems of edge populations provides important insights into the environmental and demographic factors shaping species’ distribution ranges. We analysed samples of the mangrove Avicennia marina from Vietnam, northern Philippines and Australia, with microsatellite markers. We compared genetic diversity and structure in edge (Southeast Asia, and Southern Australia) and core (North and Eastern Australia) populations, and also compared our results with previously published data from core and southern edge populations. Comparisons highlighted significantly reduced gene diversity and higher genetic structure in both margins compared to core populations, which can be attributed to very low effective population size, pollinator scarcity and high environmental pressure at distribution margins. The estimated level of inbreeding was significantly higher in northeastern populations compared to core and southern populations. This suggests that despite the high genetic load usually associated with inbreeding, inbreeding or even selfing may be advantageous in margin habitats due to the possible advantages of reproductive assurance, or local adaptation. The very high level of genetic structure and inbreeding show that populations of A. marina are functioning as independent evolutionary units more than as components of a metapopulation system connected by gene flow. The combinations of those characteristics make these peripheral populations likely to develop local adaptations and therefore to be of particular interest for conservation strategies as well as for adaptation to possible future environmental changes.
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This article outlines the approaches to modeling the distribution of threatened invertebrates using data from atlases, museums and databases. Species Distribution Models (SDMs) are useful for estimating species’ ranges, identifying suitable habitats, and identifying the primary factors affecting species’ distributions. The study tackles the strategies used to obtain SDMs without reliable absence data while exploring their applications for conservation. I examine the conservation status of Copris species and Graellsia isabelae by delimiting their populations and exploring the effectiveness of protected areas. I show that the method of pseudo‐absence selection strongly determines the model obtained, generating different model predictions along the gradient between potential and realized distributions. After assessing the effects of species’ traits and data characteristics on accuracy, I found that species are modeled more accurately when sample sizes are larger, no matter the technique used.
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Marine protected areas (MPAs) have been widely proposed for conservation purposes and as a tool for fisheries management. The Arrábida Marine Park is the first MPA in continental Portugal having a management plan, fully implemented since 2009. The main objective of this study was to evaluate the effect of protection measures on rocky reef fish assemblages and target invertebrates through before-after and control-effect (no-take vs. fished areas) underwater visual surveys and analysis of landings trends. Second, we used surveys before, during and after implementation of the management plan to understand fishers‟ preferences for fishing grounds and adaptation to the new rules, and evaluated the reserve effect through analysis of both ecological responses and fishing effort density. Third, we identified the main oceanographic drivers influencing the structure of reef fish assemblages and predicted the community structure for the last 50 years, in light of climatic change. Overall results suggest positive responses in biomass but not yet in numbers of some commercial species, with no effects on non-target species. The reserve effect is reinforced by the increase in landings of commercial species, despite increased fishing effort density in some areas, especially with octopus traps. Fishing grounds are mainly chosen based on the distribution of target species and associated habitats, but distance to port, weather conditions and safety also influence fishers‟ choices. Moreover, different fisheries respond differently to the protection measures, and within each fishery, individual fishers show distinct strategies, with some operating in a broader area whereas others keep preferred territories. Our results also show that wind stress and temperature are the main oceanographic drivers for rocky reef fish assemblages, with tropicalization of assemblages and polewards movements of species over the last 50 years consistent with temperature trends. We believe this study provides significant lessons for marine conservation and management of coastal systems.
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All systems found in nature exhibit, with different degrees, a nonlinear behavior. To emulate this behavior, classical systems identification techniques use, typically, linear models, for mathematical simplicity. Models inspired by biological principles (artificial neural networks) and linguistically motivated (fuzzy systems), due to their universal approximation property, are becoming alternatives to classical mathematical models. In systems identification, the design of this type of models is an iterative process, requiring, among other steps, the need to identify the model structure, as well as the estimation of the model parameters. This thesis addresses the applicability of gradient-basis algorithms for the parameter estimation phase, and the use of evolutionary algorithms for model structure selection, for the design of neuro-fuzzy systems, i.e., models that offer the transparency property found in fuzzy systems, but use, for their design, algorithms introduced in the context of neural networks. A new methodology, based on the minimization of the integral of the error, and exploiting the parameter separability property typically found in neuro-fuzzy systems, is proposed for parameter estimation. A recent evolutionary technique (bacterial algorithms), based on the natural phenomenon of microbial evolution, is combined with genetic programming, and the resulting algorithm, bacterial programming, advocated for structure determination. Different versions of this evolutionary technique are combined with gradient-based algorithms, solving problems found in fuzzy and neuro-fuzzy design, namely incorporation of a-priori knowledge, gradient algorithms initialization and model complexity reduction.
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Tese de doutoramento, Ciências Biomédicas, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2014
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Tese de Doutoramento, Biologia Molecular, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2001