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- Factors influencing recent benthic foraminifera distribution on the Guadiana shelf (Southwestern Iberia)Publication . Mendes, Isabel; Gonzalez, R.; Dias, João M. A.; Lobo, F.J.; Martins, V.Benthic foraminiferal assemblages in 24 sediment surface samples collected at water depths ranging from 9 to 103 m on the continental shelf off Guadiana River were analysed, leading to the identification of a total of 270 species. Cluster analyses performed on species with a relative abundance higher than 5% led to the identification of four assemblages. The shallowest assemblage, down to 12 m water depth, is represented by Ammonia beccarii, Asterigerinata mamila, Eggerelloides scaber, Mississipina concentrica, Planorbulina mediterranensis, Elphidium crispum and Quinqueloculina laevigata. A second assemblage between 12 and 40 m water depth is characterised by Bulimina elongata, Cribrononion gerthi and Nonion fabum. The assemblage between 40 and 95 m water depth is characterised by Bolivina dilatata, Epistominella vitrea, Bulimina aculeata, Bolivina ordinaria, Spiroloxostoma croarae and Nonionella iridea. Finally, below a depth of 95 m on the upper outer shelf, an assemblage exists characterised by Brizalina spathulata, Bulimina marginata, Cassidulina minuta, Brizalina subaenariensis, Cassidulina laevigata and Uvigerina peregrina. The spatial distribution of assemblages is closely associated with sea-bottom sedimentary environments and bathymetry. The number of benthic foraminiferal tests, and the distribution of several nearshore species within the two shallowest assemblages are clearly influenced by the outflow of the Guadiana Estuary and by local hydrodynamic conditions. The deeper water assemblages, on the other hand, were found to be more related to low levels of tidal energy, low oxygen environments associated to fine-grained sediments, and cold-water filaments related to seasonal upwelling.
- When hillclimbers beat genetic algorithms in multimodal optimizationPublication . Lobo, F.J.; Bazargani, MosabThis paper investigates the performance of multistart next ascent hillclimbing and well-known evolutionary algorithms incorporating diversity preservation techniques on instances of the multimodal problem generator. This generator induces a class of problems in the bitstringdomain which is interesting to study from a theoretical perspective in the context of multimodal optimization, as it is a generalization of the classical OneMax and TwoMax functions for an arbitrary number of peaks. An average-case runtime analysis for multistart next ascent hill-climbing is presented for uniformly distributed equal-height instances of this class of problems. It is shown empirically that conventional niching and mating restriction techniques incorporated in an evolutionary algorithm are not sufficient to make them competitive with the hillclimbing strategy. We conjecture the reason for this behaviour is the lack of structure in the space of local optima on instances of this problem class, which makes an optimization algorithm unable to exploit information from one optimum to infer where another optimum might be. When no such structure exist, it seems that the best strategy for discovering all optima is a brute-force one. Overall, our study gives insights with respect to the adequacy of hillclimbers and evolutionary algorithms for multimodal optimization, depending on properties of the fitness landscape.