The gambin model provides a superior fit to species abundance distributions with a single free parameter : evidence, implementation and interpretation

The species abundance distribution (SAD) has been a central focus of community ecology for over fifty years, and is currently the subject of widespread renewed interest. The gambin model has recently been proposed as a model that provides a superior fit to commonly preferred SAD models. It has also been argued that the model's single parameter (α) presents a potentially informative ecological diversity metric, because it summarises the shape of the SAD in a single number. Despite this potential, few empirical tests of the model have been undertaken, perhaps because the necessary methods and software for fitting the model have not existed. Here, we derive a maximum likelihood method to fit the model, and use it to undertake a comprehensive comparative analysis of the fit of the gambin model. The functions and computational code to fit the model are incorporated in a newly developed free-to-download R package (gambin). We test the gambin model using a variety of datasets and compare the fit of the gambin model to fits obtained using the Poisson lognormal, logseries and zero-sum multinomial distributions. We found that gambin almost universally provided a better fit to the data and that the fit was consistent for a variety of sample grain sizes. We demonstrate how α can be used to differentiate intelligibly between community structures of Azorean arthropods sampled in different land use types. We conclude that gambin presents a flexible model capable of fitting a wide variety of observed SAD data, while providing a useful index of SAD form in its single fitted parameter. As such, gambin has wide potential applicability in the study of SADs, and ecology more generally.

O financiamento da economia dos Açores

Dissertação de Mestrado em Ciências Económicas e Empresariais.

Lipid extractions from marine deep-sea invertebrates : modifications to the Bligh & Dyer method to increase lipid yields

The deep-sea environment is difficult to sample, and often only small quantities of samples can be obtained when using less destructive methods than dredging. When working with marine animals that are difficult to sample and with limited quantities of tissue to extract lipids, it is essential to ensure that the used method extracts the maximum possible quantity of lipids. This study evaluates the efficiency of introducing modifications to the method originally described by Bligh & Dyer (1959). This lipid extraction method is broadly used with modifications, although these usually lack proper description and evaluation of increment in lipids. In this study we consider the improvement in terms of amount of lipids extracted by changing the method. Lipid content was determined by gravimetric measurements in eight invertebrates from the deep-sea, including deep-sea hydrothermal vents animals, using three different approaches. Results show increases of 14% to 30% in lipid contents obtained from hydrothermal vent invertebrate tissues and whole animals by placing the samples in methanol for 24 hours before applying the Bligh & Dyer mixture. Efficiency of the extractions using frozen and freeze-dried samples was also compared. For large sponges, the use of lyophilized materials resulted in increases of 3 to 7 times more lipids extracted when compared with extractions using frozen samples.

Caracterização e valorização do recreio balnear

Dissertação de Mestrado, Ciências Económicas e Empresariais, 9 Dezembro de 2015 , Universidade dos Açores.

Students' engagement in school : analyses according to peer victimization and grade, throughout adolescence

8th International Technology, Education and Development Conference, Valencia 10th, 11th and 12th of March, 2014.

Desenvolvimento do método de Índice de Qualidade ("QIM-Quality Index Method") para as lapas (Patella candei e Patella aspera) e estudo das suas condições de transporte

Dissertação de Mestrado, Estudos Integrados dos Oceanos, 15 de Março de 2016, Universidade dos Açores.