Produção de biodiesel pelas microalgas Scenedesmus Obliquus e Nannochloropsis sp.: optimização dos processos de pré-tratamento e conversão

Tese de mestrado integrado em Engenharia da Energia e do Ambiente, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2013In the present study the suitability of microalgae Scenedesmus obliquus and Nannochloropsis sp . feedstock for biodiesel production was evaluated. Some pre-treatments for cell rupture of microalgal dry biomass were studied, in particular mechanical (coffee grinder and bead mill), in order to extract the lipid fraction. The results showed that Nannochloropsis sp. and Scenedesmus obliquus had an aproximate lipid content of 35 g/100g ps and 17 g/100g ps, respectively, and that there was no need for a particular pre-treatment for the Scenedesmus obliquus while for Nannochloropsis sp. it was necessary a relatively aggressive grinding. The lipid fraction of Scenedesmus obliquus had an acid value of 8 mgKOH/g and a fatty acid composition dominated by palmitic acid (23%), oleic (37%) and linoleic (14%). For Nannochloropsis sp., the extracted lipids had an acid value of 82 mg KOH/g and the main fatty acids were palmitic acid (33%), palmitoleic (36% ) and oleic (20%). In both cases, it was determined that the lipidic fractions had an unsaponifiable matter content above 95%. The direct transesterification process was also studied for both microalgae and, due to the high acid value, the influence of the volume of methanol, the acid catalyst concentration and reaction time for the Scenedesmus obliquus was evaluated in order to produce FAME. The results showed that it is possible to produce approximately 40 g/100g ps and 18g/100g ps fatty acid methyl esters from Nannochloropsis sp. and the Scenedesmus obliquus, respectively. In order to evaluate the potential for recovery of residual biomass the total lipids, total sugars, protein and minerals content was determined. The results for the Scenedesmus obliquus were 32 g/100g ps, 34 g/100g ps, 18 g/100g ps and 6g/100g ps, respectively, and for the Nannochloropsis sp. 51 g/100g ps , 18 g/100g ps, 8 g/100g ps and 7 g/100g ps, respectively.No presente trabalho avaliou-se a adequabilidade das microalgas Scenedesmus obliquus e Nannochloropsis sp. como matéria-prima para a produção de biodiesel. Estudaram-se alguns pré-tratamentos para a rutura celular da biomassa microalgal seca, nomeadamente mecânicos (moinho de café e de bolas), tendo em vista a extracção da fracção lipídica. Os resultados mostraram que a Nannochloropsis sp. e a Scenedesmus obliquus tinham teores aproximados de 35g/100g ps e 17g/100g ps, respectivamente, não sendo necessário nenhum pré-tratamento em particular para a Scenedesmus obliquus enquanto que para a Nannochloropsis sp. foi preciso uma moagem relativamente agressiva. A fracção lípidica da Scenedesmus obliquus apresentou um índice de acidez de 8 mgKOH/g e uma composição em ácidos gordos dominada pelo ácido palmítico (23%), oleico (37%) e linoleico (14%). Para a Nannochloropsis sp., determinou-se um índice de acidez de 82 mgKOH/g e como principais ácidos gordos o ácido palmítico (32,7%), o palmitoleico (36%) e o oleico (20,4%). Em ambos os casos, determinou-se um teor de matéria saponificável superior a 95%. Estudou-se também o processo de transesterificação directa para as duas microalgas e, face ao elevado índice de acidez, a influência do volume de metanol, da concentração do catalisador ácido e do tempo de reacção para a Scenedesmus obliquus, na produção de ésteres metílicos de ácidos gordos. Os resultados mostraram que é possível produzir ésteres metílicos na ordem de 40 g/100g ps e 18 g/100g ps a partir da Nannochloropsis sp. e da Scenedesmus obliquus, respectivamente. De modo a avaliar o potencial de valorização da biomassa residual, determinou-se o teor de lípidos totais, açúcares totais, proteína e minerais. Os resultados para a Scenedesmus obliquus foram 32 g/100g ps, 34 g/100g ps, 18 g/100g ps e 6 g/100g ps, respectivamente, e para a Nannochloropsis sp. foram 51 g/100g ps, 18 g/100g ps, 8 g/100g ps e 7 g/100g ps, respectivamente

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Mexico ants: incidence and abundance along the Nearctic–Neotropical interface

International audienceto explore different aspects of the population and community research of ants at different spatial scales, and to aid in the establishment of conservation policies and actions. There are no copyright restrictions. Please cite this data paper when using its data for publications or teaching events

Mexico's Ants: Who are They and Where do They Live?

International audienc

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data