Effects of environmental colour on growth of Nile tilapia, Oreochromis niloticus (Linnaeus, 1758), maintained individually or in groups

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Variance heterogeneity for milk yield in Brazilian and Colombian Holstein herds

Heterogeneity of variances for milk yield (MY) was determined for Brazilian and Colombian herds. The herds were grouped as high or low variability within each country, using as criterion the phenotypic standard deviation (PSD) of MY in the contemporary groups of cows, from the first to the sixth calving. Brazilian and Colombian herds with PSD greater than 1,168 kg or 1,012 kg, respectively, were classified as high variability while the herd groups with values lower than those were classified as low variability. The genetic parameters for MY within each herd group were estimated using bivariate analysis in an animal model and the restricted maximum likelihood method with a derivative free algorithm, using 72,280 first lactations of cows, daughters of 1,880 sires. Heterogeneous variances were found, and Brazilian herds with high PSD had the greatest additive and residual genetic variances and heritability coefficients for MY. MY genetic correlation coefficients between herds of high and low variability within each country were 0.96 and 0.93 while between countries they varied from 0.72 to 0.81, suggesting that there was a reclassification of animals in the two countries and also heterogeneity of variances. This phenomenon leads to the questioning of the strategy of imported semen usage and the need to do genetic evaluations to identify sires with greater genetic potential for (sub) tropical environmental conditions.

Tree species composition and environmental relationships in a Neotropical swamp forest in Southeastern Brazil

We examined the relationships between topography, soil properties and tree species composition in a Neotropical swamp forest in southeastern Brazil. Plots were sampled in the forest, encompassing three different soil ground water regimes along the topographical declivity. All non-climbing plant individuals with trunk height >1.3 m were sampled. A canonical correspondence analysis-CCA-of the species-environmental relationships grouped tree species according to drainage and chemical soil conditions. A total of 86 species were found, being 77 species in the inferior, 40 species in the intermediate and 35 species in the superior topographic section. Some species were among the 10 most abundant ones, both in the overall sampled area and in each topographical section, with alternation events occurring only with their abundance position. However, substantial differences in floristic composition between sections were detected in a fine spatial scale, due to higher number of species, diversity index (H′) and species unique (exclusives) in the inferior topographic section. These higher values can be attributed to its higher spatial heterogeneity that included better drained and seasonally waterlogged soils, higher soil fertility and lower acidity. The increase of the soil water saturation and the uniform conditions derived from the superficial water layer has led to a lower number of species and an increase on the palm trees abundance in the intermediate and superior sections. Our results showed that at a small spatial scale niche differentiation must be an important factor related to the increase of the local diversity. The wide distribution of the most abundant species in the studied area and the increase of local diversity corroborate the pattern of distribution of species in larger scales of swamp forests, in which the most abundant species repeat themselves in high densities in different remnants. However, the floristic composition of each remnant is strongly variable, contributing to the increase of regional diversity. © 2008 Springer Science+Business Media B.V.

Application of Reactions Norms in Study of Genotype Environmental Interaction for Milk Yield of Buffaloes

The aim of this study was to estimate genetic parameters for milk yield (MY) in buffaloes using reaction norms. Model included the additive direct effect as random and contemporary group (herd and year of birth) were included as fixed effects and cow age classes (linear) as covariables. The animal additive direct random effect was modeled through linear Legendre polynomials on environment gradient (EG) standardized means. Mean trends were taken into account by a linear regression on Legendre polynomials of environmental group means. Residual variance was modeled trough 6 heterogeneity classes (EG). These classes of residual variance was formed : EG1: mean = 866,93 kg (621,68 kg-1011,76 kg); EG2: mean = 1193,00 kg (1011,76 kg-1251,49 kg); EG3: mean = 1309,37 kg (1251,49 kg -1393,20 kg); EG4: mean = 1497,59 kg (1393,20 kg-1593,53 kg); EG5: mean = 1664,78 kg (1593,53 kg -1727,32kg) e EG6: mean = 1973,85 kg (1727,32 kg -2422,19 kg).(Co) variance functions were estimated by restricted maximum likelihood (REML) using the GIBBS3F90 package. The heritability estimates for MY raised as the environmental gradient increased, varying from 0.20 to 0.40. However, in intermediate to favorable environments, the heritability estimates obtained with Considerable genotype-environment interaction was found for MY using reaction norms. For genetic evaluation of MY is necessary to consider heterogeneity of variances to model the residual variance.

Spatial heterogeneity affecting fish fauna in cascade reservoirs of the Upper Parana Basin, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Environmental suitability of a highly fragmented and heterogeneous landscape for forest bird species in south-eastern Brazil

Assessment of the suitability of anthropogenic landscapes for wildlife species is crucial for setting priorities for biodiversity conservation. This study aimed to analyse the environmental suitability of a highly fragmented region of the Brazilian Atlantic Forest, one of the world's 25 recognized biodiversity hotspots, for forest bird species. Eight forest bird species were selected for the analyses, based on point counts (n = 122) conducted in April-September 2006 and January-March 2009. Six additional variables (landscape diversity, distance from forest and streams, aspect, elevation and slope) were modelled in Maxent for (1) actual and (2) simulated land cover, based on the forest expansion required by existing Brazilian forest legislation. Models were evaluated by bootstrap or jackknife methods and their performance was assessed by AUC, omission error, binomial probability or p value. All predictive models were statistically significant, with high AUC values and low omission errors. A small proportion of the actual landscape (24.41 +/- 6.31%) was suitable for forest bird species. The simulated landscapes lead to an increase of c. 30% in total suitable areas. In average, models predicted a small increase (23.69 +/- 6.95%) in the area of suitable native forest for bird species. Being close to forest increased the environmental suitability of landscapes for all bird species; landscape diversity was also a significant factor for some species. In conclusion, this study demonstrates that species distribution modelling (SDM) successfully predicted bird distribution across a heterogeneous landscape at fine spatial resolution, as all models were biologically relevant and statistically significant. The use of landscape variables as predictors contributed significantly to the results, particularly for species distributions over small extents and at fine scales. This is the first study to evaluate the environmental suitability of the remaining Brazilian Atlantic Forest for bird species in an agricultural landscape, and provides important additional data for regional environmental planning.

Morphological heterogeneity of Paracoccidioides brasiliensis: relevance of the Rho-like GTPase PbCDC42

Paracoccidioides brasiliensis budding pattern and polymorphic growth were previously shown to be closely linked to the expression of PbCDC42 and to influence the pathogenesis of the fungus. In this work we conducted a detailed morphogenetic evaluation of the yeast-forms of 11 different clinical and environmental P. brasiliensis isolates comprising four phylogenetic lineages (S1, PS2, PS3 and Pb01-like), as well as a PbCDC42 knock-down strain. High variations in the shape and size of mother and bud cells of each isolate were observed but we did not find a characteristic morphologic profile for any of the phylogenetic groups. In all isolates studied, the bud size and shape were demonstrated to be highly dependent on the mother cell. Importantly, we found strong correlations between PbCDC42 expression and both the shape of mother and bud cells and the size of the buds in all isolates and the knock-down strain. Our results suggested that PbCDC42 expression can explain approximately 80% of mother and bud cell shape and 19% of bud cell size. This data support PbCDC42 expression level as being a relevant predictor of P. brasiliensis morphology. Altogether, these findings quantitatively describe the polymorphic nature of the P. brasiliensis yeast form and provide additional support for the key role of PbCDC42 expression on yeast cell morphology.

Inter-regional wage differentials with individual heterogeneity: evidence from Brazil

This paper uses administrative data to follow Brazilian workers over time and examine what happens to the inter-regional wage differentials after controlling for unmeasured workers' characteristics that are fixed over time. Since the data allow us to track the same workers over the years, we are in the unusual position of obtaining the individual wages before and after the migration process. As a significant share of workers changed States in the sample period, it is possible to examine to what extent the wage differentials reflect the concentration of high-skilled individuals in some States. The results show that the overall wage variability across States drops to almost one third of its original value and the ranking of the State effects is significantly altered after we take into account the workers' fixed effects. A great deal of the inter-regional differentials, therefore, reflects differences in the average ability of workers across States.

Heterogeneity and time

Although heterogeneity and time are central aspects of economic activity, it was predominantly the Austrian School of economics that emphasized these two aspects. In this paper we argue that the explicit consideration of heterogeneity and time is of increasing importance due to the increasing environmental and resource problems faced by humankind today. It is shown that neo-Austrian capital theory, which revived Austrian ideas employing a formal approach in the 1970s, is not only well suited to address issues of structural change and of accompanying unemployment induced by technical progress but also can be employed for an encompassing ecological-economic analysis demanded by ecological economics. However, complexity, uncertainty, and real ignorance limit the applicability of formal economic analysis. Therefore, we conclude that economic analysis has to be supplemented by considerations of political philosophy. Copyright 2006 American Journal of Economics and Sociology, Inc..

The effect of EU environmental regulation on international trade : restriction of hazardous substance as a trade barrier

In 2003 the Restriction of Hazardous Substances (RoHS) was established in the EU, which limited the trade of machinery, electrical and electronic equipment that have at least one of the substances considered hazardous under RoHS directive. Since countries trading with the EU must comply with this new regulation, it is expected a decrease in value of imports to the EU. In this paper, it is followed the procedures used in Heckman (1979), as well as the extended procedure suggested by Helpman, Melitz, and Rubinstein (2008) to ascertain the effects on the persistence of trade and values of trade.

How does firm heterogeneity information impact the estimation of embodied carbon emissions in Chinese exports?

Using an augmented Chinese input–output table in which information about firm ownership and type of traded goods are explicitly reported, we show that ignoring firm heterogeneity causes embodied CO2 emissions in Chinese exports to be overestimated by 20% at the national level, with huge differences at the sector level, for 2007. This is because different types of firm that are allocated to the same sector of the conventional Chinese input–output table vary greatly in terms of market share, production technology and carbon intensity. This overestimation of export-related carbon emissions would be even higher if it were not for the fact that 80% of CO2 emissions embodied in exports of foreign-owned firms are, in fact, emitted by Chinese-owned firms upstream of the supply chain. The main reason is that the largest CO2 emitter, the electricity sector located upstream in Chinese domestic supply chains, is strongly dominated by Chinese-owned firms with very high carbon intensity.

Leveraging heterogeneity for energy minimization in data centers

Energy consumption in data centers is nowadays a critical objective because of its dramatic environmental and economic impact. Over the last years, several approaches have been proposed to tackle the energy/cost optimization problem, but most of them have failed on providing an analytical model to target both the static and dynamic optimization domains for complex heterogeneous data centers. This paper proposes and solves an optimization problem for the energy-driven configuration of a heterogeneous data center. It also advances in the proposition of a new mechanism for task allocation and distribution of workload. The combination of both approaches outperforms previous published results in the field of energy minimization in heterogeneous data centers and scopes a promising area of research.

Proactive and reactive thermal aware optimization techniques to minimize the environmental impact of data centers

Los Centros de Datos se encuentran actualmente en cualquier sector de la economía mundial. Están compuestos por miles de servidores, dando servicio a los usuarios de forma global, las 24 horas del día y los 365 días del año. Durante los últimos años, las aplicaciones del ámbito de la e-Ciencia, como la e-Salud o las Ciudades Inteligentes han experimentado un desarrollo muy significativo. La necesidad de manejar de forma eficiente las necesidades de cómputo de aplicaciones de nueva generación, junto con la creciente demanda de recursos en aplicaciones tradicionales, han facilitado el rápido crecimiento y la proliferación de los Centros de Datos. El principal inconveniente de este aumento de capacidad ha sido el rápido y dramático incremento del consumo energético de estas infraestructuras. En 2010, la factura eléctrica de los Centros de Datos representaba el 1.3% del consumo eléctrico mundial. Sólo en el año 2012, el consumo de potencia de los Centros de Datos creció un 63%, alcanzando los 38GW. En 2013 se estimó un crecimiento de otro 17%, hasta llegar a los 43GW. Además, los Centros de Datos son responsables de más del 2% del total de emisiones de dióxido de carbono a la atmósfera. Esta tesis doctoral se enfrenta al problema energético proponiendo técnicas proactivas y reactivas conscientes de la temperatura y de la energía, que contribuyen a tener Centros de Datos más eficientes. Este trabajo desarrolla modelos de energía y utiliza el conocimiento sobre la demanda energética de la carga de trabajo a ejecutar y de los recursos de computación y refrigeración del Centro de Datos para optimizar el consumo. Además, los Centros de Datos son considerados como un elemento crucial dentro del marco de la aplicación ejecutada, optimizando no sólo el consumo del Centro de Datos sino el consumo energético global de la aplicación. Los principales componentes del consumo en los Centros de Datos son la potencia de computación utilizada por los equipos de IT, y la refrigeración necesaria para mantener los servidores dentro de un rango de temperatura de trabajo que asegure su correcto funcionamiento. Debido a la relación cúbica entre la velocidad de los ventiladores y el consumo de los mismos, las soluciones basadas en el sobre-aprovisionamiento de aire frío al servidor generalmente tienen como resultado ineficiencias energéticas. Por otro lado, temperaturas más elevadas en el procesador llevan a un consumo de fugas mayor, debido a la relación exponencial del consumo de fugas con la temperatura. Además, las características de la carga de trabajo y las políticas de asignación de recursos tienen un impacto importante en los balances entre corriente de fugas y consumo de refrigeración. La primera gran contribución de este trabajo es el desarrollo de modelos de potencia y temperatura que permiten describes estos balances entre corriente de fugas y refrigeración; así como la propuesta de estrategias para minimizar el consumo del servidor por medio de la asignación conjunta de refrigeración y carga desde una perspectiva multivariable. Cuando escalamos a nivel del Centro de Datos, observamos un comportamiento similar en términos del balance entre corrientes de fugas y refrigeración. Conforme aumenta la temperatura de la sala, mejora la eficiencia de la refrigeración. Sin embargo, este incremente de la temperatura de sala provoca un aumento en la temperatura de la CPU y, por tanto, también del consumo de fugas. Además, la dinámica de la sala tiene un comportamiento muy desigual, no equilibrado, debido a la asignación de carga y a la heterogeneidad en el equipamiento de IT. La segunda contribución de esta tesis es la propuesta de técnicas de asigación conscientes de la temperatura y heterogeneidad que permiten optimizar conjuntamente la asignación de tareas y refrigeración a los servidores. Estas estrategias necesitan estar respaldadas por modelos flexibles, que puedan trabajar en tiempo real, para describir el sistema desde un nivel de abstracción alto. Dentro del ámbito de las aplicaciones de nueva generación, las decisiones tomadas en el nivel de aplicación pueden tener un impacto dramático en el consumo energético de niveles de abstracción menores, como por ejemplo, en el Centro de Datos. Es importante considerar las relaciones entre todos los agentes computacionales implicados en el problema, de forma que puedan cooperar para conseguir el objetivo común de reducir el coste energético global del sistema. La tercera contribución de esta tesis es el desarrollo de optimizaciones energéticas para la aplicación global por medio de la evaluación de los costes de ejecutar parte del procesado necesario en otros niveles de abstracción, que van desde los nodos hasta el Centro de Datos, por medio de técnicas de balanceo de carga. Como resumen, el trabajo presentado en esta tesis lleva a cabo contribuciones en el modelado y optimización consciente del consumo por fugas y la refrigeración de servidores; el modelado de los Centros de Datos y el desarrollo de políticas de asignación conscientes de la heterogeneidad; y desarrolla mecanismos para la optimización energética de aplicaciones de nueva generación desde varios niveles de abstracción. ABSTRACT Data centers are easily found in every sector of the worldwide economy. They consist of tens of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of data centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grew 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, data centers are responsible for more than 2% of total carbon dioxide emissions. This PhD Thesis addresses the energy challenge by proposing proactive and reactive thermal and energy-aware optimization techniques that contribute to place data centers on a more scalable curve. This work develops energy models and uses the knowledge about the energy demand of the workload to be executed and the computational and cooling resources available at data center to optimize energy consumption. Moreover, data centers are considered as a crucial element within their application framework, optimizing not only the energy consumption of the facility, but the global energy consumption of the application. The main contributors to the energy consumption in a data center are the computing power drawn by IT equipment and the cooling power needed to keep the servers within a certain temperature range that ensures safe operation. Because of the cubic relation of fan power with fan speed, solutions based on over-provisioning cold air into the server usually lead to inefficiencies. On the other hand, higher chip temperatures lead to higher leakage power because of the exponential dependence of leakage on temperature. Moreover, workload characteristics as well as allocation policies also have an important impact on the leakage-cooling tradeoffs. The first key contribution of this work is the development of power and temperature models that accurately describe the leakage-cooling tradeoffs at the server level, and the proposal of strategies to minimize server energy via joint cooling and workload management from a multivariate perspective. When scaling to the data center level, a similar behavior in terms of leakage-temperature tradeoffs can be observed. As room temperature raises, the efficiency of data room cooling units improves. However, as we increase room temperature, CPU temperature raises and so does leakage power. Moreover, the thermal dynamics of a data room exhibit unbalanced patterns due to both the workload allocation and the heterogeneity of computing equipment. The second main contribution is the proposal of thermal- and heterogeneity-aware workload management techniques that jointly optimize the allocation of computation and cooling to servers. These strategies need to be backed up by flexible room level models, able to work on runtime, that describe the system from a high level perspective. Within the framework of next-generation applications, decisions taken at this scope can have a dramatical impact on the energy consumption of lower abstraction levels, i.e. the data center facility. It is important to consider the relationships between all the computational agents involved in the problem, so that they can cooperate to achieve the common goal of reducing energy in the overall system. The third main contribution is the energy optimization of the overall application by evaluating the energy costs of performing part of the processing in any of the different abstraction layers, from the node to the data center, via workload management and off-loading techniques. In summary, the work presented in this PhD Thesis, makes contributions on leakage and cooling aware server modeling and optimization, data center thermal modeling and heterogeneityaware data center resource allocation, and develops mechanisms for the energy optimization for next-generation applications from a multi-layer perspective.

Forms and role of the cluster initiatives in fostering innovation in post-industrial regions: A comparative study of environmental clusters in British West Midlands and Spanish Basque country. ACES Working Paper No. 8, August 2008

The objective of this research is to present cluster initiative approaches in post industrial regions characterized by similar economic history and challenges, with additional emphasis on their role in promoting innovation among regional businesses. The research is based on a comparison study of two environmental industry clusters: Environmental Technology Cluster (ET) from British West Midlands and ACLIMA from Spanish Basque Country. The study analyzes clusters' design and their role in fostering innovation based on environment industry clusters. In both regions environmental industry clusters represent strong potential for further dynamic development with grow opportunities driven by legislation introduced at EU, national or regional levels. The paper compares clusters' heterogeneity, goals and priorities, financing schemes, management structure, types of projects, character of private-public partnerships, challenges, as well as clusters' collaboration at regional/national/international levels. Also focus is given on how the clusters enhance innovation and what types of projects are executed by the regions in this field.

Essays on Environmental and Health Economics

Thesis (Ph.D.)--University of Washington, 2016-06