Does the (structural) context matter? Analysing individual and structural factors of members’ commitment to sports clubs

Introduction: Over the last decades, Swiss sports clubs have lost their "monopoly" in the market for sports-related services and increasingly are in competition with other sports providers. For many sport clubs long-term membership cannot be seen as a matter of course. Current research on sports clubs in Switzerland – as well as for other European countries – confirms the increasing difficulties in achieving long-term member commitment. Looking at recent findings of the Swiss sport clubs report (Lamprecht, Fischer & Stamm, 2012), it can be noted, that a decrease in memberships does not equally affect all clubs. There are sports clubs – because of their specific situational and structural conditions – that have few problems with member fluctuation, while other clubs show considerable declines in membership. Therefore, a clear understanding of individual and structural factors that trigger and sustain member commitment would help sports clubs to tackle this problem more effectively. This situation poses the question: What are the individual and structural determinants that influence the tendency to continue or to quit the membership? Methods: Existing research has extensively investigated the drivers of members’ commitment at an individual level. As commitment of members usually occurs within an organizational context, the characteristics of the organisation should be also considered. However, this context has been largely neglected in current research. This presentation addresses both the individual characteristics of members and the corresponding structural conditions of sports clubs resulting in a multi-level framework for the investigation of the factors of members’ commitment in sports clubs. The multilevel analysis grant a adequate handling of hierarchically structured data (e.g., Hox, 2002). The influences of both the individual and context level on the stability of memberships are estimated in multi-level models based on a sample of n = 1,434 sport club members from 36 sports clubs. Results: Results of these multi-level analyses indicate that commitment of members is not just an outcome of individual characteristics, such as strong identification with the club, positively perceived communication and cooperation, satisfaction with sports clubs’ offers, or voluntary engagement. It is also influenced by club-specific structural conditions: stable memberships are more probable in rural sports clubs, and in clubs that explicitly support sociability, whereas sporting-success oriented goals in clubs have a destabilizing effect. Discussion/Conclusion: The proposed multi-level framework and the multi-level analysis can open new perspectives for research concerning commitment of members to sports clubs and other topics and problems of sport organisation research, especially in assisting to understand individual behavior within organizational contexts. References: Hox, J. J. (2002). Multilevel analysis: Techniques and applications. Mahwah: Lawrence Erlbaum. Lamprecht, M., Fischer, A., & Stamm, H.-P. (2012). Die Schweizer Sportvereine – Strukturen, Leistungen, Herausforderungen. Zurich: Seismo.

Efficacy of motivational enhancement therapy on alcohol use disorders in patients with chronic hepatitis C: a randomized controlled trial

AIMS: To determine the efficacy of motivational enhancement therapy (MET) on alcohol use in patients with the hepatitis C virus (HCV) and an alcohol use disorder (AUD). DESIGN: Randomized, single-blind, controlled trial comparing MET to a control education condition with 6-month follow-up. SETTING: Patients were recruited from hepatitis clinics at the Minneapolis, Minnesota and Portland, Oregon Veterans Affairs Health Care Systems, USA. PARTICIPANTS AND INTERVENTION: Patients with HCV, an AUD and continued alcohol use (n = 139) were randomized to receive either MET (n = 70) or a control education condition (n = 69) over 3 months. MEASUREMENTS: Data were self-reported percentage of days abstinent from alcohol and number of standard alcohol drinks per week 6 months after randomization. FINDINGS: At baseline, subjects in MET had 34.98% days abstinent, which increased to 73.15% at 6 months compared to 34.63 and 59.49% for the control condition. Multi-level models examined changes in alcohol consumption between MET and control groups. Results showed a significant increase in percentage of days abstinent overall (F(1120.4)  = 28.04, P < 0.001) and a significant group × time effect (F(1119.9)  = 5.23, P = 0.024) with the MET group showing a greater increase in percentage of days abstinent at 6 months compared with the education control condition. There were no significant differences between groups for drinks per week. The effect size of the MET intervention was moderate (0.45) for percentage of days abstinent. CONCLUSION: Motivational enhancement therapy (MET) appears to increase the percentage of days abstinent in patients with chronic hepatitis C, alcohol use disorders and ongoing alcohol use. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Long-term trends in invertebrate–habitat relationships under protected and fished conditions

Few studies examine the long-term effects of changing predator size and abundance on the habitat associations of resident organisms despite that this knowledge is critical to understand the ecosystem effects of fishing. Marine reserves offer the opportunity to determine ecosystem-level effects of manipulated predator densities, while parallel monitoring of adjacent fished areas allows separating these effects from regional-scale change. Relationships between two measures of benthic habitat structure (reef architecture and topographic complexity) and key invertebrate species were followed over 17 years at fished and protected subtidal rocky reefs associated with two southern Australian marine reserves. Two commercially harvested species, the southern rock lobster (Jasus edwardsii) and blacklip abalone (Haliotis rubra) were initially weakly associated with habitat structure across all fished and protected sites. The strength of association with habitat for both species increased markedly at protected sites 2 years after marine reserve declaration, and then gradually weakened over subsequent years. The increasing size of rock lobster within reserves apparently reduced their dependency on reef shelters as refuges from predation. Rising predation by fish and rock lobster in the reserves corresponded with weakening invertebrate–habitat relationships for H. rubra and sea urchins (Heliocidaris erythrogramma). These results emphasise that animal–habitat relationships are not necessarily stable through time and highlight the value of marine reserves as reference sites. Our work shows that fishery closures to enhance populations of commercially important and keystone species should be in areas with a range of habitat features to accommodate shifting ecological requirements with ontogenesis.

Development and voluntarism in football clubs

Volunteers are still the most important resource for amateur football clubs. However, stable voluntary engagement can no longer be granted. This difficulty is confirmed by existing research across various European countries. From a club management point of view, a detailed understanding of how to attract volunteers and retain them is becoming a high priority. The purpose of this study is (1) to analyse the influence of individual characteristics and corresponding organisational conditions on volunteering and (2) to examine the decision-making processes in relation to implement effective strategies for recruiting volunteers. To answer these questions, the current state of research is summarised and then a multi-level-framework is developed which is based on the structural-individualistic social theory. The individual and context factors for volunteering are estimated in different multi-level models based on a sample of n=1,434 sport club members from 36 sport clubs in Switzerland. Results indicate that volunteering is not just an outcome of individual characteristics such as lower workloads, higher income, children belonging to the sport club, longer club membership, or a strong commitment to the club. It is also influenced by club-specific structural conditions. Concerning decision-making processes an in-depth analysis of recruitment practices for volunteers was conducted in selected clubs (case study design). based on the garbage can model. The results show that systematically designed decision-making processes with a clear regulation of responsibilities seem to solve personnel problems more purposefully and more quickly. Based on the findings some recommendations for volunteer management in football clubs are worked out.

ERA-interim reanalysis debiased at FLUXNET sites

(preliminary) Exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 sites registered and up to 250 of them sharing data (Free Fair Use dataset). Many modelling groups use the FLUXNET dataset for evaluating ecosystem model's performances but it requires uninterrupted time series for the meteorological variables used as input. Because original in-situ data often contain gaps, from very short (few hours) up to relatively long (some months), we develop a new and robust method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-interim) and high temporal resolution spanning from 1989 to today. These data are however not measured at site level and for this reason a method to downscale and correct the ERA-interim data is needed. We apply this method on the level 4 data (L4) from the LaThuile collection, freely available after registration under a Fair-Use policy. The performances of the developed method vary across sites and are also function of the meteorological variable. On average overall sites, the bias correction leads to cancel from 10% to 36% of the initial mismatch between in-situ and ERA-interim data, depending of the meteorological variable considered. In comparison to the internal variability of the in-situ data, the root mean square error (RMSE) between the in-situ data and the un-biased ERA-I data remains relatively large (on average overall sites, from 27% to 76% of the standard deviation of in-situ data, depending of the meteorological variable considered). The performance of the method remains low for the Wind Speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.

Relative sensitivity of soft-bottom intertidal macrofauna to increased CO2 and experimental stress

We used a controlled CO2 perturbation experiment to test hypotheses about changes in diversity, composition and structure of soft-bottom intertidal macrobenthic assemblages, under realistic and locally relevant scenarios of seawater acidification. Patches of undisturbed sediment were collected from 2 types of intertidal sedimentary habitat in the Ria Formosa coastal lagoon (South Portugal) and exposed to 2 levels of seawater acidification (pH reduced by 0.3 and 0.6 units) and 1 unmanipulated (control) level. After 75 d the assemblages differed significantly between the 2 types of sediment and between field controls and the ex situ treatments, but not among the 3 pH levels tested. The naturally high values of total alkalinity buffered seawater from the changes imposed on carbonate chemistry and may have contributed to offsetting acidification at the local scale. Observed differences on biota were strongly related to the organic matter content and grain-size of the sediments, particularly to the fractions of medium and coarse sand. Soft-bottom intertidal macrofauna was significantly affected by the stress of being held in an artificial environment, but not by CO2-induced seawater acidification. Given the previously observed variations in the sensitivities of marine organisms to seawater acidification, direct extrapolations of the present findings to different regions or other types of assemblages do not seem advisable. However, the contribution of ex situ studies to the assessment of ecosystem-level responses to environmental disturbances could generally be improved by incorporating adequate field controls in the experimental design.

Seawater carbonate chemistry and benthic marine community during experiments, 2011

Ocean acidification is predicted to impact all areas of the oceans and affect a diversity of marine organisms. However, the diversity of responses among species prevents clear predictions about the impact of acidification at the ecosystem level. Here, we used shallow water CO2 vents in the Mediterranean Sea as a model system to examine emergent ecosystem responses to ocean acidification in rocky reef communities. We assessed in situ benthic invertebrate communities in three distinct pH zones (ambient, low, and extreme low), which differed in both the mean and variability of seawater pH along a continuous gradient. We found fewer taxa, reduced taxonomic evenness, and lower biomass in the extreme low pH zones. However, the number of individuals did not differ among pH zones, suggesting that there is density compensation through population blooms of small acidification-tolerant taxa. Furthermore, the trophic structure of the invertebrate community shifted to fewer trophic groups and dominance by generalists in extreme low pH, suggesting that there may be a simplification of food webs with ocean acidification. Despite high variation in individual species' responses, our findings indicate that ocean acidification decreases the diversity, biomass, and trophic complexity of benthic marine communities. These results suggest that a loss of biodiversity and ecosystem function is expected under extreme acidification scenarios.

Seawater carbonate chemistry and processes during an experiment with coral reef, 2000

The concentration of CO2 in the atmosphere is projected to reach twice the preindustrial level by the middle of the 21st century. This increase will reduce the concentration of [CO3]2- of the surface ocean by 30% relative to the preindustrial level and will reduce the calcium carbonate saturation state of the surface ocean by an equal percentage. Using the large 2650 m3 coral reef mesocosm at the BIOSPHERE-2 facility near Tucson, Arizona, we investigated the effect of the projected changes in seawater carbonate chemistry on the calcification of coral reef organisms at the community scale. Our experimental design was to obtain a long (3.8 years) time series of the net calcification of the complete system and all relevant physical and chemical variables (temperature, salinity, light, nutrients, Ca2+,pCO2, TCO2, and total alkalinity). Periodic additions of NaHCO3, Na2CO3, and/or CaCl2 were made to change the calcium carbonate saturation state of the water. We found that there were consistent and reproducible changes in the rate of calcification in response to our manipulations of the saturation state. We show that the net community calcification rate responds to manipulations in the concentrations of both Ca2+ and [CO3]2- and that the rate is well described as a linear function of the ion concentration product, [Ca2+]0.69[[CO3]2-]. This suggests that saturation state or a closely related quantity is a primary environmental factor that influences calcification on coral reefs at the ecosystem level. We compare the sensitivity of calcification to short-term (days) and long-term (months to years) changes in saturation state and found that the response was not significantly different. This indicates that coral reef organisms do not seem to be able to acclimate to changing saturation state. The predicted decrease in coral reef calcification between the years 1880 and 2065 A.D. based on our long-term results is 40%. Previous small-scale, short-term organismal studies predicted a calcification reduction of 14-30%. This much longer, community-scale study suggests that the impact on coral reefs may be greater than previously suspected. In the next century coral reefs will be less able to cope with rising sea level and other anthropogenic stresses.

Functional consequences of prey acclimation to ocean acidification for the prey and its predator

Ocean acidification is the suite of chemical changes to the carbonate system of seawater as a consequence of anthropogenic carbon dioxide (CO2) emissions. Despite a growing body of evidences demonstrating the negative effects of ocean acidification on marine species, the consequences at the ecosystem level are still unclear. One factor limiting our ability to upscale from species to ecosystem is the poor mechanistic understanding of the functional consequences of the observed effects on organisms. This is particularly true in the context of species interactions. The aim of this work was to investigate the functional consequence of the exposure of a prey (the mussel Brachidontes pharaonis) to ocean acidification for both the prey and its predator (the crab Eriphia verrucosa). Mussels exposed to pH 7.5 for >4 weeks showed significant decreases in condition index and in mechanical properties (65% decrease in maximum breaking load) as compared with mussels acclimated to pH 8.0. This translated into negative consequences for the mussel in presence of the predator crab. The crab feeding efficiency increased through a significant 27% decrease in prey handling time when offered mussels acclimated to the lowest pH. The predator was also negatively impacted by the acclimation of the prey, probably as a consequence of a decreased food quality. When fed with prey acclimated under decreased pH for 3 months, crab assimilation efficiency significantly decreased by 30% and its growth rate was 5 times slower as compared with crab fed with mussels acclimated under high pH. Our results highlight the important to consider physiological endpoints in the context of species interactions.

Effects of ocean acidification on Posidonia oceanica epiphytic community and shoot productivity

1. Biological interactions can alter predictions that are based on single-species physiological response. It is known that leaf segments of the seagrass Posidonia oceanica will increase photosynthesis with lowered pH, but it is not clear whether the outcome will be altered when the whole plant and its epiphyte community, with different respiratory and photosynthetic demands, are included. In addition, the effects on the Posidonia epiphyte community have rarely been tested under controlled conditions, at near-future pH levels. 2. In order to better evaluate the effects of pH levels as projected for the upcoming decades on seagrass meadows, shoots of P. oceanica with their associated epiphytes were exposed in the laboratory to three pH levels (ambient: 8.1, 7.7 and 7.3, on the total scale) for 4 weeks. Net productivity, respiration, net calcification and leaf fluorescence were measured on several occasions. At the end of the study, epiphyte community abundance and composition, calcareous mass and crustose coralline algae growth were determined. Finally, photosynthesis vs. irradiance curves (PE) was produced from segments of secondary leaves cleaned of epiphytes and pigments extracted. 3. Posidonia leaf fluorescence and chlorophyll concentrations did not differ between pH treatments. Net productivity of entire shoots and epiphyte-free secondary leaves increased significantly at the lowest pH level yet limited or no stimulation in productivity was observed at the intermediate pH treatment. Under both pH treatments, significant decreases in epiphytic cover were observed, mostly due to the reduction of crustose coralline algae. The loss of the dominant epiphyte producer yet similar photosynthetic response for epiphyte-free secondary leaves and shoots suggests a minimal contribution of epiphytes to shoot productivity under experimental conditions. 4. Synthesis. Observed responses indicate that under future ocean acidification conditions foreseen in the next century an increase in Posidonia productivity is not likely despite the partial loss of epiphytic coralline algae which are competitors for light. A decline in epiphytic cover could, however, reduce the feeding capacity of the meadow for invertebrates. In situ long-term experiments that consider both acidification and warming scenarios are needed to improve ecosystem-level predictions.

Estimación de variables dasométricas a partir de datos LiDAR y obtención de modelos de referencia para las distribuciones de alturas y diámetros del arbolado

La Gestión Forestal Sostenible se define como “la administración y uso de los bosques y tierras forestales de forma e intensidad tales que mantengan su biodiversidad, productividad, capacidad de regeneración, vitalidad y su potencial para atender, ahora y en el futuro, las funciones ecológicas, económicas y sociales relevantes a escala local, nacional y global, y que no causan daño a otros ecosistemas” (MCPFE Conference, 1993). Dentro del proceso los procesos de planificación, en cualquier escala, es necesario establecer cuál será la situación a la que se quiere llegar mediante la gestión. Igualmente, será necesario conocer la situación actual, pues marcará la situación de partida y condicionará el tipo de actuaciones a realizar para alcanzar los objetivos fijados. Dado que, los Proyectos de Ordenación de Montes y sus respectivas revisiones son herramientas de planificación, durante la redacción de los mismos, será necesario establecer una serie de objetivos cuya consecución pueda verificarse de forma objetiva y disponer de una caracterización de la masa forestal que permita conocer la situación de partida. Esta tesis se centra en problemas prácticos, propios de una escala de planificación local o de Proyecto de Ordenación de Montes. El primer objetivo de la tesis es determinar distribuciones diamétricas y de alturas de referencia para masas regulares por bosquetes, empleando para ello el modelo conceptual propuesto por García-Abril et al., (1999) y datos procedentes de las Tablas de producción de Rojo y Montero (1996). Las distribuciones de referencia obtenidas permitirán guiar la gestión de masas irregulares y regulares por bosquetes. Ambos tipos de masas aparecen como una alternativa deseable en aquellos casos en los que se quiere potenciar la biodiversidad, la estabilidad, la multifuncionalidad del bosque y/o como alternativa productiva, especialmente indicada para la producción de madera de calidad. El segundo objetivo de la Tesis está relacionado con la necesidad de disponer de una caracterización adecuada de la masa forestal durante la redacción de los Proyectos de Ordenación de Montes y de sus respectivas revisiones. Con el fin de obtener estimaciones de variables forestales en distintas unidades territoriales de potencial interés para la Ordenación de Montes, así como medidas de la incertidumbre en asociada dichas estimaciones, se extienden ciertos resultados de la literatura de Estimación en Áreas Pequeñas. Mediante un caso de estudio, se demuestra el potencial de aplicación de estas técnicas en inventario forestales asistidos con información auxiliar procedente de sensores láser aerotransportados (ALS). Los casos de estudio se realizan empleando datos ALS similares a los recopilados en el marco del Plan Nacional de Ortofotografía Aérea (PNOA). Los resultados obtenidos muestran que es posible aumentar la eficiencia de los inventarios forestales tradicionales a escala de proyecto de Ordenación de Montes, mediante la aplicación de estimadores EBLUP (Empirical Best Linear Unbiased Predictor) con modelos a nivel de elemento poblacional e información auxiliar ALS similar a la recopilada por el PNOA. ABSTRACT According to MCPFE (1993) Sustainable Forest Management is “the stewardship and use of forests and forest lands in a way, and at a rate, that maintains their biodiversity, productivity, regeneration capacity, vitality and their potential to fulfill, now and in the future, relevant ecological, economic and social functions, at local, national, and global levels, and that does not cause damage to other ecosystems”. For forest management planning, at any scale, we must determine what situation is hoped to be achieved through management. It is also necessary to know the current situation, as this will mark the starting point and condition the type of actions to be performed in order to meet the desired objectives. Forest management at a local scale is no exception. This Thesis focuses on typical problems of forest management planning at a local scale. The first objective of this Thesis is to determine management objectives for group shelterwood management systems in terms of tree height and tree diameter reference distributions. For this purpose, the conceptual model proposed by García-Abril et al., (1999) is applied to the yield tables for Pinus sylvestris in Sierra de Guadrrama (Rojo y Montero, 1996). The resulting reference distributions will act as a guide in the management of forests treated under the group shelterwood management systems or as an approximated reference for the management of uneven aged forests. Both types of management systems are desirable in those cases where forest biodiversity, stability and multifunctionality are pursued goals. These management systems are also recommended as alternatives for the production of high quality wood. The second objective focuses on the need to adequately characterize the forest during the decision process that leads to local management. In order to obtain estimates of forest variables for different management units of potential interest for forest planning, as well as the associated measures of uncertainty in these estimates, certain results from Small Area Estimation Literature are extended to accommodate for the need of estimates and reliability measures in very small subpopulations containing a reduced number of pixels. A case study shows the potential of Small Area Estimation (SAE) techniques in forest inventories assisted with remotely sensed auxiliary information. The influence of the laser pulse density in the quality of estimates in different aggregation levels is analyzed. This study considers low laser pulse densities (0.5 returns/m2) similar to, those provided by large-scale Airborne Laser Scanner (ALS) surveys, such as the one conducted by the Spanish National Geographic Institute for about 80% of the Spanish territory. The results obtained show that it is possible to improve the efficiency of traditional forest inventories at local scale using EBLUP (Empirical Best Linear Unbiased Predictor) estimators based on unit level models and low density ALS auxiliary information.

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.

LiDAR remote sensing applied to forest resources assessment

Disponer de información precisa y actualizada de inventario forestal es una pieza clave para mejorar la gestión forestal sostenible y para proponer y evaluar políticas de conservación de bosques que permitan la reducción de emisiones de carbono debidas a la deforestación y degradación forestal (REDD). En este sentido, la tecnología LiDAR ha demostrado ser una herramienta perfecta para caracterizar y estimar de forma continua y en áreas extensas la estructura del bosque y las principales variables de inventario forestal. Variables como la biomasa, el número de pies, el volumen de madera, la altura dominante, el diámetro o la altura media son estimadas con una calidad comparable a los inventarios tradicionales de campo. La presente tesis se centra en analizar la aplicación de los denominados métodos de masa de inventario forestal con datos LIDAR bajo diferentes condiciones y características de masa forestal (bosque templados puros y mixtos) y utilizando diferentes bases de datos LiDAR (información proveniente de vuelo nacionales e información capturada de forma específica). Como consecuencia de lo anterior, se profundiza en la generación de inventarios forestales continuos con LiDAR en grandes áreas. Los métodos de masa se basan en la búsqueda de relaciones estadísticas entre variables predictoras derivadas de la nube de puntos LiDAR y las variables de inventario forestal medidas en campo con el objeto de generar una cartografía continua de inventario forestal. El rápido desarrollo de esta tecnología en los últimos años ha llevado a muchos países a implantar programas nacionales de captura de información LiDAR aerotransportada. Estos vuelos nacionales no están pensados ni diseñados para fines forestales por lo que es necesaria la evaluación de la validez de esta información LiDAR para la descripción de la estructura del bosque y la medición de variables forestales. Esta información podría suponer una drástica reducción de costes en la generación de información continua de alta resolución de inventario forestal. En el capítulo 2 se evalúa la estimación de variables forestales a partir de la información LiDAR capturada en el marco del Plan Nacional de Ortofotografía Aérea (PNOA-LiDAR) en España. Para ello se compara un vuelo específico diseñado para inventario forestal con la información de la misma zona capturada dentro del PNOA-LiDAR. El caso de estudio muestra cómo el ángulo de escaneo, la pendiente y orientación del terreno afectan de forma estadísticamente significativa, aunque con pequeñas diferencias, a la estimación de biomasa y variables de estructura forestal derivadas del LiDAR. La cobertura de copas resultó más afectada por estos factores que los percentiles de alturas. Considerando toda la zona de estudio, la estimación de la biomasa con ambas bases de datos no presentó diferencias estadísticamente significativas. Las simulaciones realizadas muestran que las diferencias medias en la estimación de biomasa entre un vuelo específico y el vuelo nacional podrán superar el 4% en áreas abruptas, con ángulos de escaneo altos y cuando la pendiente de la ladera no esté orientada hacia la línea de escaneo. En el capítulo 3 se desarrolla un estudio en masas mixtas y puras de pino silvestre y haya, con un enfoque multi-fuente empleando toda la información disponible (vuelos LiDAR nacionales de baja densidad de puntos, imágenes satelitales Landsat y parcelas permanentes del inventario forestal nacional español). Se concluye que este enfoque multi-fuente es adecuado para realizar inventarios forestales continuos de alta resolución en grandes superficies. Los errores obtenidos en la fase de ajuste y de validación de los modelos de área basimétrica y volumen son similares a los registrados por otros autores (usando un vuelo específico y parcelas de campo específicas). Se observan errores mayores en la variable número de pies que los encontrados en la literatura, que pueden ser explicados por la influencia de la metodología de parcelas de radio variable en esta variable. En los capítulos 4 y 5 se evalúan los métodos de masa para estimar biomasa y densidad de carbono en bosques tropicales. Para ello se trabaja con datos del Parque Nacional Volcán Poás (Costa Rica) en dos situaciones diferentes: i) se dispone de una cobertura completa LiDAR del área de estudio (capitulo 4) y ii) la cobertura LiDAR completa no es técnica o económicamente posible y se combina una cobertura incompleta de LiDAR con imágenes Landsat e información auxiliar para la estimación de biomasa y carbono (capitulo 5). En el capítulo 4 se valida un modelo LiDAR general de estimación de biomasa aérea en bosques tropicales y se compara con los resultados obtenidos con un modelo ajustado de forma específica para el área de estudio. Ambos modelos están basados en la variable altura media de copas (TCH por sus siglas en inglés) derivada del modelo digital LiDAR de altura de la vegetación. Los resultados en el área de estudio muestran que el modelo general es una alternativa fiable al ajuste de modelos específicos y que la biomasa aérea puede ser estimada en una nueva zona midiendo en campo únicamente la variable área basimétrica (BA). Para mejorar la aplicación de esta metodología es necesario definir en futuros trabajos procedimientos adecuados de medición de la variable área basimétrica en campo (localización, tamaño y forma de las parcelas de campo). La relación entre la altura media de copas del LiDAR y el área basimétrica (Coeficiente de Stock) obtenida en el área de estudio varía localmente. Por tanto es necesario contar con más información de campo para caracterizar la variabilidad del Coeficiente de Stock entre zonas de vida y si estrategias como la estratificación pueden reducir los errores en la estimación de biomasa y carbono en bosques tropicales. En el capítulo 5 se concluye que la combinación de una muestra sistemática de información LiDAR con una cobertura completa de imagen satelital de moderada resolución (e información auxiliar) es una alternativa efectiva para la realización de inventarios continuos en bosques tropicales. Esta metodología permite estimar altura de la vegetación, biomasa y carbono en grandes zonas donde la captura de una cobertura completa de LiDAR y la realización de un gran volumen de trabajo de campo es económica o/y técnicamente inviable. Las alternativas examinadas para la predicción de biomasa a partir de imágenes Landsat muestran una ligera disminución del coeficiente de determinación y un pequeño aumento del RMSE cuando la cobertura de LiDAR es reducida de forma considerable. Los resultados indican que la altura de la vegetación, la biomasa y la densidad de carbono pueden ser estimadas en bosques tropicales de forma adecuada usando coberturas de LIDAR bajas (entre el 5% y el 20% del área de estudio). ABSTRACT The availability of accurate and updated forest data is essential for improving sustainable forest management, promoting forest conservation policies and reducing carbon emissions from deforestation and forest degradation (REDD). In this sense, LiDAR technology proves to be a clear-cut tool for characterizing forest structure in large areas and assessing main forest-stand variables. Forest variables such as biomass, stem volume, basal area, mean diameter, mean height, dominant height, and stem number can be thus predicted with better or comparable quality than with costly traditional field inventories. In this thesis, it is analysed the potential of LiDAR technology for the estimation of plot-level forest variables under a range of conditions (conifer & broadleaf temperate forests and tropical forests) and different LiDAR capture characteristics (nationwide LiDAR information vs. specific forest LiDAR data). This study evaluates the application of LiDAR-based plot-level methods in large areas. These methods are based on statistical relationships between predictor variables (derived from airborne data) and field-measured variables to generate wall to wall forest inventories. The fast development of this technology in recent years has led to an increasing availability of national LiDAR datasets, usually developed for multiple purposes throughout an expanding number of countries and regions. The evaluation of the validity of nationwide LiDAR databases (not designed specifically for forest purposes) is needed and presents a great opportunity for substantially reducing the costs of forest inventories. In chapter 2, the suitability of Spanish nationwide LiDAR flight (PNOA) to estimate forest variables is analyzed and compared to a specifically forest designed LiDAR flight. This study case shows that scan angle, terrain slope and aspect significantly affect the assessment of most of the LiDAR-derived forest variables and biomass estimation. Especially, the estimation of canopy cover is more affected than height percentiles. Considering the entire study area, biomass estimations from both databases do not show significant differences. Simulations show that differences in biomass could be larger (more than 4%) only in particular situations, such as steep areas when the slopes are non-oriented towards the scan lines and the scan angles are larger than 15º. In chapter 3, a multi-source approach is developed, integrating available databases such as nationwide LiDAR flights, Landsat imagery and permanent field plots from SNFI, with good resultos in the generation of wall to wall forest inventories. Volume and basal area errors are similar to those obtained by other authors (using specific LiDAR flights and field plots) for the same species. Errors in the estimation of stem number are larger than literature values as a consequence of the great influence that variable-radius plots, as used in SNFI, have on this variable. In chapters 4 and 5 wall to wall plot-level methodologies to estimate aboveground biomass and carbon density in tropical forest are evaluated. The study area is located in the Poas Volcano National Park (Costa Rica) and two different situations are analyzed: i) available complete LiDAR coverage (chapter 4) and ii) a complete LiDAR coverage is not available and wall to wall estimation is carried out combining LiDAR, Landsat and ancillary data (chapter 5). In chapter 4, a general aboveground biomass plot-level LiDAR model for tropical forest (Asner & Mascaro, 2014) is validated and a specific model for the study area is fitted. Both LiDAR plot-level models are based on the top-of-canopy height (TCH) variable that is derived from the LiDAR digital canopy model. Results show that the pantropical plot-level LiDAR methodology is a reliable alternative to the development of specific models for tropical forests and thus, aboveground biomass in a new study area could be estimated by only measuring basal area (BA). Applying this methodology, the definition of precise BA field measurement procedures (e.g. location, size and shape of the field plots) is decisive to achieve reliable results in future studies. The relation between BA and TCH (Stocking Coefficient) obtained in our study area in Costa Rica varied locally. Therefore, more field work is needed for assessing Stocking Coefficient variations between different life zones and the influence of the stratification of the study areas in tropical forests on the reduction of uncertainty. In chapter 5, the combination of systematic LiDAR information sampling and full coverage Landsat imagery (and ancillary data) prove to be an effective alternative for forest inventories in tropical areas. This methodology allows estimating wall to wall vegetation height, biomass and carbon density in large areas where full LiDAR coverage and traditional field work are technically and/or economically unfeasible. Carbon density prediction using Landsat imaginery shows a slight decrease in the determination coefficient and an increase in RMSE when harshly decreasing LiDAR coverage area. Results indicate that feasible estimates of vegetation height, biomass and carbon density can be accomplished using low LiDAR coverage areas (between 5% and 20% of the total area) in tropical locations.

Unifying theory of hypoxia tolerance: molecular/metabolic defense and rescue mechanisms for surviving oxygen lack.

We develop a unifying theory of hypoxia tolerance based on information from two cell level models (brain cortical cells and isolated hepatocytes) from the highly anoxia tolerant aquatic turtle and from other more hypoxia sensitive systems. We propose that the response of hypoxia tolerant systems to oxygen lack occurs in two phases (defense and rescue). The first lines of defense against hypoxia include a balanced suppression of ATP-demand and ATP-supply pathways; this regulation stabilizes (adenylates) at new steady-state levels even while ATP turnover rates greatly decline. The ATP demands of ion pumping are down-regulated by generalized "channel" arrest in hepatocytes and by "spike" arrest in neurons. Hypoxic ATP demands of protein synthesis are down-regulated probably by translational arrest. In hypoxia sensitive cells this translational arrest seems irreversible, but hypoxia-tolerant systems activate "rescue" mechanisms if the period of oxygen lack is extended by preferentially regulating the expression of several proteins. In these cells, a cascade of processes underpinning hypoxia rescue and defense begins with an oxygen sensor (a heme protein) and a signal-transduction pathway, which leads to significant gene-based metabolic reprogramming-the rescue process-with maintained down-regulation of energy-demand and energy-supply pathways in metabolism throughout the hypoxic period. This recent work begins to clarify how normoxic maintenance ATP turnover rates can be drastically (10-fold) down-regulated to a new hypometabolic steady state, which is prerequisite for surviving prolonged hypoxia or anoxia. The implications of these developments are extensive in biology and medicine.

Grasshopper crop and midgut extract effects on plants: an example of reward feedback.

Acid extracts and a resultant fraction from solid-phase extraction (SPE) of Romalea guttata crop and midgut tissues induce sorghum (Sorghum bicolor var. Rio) coleoptile growth in 24-h incubations an average of 49% above untreated controls. When combined with plant auxin, indole-3-acetic acid (IAA), the SPE fraction shows a synergistic reaction, yielding increases in coleoptile growth that average 295% above untreated controls and 8% above IAA standards. The interaction lowered the point of maximum sensitivity of IAA 3 orders of magnitude, resulting in a new IAA physiological set point at 10(-7) g/ml. This synergism suggests that contents in animal regurgitants making their way into plant tissue during feeding may produce a positive feedback in plant growth and development following herbivory. Such a process, also known as reward feedback, may exert major controls on ecosystem-level relationships in nature.