Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.

The power of the purse : what do the data say on US federal budget allocation to the states?

This paper provides new evidence on the determinants of the allocation of the US federal budget to the states and tests the capability of congressional, electoral and partisan theories to explain such allocation. We find that socio-economic characteristics are important explanatory variables but are not sufficient to explain the disparities in the distribution of federal monies. First, prestige committee membership is not conducive to pork-barrelling. We do not find any evidence that marginal states receive more funding; on the opposite, safe states tend to be rewarded. Also, states that are historically "swing" in presidential elections tend to receive more funds. Finally, we find strong evidence supporting partisan theories of budget allocation. States whose governor has the same political affiliation of the President receive more federal funds; while states whose representatives belong to a majority opposing the president party receive less funds.

Social relations and power

This paper presents an explanatory typology of social relations which moves forward from those habitual and known by social disciplines, and labels the three types: actions - strategies - institutions . We set out to research characteristics, specificities, relevance of and differences between each type, as well as their interactions and interweaving, which make up the complexity of social relations. Moreover, mutual interdependence between the said social categories is established, which corresponds to a new conceptualization of power . This avoids traditional reductionism and rescues rarely taken-into-account capacities and determinations. The pair "social relations and power" makes up a necessary and indispensable framework to tackle the various problems of the social world.

Secret and power in social life

Secret and power constitute two fundamental instances of the social world. Secret takes care of the concealment of things and of social processes. Secret is also a power device. Power is the social capacity to do, create, not doing and stop from doing. Secret and power get mutual feedback. Power uses the secret to protect his potential, be it what may, to increment its operative strength. Secret uses the power to achieve its aims and proposals. Social sciences seem to ignore the huge explanatory capacity of these two interrelated concepts, and even more, their powerful intervention in societies.

Social relations and power

This paper presents an explanatory typology of social relations which moves forward from those habitual and known by social disciplines, and labels the three types: actions - strategies - institutions . We set out to research characteristics, specificities, relevance of and differences between each type, as well as their interactions and interweaving, which make up the complexity of social relations. Moreover, mutual interdependence between the said social categories is established, which corresponds to a new conceptualization of power . This avoids traditional reductionism and rescues rarely taken-into-account capacities and determinations. The pair "social relations and power" makes up a necessary and indispensable framework to tackle the various problems of the social world.

Secret and power in social life

Secret and power constitute two fundamental instances of the social world. Secret takes care of the concealment of things and of social processes. Secret is also a power device. Power is the social capacity to do, create, not doing and stop from doing. Secret and power get mutual feedback. Power uses the secret to protect his potential, be it what may, to increment its operative strength. Secret uses the power to achieve its aims and proposals. Social sciences seem to ignore the huge explanatory capacity of these two interrelated concepts, and even more, their powerful intervention in societies.

Secret and power in social life

Secret and power constitute two fundamental instances of the social world. Secret takes care of the concealment of things and of social processes. Secret is also a power device. Power is the social capacity to do, create, not doing and stop from doing. Secret and power get mutual feedback. Power uses the secret to protect his potential, be it what may, to increment its operative strength. Secret uses the power to achieve its aims and proposals. Social sciences seem to ignore the huge explanatory capacity of these two interrelated concepts, and even more, their powerful intervention in societies.

Social relations and power

This paper presents an explanatory typology of social relations which moves forward from those habitual and known by social disciplines, and labels the three types: actions - strategies - institutions . We set out to research characteristics, specificities, relevance of and differences between each type, as well as their interactions and interweaving, which make up the complexity of social relations. Moreover, mutual interdependence between the said social categories is established, which corresponds to a new conceptualization of power . This avoids traditional reductionism and rescues rarely taken-into-account capacities and determinations. The pair "social relations and power" makes up a necessary and indispensable framework to tackle the various problems of the social world.

Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting

Wind power time series usually show complex dynamics mainly due to non-linearities related to the wind physics and the power transformation process in wind farms. This article provides an approach to the incorporation of observed local variables (wind speed and direction) to model some of these effects by means of statistical models. To this end, a benchmarking between two different families of varying-coefficient models (regime-switching and conditional parametric models) is carried out. The case of the offshore wind farm of Horns Rev in Denmark has been considered. The analysis is focused on one-step ahead forecasting and a time series resolution of 10 min. It has been found that the local wind direction contributes to model some features of the prevailing winds, such as the impact of the wind direction on the wind variability, whereas the non-linearities related to the power transformation process can be introduced by considering the local wind speed. In both cases, conditional parametric models showed a better performance than the one achieved by the regime-switching strategy. The results attained reinforce the idea that each explanatory variable allows the modelling of different underlying effects in the dynamics of wind power time series.

Statistical models for short-term wind power ramp forecasting

La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.

Leadership in American Evangelical churches:an explanatory theory

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT This study is about leadership in American Evangelical Churches, which as a sub-set of American Christianity, are growing, while American Christianity as a whole is in decline. As a result evangelicalism is quickly becoming the dominate iteration of American Christianity. It is anecdotal that well led churches grow while poorly led churches do not, yet no one has identified what leadership, in the evangelical church context, is. Researchers have investigated a number of aspects of church leadership (much of it without identifying whether or not the churches under investigation were evangelical or not) but no one has put forth a unified theory linking these aspects together. The purpose of this research is to address that gap and develop a theory that explains how evangelicals view leadership in their local churches. In this study of three churches, dissimilar in size and governance, a purely qualitative approach to data collection and analysis was employed. The study involved 60 interviews that sought points-of-view from top and mid-level leadership along with congregant followers. The study borrowed heavily from Glaser and Strauss (1967) Grounded Theory approach to data analysis. The results developed a theory which provides a unified explanation of how leadership actually works in the three evangelical churches. Several implications for practice are discussed as to the theory's usefulness as a method of leadership education and evaluation. An original discovery was found that an individual's incumbency within the organization was identified as a social power. Limitations to this research are the limitations generally imputed to purely qualitative research in that questions are raised about the theory's applicability to evangelical churches beyond the three studied. The suggestions for further research involve addressing those limitations