The most important indigenous bee plant in South Africa is the winter flowering Aloe greatheadii var davyana, with a widespread distribution across the summer rainfall region. Beekeepers commonly move their hives to the "aloe fields" during winter, using the strong pollen and nectar flow for colony growth, queen rearing and honey production. In spite of its importance for the bee industry, no complete pollen analysis is available and, except for the popular bee literature, little is known about nectar production or pollinators. The aim of the study was therefore to evaluate the floral rewards of this aloe and to investigate the importance of these resources for honeybees. We analysed fresh, bee-collected and stored aloe pollen for its nutritional content (not previously done for any plant species). Addition of nectar and glandular secretions leads to an increase in water and carbohydrate content and a decrease in protein and lipid content. All the essential amino acids, except tryptophan, met or exceeded the minimum levels for honeybee development. In worker bees in queenright colonies, ovarian development is greater on aloe than on sunflower pollen, which may be explained by the exceptionally high protein content and high extraction efficiency during digestion. In assessing the nectar resource, we investigated the nectary structure and nectar presentation of two species belonging to different sections of the genus Aloe, A. castanea and A. greatheadii var davyana, but anatomical differences were not related to the nectar production. We looked at variation in nectar volume and concentration of A. greatheadii var davyana on various levels, from within the flowers to across the summer rainfall area. Nectar was continuously available and, although dilute (mean concentration 18.6%), the nectar of A. greatheadii var davyana is more concentrated than that of other Aloe species, making it an ideal source of energy and water for honeybees. Utilisation of dilute nectar by bees requires elimination of much excess water. We sampled crop contents of nectar foragers to determine if changes in nectar concentration occurred after collection and before unloading in the hive. Contrary to the common assumption that nectar is either unchanged or slightly diluted during transport, we observed a dramatic increase in concentration and a decrease in volume between the flowers and the hive. Bees may be foraging primarily to get enough water for their physiological needs. Using miniaturised data loggers, we showed that bees are able to adjust nest humidity within sub-optimal limits, in addition to efficient regulation of hive temperature. Humidity levels are influenced by trade-offs with regulation of temperature and respiratory gas exchanges. Although the dilute nectar and pinkish red tubular flowers are characteristic of bird-pollination, exclusion experiments showed that bees are the primary pollinators of A. greatheadii var davyana. This contrasts with other Aloe species which are pollinated by sunbirds and other passerine birds, but highlights the two-way interaction between the bees and the aloes. / Thesis (PhD (Entomology))--University of Pretoria, 2008. / Zoology and Entomology / unrestricted

Colony Collapse Disorder (CCD) has been a major threat to bee colonies around the world which affects vital human food crop pollination. The decline in bee population can have tragic consequences, for humans as well as the bees and the ecosystem. Bee health has been a cause of urgent concern for farmers and scientists around the world for at least a decade but a specific cause for the phenomenon has yet to be conclusively identified. This work uses Artificial Intelligence and Computer Vision approaches to develop and analyze techniques to help in continuous monitoring of bee traffic which will further help in monitoring forager traffic. Bee traffic is the number of bees moving in a given area in front of the hive over a given period of time. And, forager traffic is the number of bees entering and/or exiting the hive over a given period of time. Forager traffic is an important variable to monitor food availability, food demand, colony age structure, impact of pesticides, etc. on bee hives. This will lead to improved remote monitoring and general hive status and improved real time detection of the impact of pests, diseases, pesticide exposure and other hive management problems.

En las últimas décadas, la utilización de las Tecnologías de la Información y la Comunicación (TIC) se ha extendido a diferentes ámbitos de nuestra sociedad. Entre dichos ámbitos nos encontramos con la educación. De manera general, las escuelas han ido incorporando diferentes herramientas tecnológicas con el objetivo de mejorar el proceso de enseñanza-aprendizaje del alumnado. Estas herramientas innovadoras mejoran no solo el aprendizaje, sino también la participación y la presencia del alumnado con Necesidades Específicas de Apoyo Educativo en los colegios ordinarios. Entre este grupo de alumnos y alumnas encontramos aquellos con Trastorno del Espectro Autista (TEA). Un trastorno del neurodesarrollo que afecta la capacidad de los individuos para comunicarse y desarrollar interacciones sociales, junto con la presencia de patrones restringidos y conductas, intereses y actividades repetitivas. Esta línea de diagnóstico trae consigo un grupo muy heterogéneo de individuos, para los cuales es muy complicado identificar un método concreto de aprendizaje. La utilización de las TIC ha añadido nuevas posibilidades para su intervención educativa. Entre estas herramientas tecnológicas ha experimentado un gran auge la robótica educativa la cual, gracias a su predictibilidad, su capacidad para actuar como soporte visual y secuenciar la presentación de la información se constituye como una herramienta ideal para la enseñanza de este alumnado. No obstante, el elevado coste de los robots, así como la falta de dispositivos, hace que la mayoría de las aplicaciones se desarrollen en un entorno clínico y no educativo. Ante este panorama, la presente investigación tiene por objetivo general evaluar la competencia en el área de comunicación e interacción social del alumnado con Trastorno del Espectro Autista (TEA) a partir de la aplicación en función de la utilización de la robótica. Para ello, se opta por un enfoque cuantitativo cuasi experimental con un diseño de dos grupos no equivalentes con pretest y postest y grupo control. Donde tanto los participantes del grupo control, quienes realizan las tareas sin utilizar la robótica, como los participantes del grupo experimental, quienes realizan las tareas con mediación del robot Bee-bot, son alumnos y alumnas con TEA. y grupo control. El procedimiento utilizado para la selección de la muestra fue el muestreo no probabilístico disponible entre las unidades específicas de Comunicación y Lenguaje de la ciudad de Alicante (UECil). Por otro lado, el instrumento utilizado fue el cuestionario diseñado adhoc CACIS-TEA y el análisis de datos se realizará con el paquete estadístico SPSS para Windows (Statistical Package for Social Sciences) en su versión 21. El análisis de datos se basa en pruebas no paramétricas. Los resultados indicaron variaciones en un mayor número de ítems del cuestionario para el alumnado del grupo experimental. Asimismo, también indican que alumnado del grupo experimental ha mejorado significativamente sus habilidades en el área de comunicación e interacción social tras el desarrollo del programa de intervención mediado por el robot Bee-Bot, respecto al alumnado del grupo control en el que se ha aplicado una metodología sin TIC. Y, por último, se observan diferencias significativas dentro del grupo experimental en función del tipo de comunicación, el género y el nivel actual de competencia (NAC). Como conclusión se puede afirmar que este la robótica posee potencialidades para el aprendizaje del alumnado con Trastorno del Espectro Autista.

Previous research confirms that gender affects organizations and the overall organizational culture. Organizations are heavily gendered and, in most cases, to the disadvantage of women. It has been shown that gender bias within male-dominated organizations creates the queen bee syndrome, characterized by a lack of solidarity and hostile behavior amongst women. Because gender bias exists in all organizations, it is reasonable to believe it also exists in female-dominated organizations. This study examines the queen bee syndrome in female-dominated organizations, analyzing how the characteristics permeate the organizational culture. The study employs a qualitative research method and collects data through qualitative surveys with LiVO members, a Swedish union organization for managers within the health and care sector. The study aims to build on theory regarding the queen bee syndrome and extend knowledge about gendered organizations and female-dominated organizations. This study suggests that signs of the queen bee syndrome, to some extent, permeate the organizational culture in female-dominated organizations. However, the result also reveals that complexity and duality exist. The triggering structures that create the queen bee syndrome need to be addressed rather than the gender composition to counteract queen bee behavior.

Pollinators are essential to food production globally. Without them, the production of food becomes increasingly difficult, time consuming, and costly. Unfortunately, due to the rapid changes to our earth's physical and climatic structure millions of species are becoming classified as threatened, endangered or extinct. Among these declining species are pollinating insects such as Aphis mellifera (honeybee) and other native species. This is due to a phenomenon known as colony collapse disorder (CCD) and other native bees. The decline indicates that the future habitability of earth may be in jeopardy. The solution to this crisis is to expand the habitat of native bees into our existing infrastructure, connecting the pollinator dependent crops with a network of biodiverse habitat. This will greatly improve the existing agricultural industries resiliency towards change. Thus, ensuring that California can be economically prosperous while continuing to feed the globe. The Sacramento Valley is one location which is ideal to develop such a network of native pollinator habitat due to its reliance on the agriculture industry and favorable environmental conditions.

Declines in pollinators around the globe, notably the loss of honey bees (Apis mellifera L.) to Colony Collapse Disorder, coupled with a dearth of quantitative data on non-Apis bee pollinators, led to this dissertation research, which documents the role of non-Apis bees in crop pollination in southwest Virginia. Major findings of this first study of its kind in the region were that non-Apis bees provided the majority of pollination—measured by visitation—for several economically important entomophilous crops (apple, blueberry, caneberry, and cucurbits); diverse bee populations may be helping to stabilize pollination service (105 species on crop flowers); landscape factors were better predictors of non-Apis crop pollination service than farm management factors or overall bee diversity; and non-Apis bees in the genera Andrena, Bombus, and Osmia were as constant as honey bees when foraging on apple. Non-Apis, primarily native, bees made up between 68% (in caneberries) and 83% (in cucurbits) of bees observed visiting crop flowers. While 37–59 species visited crop flowers, there was low correspondence between bee communities across or within crop systems ("within crop" Jaccard similarity indices for richness ranged from 0.12–0.28). Bee community diversity on crop flowers may help stabilize pollination service if one or more species declines temporally or spatially. A few species were especially important in each crop: Andrena barbara in apple; Andrena carlini and A. vicina in blueberry; Lasioglossum leucozonium in caneberry; and Peponapis pruinosa and Bombus impatiens in cucurbits. Eight species collected were Virginia state records. In models testing effects of farm management and landscape on non-Apis crop pollination service, percent deciduous forest was positively correlated in apple, blueberry, and squash, but at different scales. For apple and blueberry, pollination service declined with an increase in utilized alternative forage but was positively related to habitat heterogeneity. For squash, percent native plants also related positively, possibly due to increased presence of bumble bees in late summer. Species collected from both bowl traps and flowers was as low as 22% and overall site bee diversity had no effect on crop pollination service, highlighting the value in pollination research of monitoring bees on flowers. / Ph. D.

The mite ectoparasite Varroa destructor, poses a serious threat for the survival of the Apis mellifera colonies. The intensive use of acaricidal products is one of the most common methods for defending bees from Varroa that can cause the contamination of the wax foundation used in beekeeping. The natural honeycomb management could provide a solution for this problem, because it involves the use of frames without wax foundation which allows the bees to build a complete comb ex novo. On the other hand, colonies which are free to build cells of their choice, usually build a number of drone cells higher than colonies managed with the wax foundation. This could potentially lead to several negative consequences because the V. destructor reproductive success is greater on drone broods than on worker broods. The aim of the present study was to examine the colony development, to evaluate the honey production and to monitor the growth of V. destructor infestations and associated virus infections in Apis mellifera colonies managed by using natural honeycombs compared with the conventional management. Several colony parameters were measured in spring and summer. The strength of the colony was used to estimate the worker and drone populations. In order to measure the V. destructor infestations were used several methods, such as the natural mite fall, the powdered sugar roll, the soapy water and the brood cell uncapping. Molecular analysis was performed in order to measure the viral load of five Apis mellifera viruses. The honey produced was measured by collecting the honey stored in the supers, which are boxes placed on a beehive for bees to store. The results showed that the higher presence of drone brood in the colonies managed using the natural honeycomb did not negatively affect the colony development nor the mite V. destructor population compared to control colonies. The molecular analysis showed that the DWV was the most common virus found in bee samples, and its viral load was more influenced from the mite infestation rate than from the treatment. The analysis carried out in this study showed that the natural honeycomb management can represent a valid alternative to the wax foundation. This kind of colony management thus appears to contradict our primary hypothesis which was that letting the bees build their own honeycomb would have led to a significant increase in the V. destructor infestation. Productivity data did not provide reliable results about the difference between the natural honeycomb and the conventional colony management due to climatic adversities. Further studies will be performed to better investigate this aspect. Data about the natural mite fall and the estimation of the mite population in the phoretic/reproductive phases provided a useful starting point for further studies on the correct timing to carry out acaricide treatments both in conventional and natural honeycomb managed colonies.

yes / This paper introduces a novel symbolic regression approach, namely biogeographical-based programming (BBP), for the prediction of elastic modulus of self-compacting concrete (SCC). The BBP model was constructed directly from a comprehensive dataset of experimental results of SCC available in the literature. For comparison purposes, another new symbolic regression model, namely artificial bee colony programming (ABCP), was also developed. Furthermore, several available formulas for predicting the elastic modulus of SCC were assessed using the collected database. The results show that the proposed BBP model provides slightly closer results to experiments than ABCP model and existing available formulas. A sensitivity analysis of BBP parameters also shows that the prediction by BBP model improves with the increase of habitat size, colony size and maximum tree depth. In addition, among all considered empirical and design code equations, Leemann and Hoffmann and ACI 318-08’s equations exhibit a reasonable performance but Persson and Felekoglu et al.’s equations are highly inaccurate for the prediction of SCC elastic modulus.

The populations of wild pollinators have been declining worldwide, mainly due to habitat loss or change. Some farmers use honeybees to secure pollination of their crops, but honeybees can cause further problems effecting wild pollinators. Knowledge of foraging plants for honeybees can give a clue to the conditions of interactions and competition between honeybees and wild pollinators. The aim of this study was to identify plants visited by honeybees, and to compare classic morphological methods of identifying pollen to other modern palynological techniques. Samples of bee pollen from two hives in Västerbotten county, Sweden, was studied with light microscope. A selection of the samples were also studied in scanning electron microscope or by extraction of nucleic acid followed by PCR. All the identified pollen types originated from plants common in Sweden, for example, raspberry, rosebay willowherb, member of the genus Vaccinium and different types of clover. Due to similar morphology, many of the pollen types had more than one possible origin. Many types of pollen found in the samples remained unidentified. Regarding modern palynological techniques, one grain of bee pollen was substantial to extract enough nucleic acid to perform PCR. Positive PCR reactions were found for all but one of the seven PCR primers tested. Each primer gave positive reaction to only one color of bee pollen. One of the colors of bee pollen did not give any positive PCR reaction. The result of this study highlights the further need of reliable and available reference material in the palynological field.

Ecological interactions within a community shape the structure of ecosystems and influence ecosystem function. Plant-pollinator interactions exist as mutualistic exchange networks that may collapse as habitat loss occurs, thereby threatening the overall health of an ecosystem. Understanding the impacts of human-mediated habitat disturbance on ecological interactions is therefore crucial for conservation efforts. Archbold Biological Station (ABS) in Venus, Florida contains over 2000 hectares of protected Florida scrub habitat nested within a human-dominated environment that is threatened by anthropogenic habitat disturbance. In past studies, over 113 bee species and 157 associated host plants, many endemic to the Lake Wales Ridge, have been found on ABS property, providing an understanding of this system's plant-bee network. Using those data as a baseline, this study investigated the effects of varying levels of mechanical habitat disturbance intensity on the diversity and network structure of plant-bee interaction networks. Flowering plant abundance, richness, diversity, and composition as well as bee abundance and composition were significantly different across mechanical habitat disturbance levels. Interactions between bees and flowering plants also differed with varying disturbance intensity. From these results, it is clear that plants, bees and interactions between them are impacted by mechanical habitat disturbance in this system. This project informs management efforts not only for natural systems with the threat of alteration, but also for agricultural systems, many of which heavily rely on flower visitation by bee pollinators. This research also contributes to the growing field of interaction ecology by increasing understanding of habitat alteration effects on a valuable ecological interaction and ultimately ecosystem function.