Causes and consequences of variation in the nutrition and endemic microflora of food stores in managed honey bees (Apis mellifera L.)

Honey bees are pollinators, accounting for around 90% of commercial pollination of animal-pollinated plants and approximately 35% of global food production. Global populations of honey bees have declined significantly recently with heavy losses attributed to Colony Collapse Disorder, pesticides, parasites and pathogens. One of the factors that may be contributing to an increase in susceptibility to these stresses is the quality of food available in a hive. This thesis focuses on the interactions between honey bee nutrition, microbial communities and fitness. In Chapter 2 the nutritional composition of bee bread (pollen stored inside hives) was studied. The composition in terms of protein and reducing sugar was found to vary both spatially and temporally; lipid and starch content was found to vary temporally through the season. The spatial trends in protein content were found to be associated with changes in landscape composition, as estimated by the Countryside Survey database. The implications for these findings are that certain landscape types may produce higher quality diets for honey bees. In Chapter 3, the link between nutritional composition of bee bread and the species of plant that comprise it was investigated. Previous research indicates that pollens vary in their nutritional content and using molecular tools, we investigated the impact of complex plant communities in this system. The number of plant species in bee bread was positively correlated with increasing protein levels, and specifically certain individual plant species were found to be driving this pattern. These results indicate that a more diverse diet of plants will benefit honey bees by increasing their dietary protein intake. The conversion of pollen to bee bread requires the activity of certain microorganisms. In chapter 4, we again used molecular tools to study the microbial community found associated with bee bread. We found a community that was not significantly different between hives located in different areas, but which varied significantly in is composition through the beekeeping season. This suggests that the environment does not determine the bacterial communities in honey bee hives; rather it is being determined by seasonal changes. Finally, in chapter 5 the relationship between the nutritional composition of bee bread and the immunocompetence of larval and adult honey bees was examined. The results showed that dietary protein and carbohydrate is significantly correlated with the overall fitness of a hive in terms of expression a constituent immune response. The link between landscape composition and nutrition established in chapter 2 was used to predict honey bee nutrition across the UK, and then was used to predict immune response for all UK bees. These predictions were comparable to honey bee disease records maintained by UK government. This thesis provides a detailed examination of the effects of landscape composition on honey bee nutrition and immunity. The results presented here have implications for understanding spatial patterns in bee fitness and bee disease epidemiology

Witch’s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia):Identifying High-Risk Areas by Climatic Mapping

Biological invasions of vectorborne diseases can be devastating. Bioclimatic modeling provides an opportunity to assess and predict areas at risk from complex multitrophic interactions of pathogens, highlighting areas in need of increased monitoring effort. Here, we model the distribution of an economically critical vectorborne plant pathogen ‘Candidatus Phytoplasma aurantifolia’, the etiological agent of Witches’ Broom Disease of Lime. This disease is a significant limiting factor on acid lime production (Citrus aurantifolia, Swingle) in the Middle East and threatens its production globally. We found that temperature, humidity, and the vector populations significantly determine disease distribution. Following this, we used bioclimatic modeling to predict potential novel sites of infections. The model outputs identified potential novel sites of infection in the citrus producing regions of Brazil and China. We also used our model to explore sites in Oman where the pathogen may not be infectious, and suggest nurseries be established there. Recent major turbulence in the citrus agricultural economy has highlighted the importance of this work and the need for appropriate and targeted monitoring programs to safeguard lime production

Trees for Bees

Limited resources and land-use pressures require more efficient conservation strategies, from increasingly limited input. Pollinator declines are threatening food security and natural capital. I present a novel perspective on landscape level pollinator conservation from across multiple scientific fields. I examine the value of landscape structure provided by trees and hedgerows compared with floral strips, and discuss use of computer simulation technologies for understanding how spatial structure impacts pollinators’ ability to forage. All bees forage on a mixture of both flowering plants and tree species. Honeybees have a detectable preference for foraging on trees, even when sparse. The spatial information provided by trees and hedgerows positively impacts formation of the “cognitive map”, making pollination and foraging more efficient. Woody habitat features like trees and hedgerows provide more efficient resources for pollinators in a number of ways. They are more efficient forage targets due to absolute resource density; tree and hedgerow planting could provide more optimised foraging landscapes for pollinators. Using computer simulation may enable us to study pollinator responses to landscape development at this scale. Woodland development results in non-pollinator ecosystem services, representing a more cost-effective conservation strategy. Moving forward we need to identify the key impediments to its successful implementation