Declines in insect pollinators in Europe have been linked to changes in land use. Pollinator nutrition is dependent on floral resources (i.e., nectar and pollen), which are linked to landscape composition. Here, we present a stratified analysis of the nutritional composition of beebread in managed honeybee hives with a view to examining potential sources of variation in its nutritional composition. Specifically, we tested the hypothesis that beebread composition correlates with local land use and therefore available floral resources. The results demonstrated that the starch, lipid, and moisture contents of beebread are all highly conserved across hives, whereas levels of protein and nonreducing sugar increased as the year progressed, reducing sugars, however, decreased during the first half of the year and then increased toward the end. Local land use around hives was quantified using data from the Countryside Survey 2007 Land Cover Map. Bee-bread protein content was negatively correlated with increasing levels of arable and horticultural farmland surrounding hives and positively correlated with the cover of natural grasslands and broadleaf woodlands. Reducing sugar content was also positively correlated with the amount of broad-leaved woodland in a 3 Km² radius from the hives. Previous studies on a range of invertebrates, including honeybees, indicate that dietary protein intake may have a major impact on correlates of fitness, including longevity and immune function. The finding that beebread protein content correlates with land use suggests that landscape composition may impact on insect pollinator well-being and provides a link between landscape and the nutritional ecology of socially foraging insects in a way not previously considered.
Sufficiently diverse and abundant resources are essential for generalist consumers, and form an important part of a suite of conservation strategies for pollinators. Honey bees are generalist foragers and are dependent on diverse forage to adequately meet their nutritional needs. Through analysis of stored pollen (bee bread) samples obtained from 26 honey bee (Apis mellifera L.) hives across NW-England, we quantified bee bread nutritional content and the plant species that produced these stores from pollen. Protein was the most abundant nutrient by mass (63%), followed by carbohydrates (26%). Protein and lipid content (but not carbohydrate) contributed significantly to ordinations of floral diversity, linking dietary quality with forage composition. DNA sequencing of the ITS2 region of the nuclear ribosomal DNA gene identified pollen from 89 distinct plant genera, with each bee bread sample containing between 6 and 35 pollen types. Dominant genera included dandelion (Taraxacum), which was positively correlated with bee bread protein content, and cherry (Prunus), which was negatively correlated with the amount of protein. In addition, proportions of amino acids (e.g. histidine and valine) varied as a function of floral species composition. These results also quantify the effects of individual plant genera on the nutrition of honey bees. We conclude that pollens of different plants act synergistically to influence host nutrition; the pollen diversity of bee bread is linked to its nutrient content. Diverse environments compensate for the loss of individual forage plants, and diversity loss may, therefore, destabilize consumer communities due to restricted access to alternative resources.Electronic supplementary materialThe online version of this article (10.1007/s00442-017-3968-3) contains supplementary material, which is available to authorized users.
Microbial communities, associated with almost all metazoans, can be inherited from the environment. Although the honeybee (Apis mellifera L.) gut microbiome is well documented, studies of the gut focus on just a small component of the bee microbiome. Other key areas such as the comb, propolis, honey, and stored pollen (bee bread) are poorly understood. Furthermore, little is known about the relationship between the pollinator microbiome and its environment. Here we present a study of the bee bread microbiome and its relationship with land use. We estimated bacterial community composition using both Illumina MiSeq DNA sequencing and denaturing gradient gel electrophoresis (DGGE). Illumina was used to gain a deeper understanding of precise species diversity across samples. DGGE was used on a larger number of samples where the costs of MiSeq had become prohibitive and therefore allowed us to study a greater number of bee breads across broader geographical axes. The former demonstrates bee bread comprises, on average, 13 distinct bacterial phyla; Bacteroidetes, Firmicutes, Alpha‐proteobacteria, Beta‐proteobacteria, and Gamma‐proteobacteria were the five most abundant. The most common genera were Pseudomonas, Arsenophonus, Lactobacillus, Erwinia, and Acinetobacter. DGGE data show bacterial community composition and diversity varied spatially and temporally both within and between hives. Land use data were obtained from the 2007 Countryside Survey. Certain habitats, such as improved grasslands, are associated with low diversity bee breads, meaning that these environments may be poor sources of bee‐associated bacteria. Decreased bee bread bacterial diversity may result in reduced function within hives. Although the dispersal of microbes is ubiquitous, this study has demonstrated landscape‐level effects on microbial community composition.
Limes as a fruit crop are of great economic importance, key to Asian and South American cuisines and cultivated in nearly all tropical and subtropical regions of the world. Demand for limes is increasing, driven by World Health Organization recommendations. Pests and pathogens have significantly reduced global productivity, while changes in agronomic techniques aim to alleviate this stress. We present here a holistic examination of the major biotic (pests and pathogens) and abiotic (environment and socioeconomic) factors that presently limit global production of lime. The major producers of limes are India, China and Mexico, while loss of lime production in the United States from 2006 has led many countries in the Western Hemisphere (Mexico, Costa Rica and Brazil) to export primarily to the USA. The most widespread invertebrate pests of lime are Toxoptera citricida and Scirtothrips citri. Another insect, Diaphorina citri, vectors both Huanglongbing (HLB) and Witches Broom of Lime, which are particularly destructive diseases. Developing agronomic techniques focus on production of resistant and pathogen-free planting materials and control of insect vectors. HLB infects citrus in nearly all growing regions, and has been particularly devastating in Asian citrus. Meanwhile, Citrus tristeza virus has infected over 100 million citrus trees, mainly in the Americas and Mediterranean. Currently, Witches Broom Disease of Lime is localised to the Middle East, but recently it has been detected in South America. The range of its vectors (D. citri and Hishimonus phycitis) further raises concerns about the potential spread of this disease. Abiotic threats to lime production are also a significant concern; key areas of lime production such as Mexico, India and the Middle East suffer from increasing water stress and high soil salinity, which combined with invasive pests and pathogens, may eliminate lime production in these areas. To ensure future security in lime production, policy makers, researchers and growers will need to examine the potential of more resistant lime cultivars and establish novel areas of cultivation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.