Identifying the floral composition of honey provides a method for investigating the plants that honey bees visit. We compared melissopalynology, where pollen grains retrieved from honey are identified morphologically, with a DNA metabarcoding approach using the rbcL DNA barcode marker and 454-pyrosequencing. We compared nine honeys supplied by beekeepers in the UK. DNA metabarcoding and melissopalynology were able to detect the most abundant floral components of honey. There was 92% correspondence for the plant taxa that had an abundance of over 20%. However, the level of similarity when all taxa were compared was lower, ranging from 22–45%, and there was little correspondence between the relative abundance of taxa found using the two techniques. DNA metabarcoding provided much greater repeatability, with a 64% taxa match compared to 28% with melissopalynology. DNA metabarcoding has the advantage over melissopalynology in that it does not require a high level of taxonomic expertise, a greater sample size can be screened and it provides greater resolution for some plant families. However, it does not provide a quantitative approach and pollen present in low levels are less likely to be detected. We investigated the plants that were frequently used by honey bees by examining the results obtained from both techniques. Plants with a broad taxonomic range were detected, covering 46 families and 25 orders, but a relatively small number of plants were consistently seen across multiple honey samples. Frequently found herbaceous species were Rubus fruticosus, Filipendula ulmaria, Taraxacum officinale, Trifolium spp., Brassica spp. and the non-native, invasive, Impatiens glandulifera. Tree pollen was frequently seen belonging to Castanea sativa, Crataegus monogyna and species of Malus, Salix and Quercus. We conclude that although honey bees are considered to be supergeneralists in their foraging choices, there are certain key species or plant groups that are particularly important in the honey bees environment. The reasons for this require further investigation in order to better understand honey bee nutritional requirements. DNA metabarcoding can be easily and widely used to investigate floral visitation in honey bees and can be adapted for use with other insects. It provides a starting point for investigating how we can better provide for the insects that we rely upon for pollination.

The incidences of respiratory allergies are at an all-time high. Pollen aeroallergens can reflect changing climate, with recent studies in Europe showing some, but not all, pollen types are increasing in severity, season duration and experiencing an earlier onset. This study aimed to identify pollen trends in the UK over the last twenty-six years for a range of pollen sites, with a focus on the key pollen types of Poaceae (grass), Betula (birch) and Quercus (oak) and to examine the relationship of these trends with meteorological factors. Betula pollen seasons show no significant trends for onset, first high day or duration but increasing pollen production in the Midlands region of the UK is being driven by warmer temperatures in the previous June and July. Quercus pollen seasons are starting earlier, due to increasing temperature and sunshine totals in April, but are not becoming more severe. The seasons are lasting longer, although no significant climate drivers for this were identified. The first high day of the Poaceae pollen season is occurring earlier in central UK regions due to an increasing trend for all temperature variables in the previous December, January, April, May and June. Severity and duration of the season show no significant trends and are spatially and temporally variable. Important changes are occurring in the UK pollen seasons that will impact on the health of respiratory allergy sufferers, with more severe Betula pollen seasons and longer Quercus pollen seasons. Most of the changes identified were caused by climate drivers of increasing temperature and sunshine total. However, Poaceae pollen seasons are neither becoming more severe nor longer. The reasons for this included a lack of change in some monthly meteorological variables, or land-use change, such as grassland being replaced by urban areas or woodland.

Pollen monitoring has traditionally been carried out using manual methods first developed in the early 1950s. Although this technique has been recently standardised, it suffers from several drawbacks, notably data usually only being available with a delay of 3–9 days and usually delivered at a daily resolution. Several automatic instruments have come on to the market over the past few years, with more new devices also under development. This paper provides a comprehensive overview of all available and developing automatic instruments, how they measure, how they identify airborne pollen, what impacts measurement quality, as well as what potential there is for further advancement in the field of bioaerosol monitoring.