Using qPCR and microscopy to assess the impact of harvesting and weather conditions on the relationship between Alternaria alternata and Alternaria spp. spores in rural and urban atmospheres.

Alternaria is a plant pathogen and human allergen. Alternaria alternata is one of the most abundant fungal spores in the air. The purpose of this study was to examine whether Alternaria spp. spore concentrations can be used to predict the abundance and spatio-temporal pattern of A. alternata spores in the air. This was investigated by testing the hypothesis that A. alternata dominates airborne Alternaria spp. spores and varies spatio-temporally. Secondarily, we aimed at investigating the relationship between airborne Alternaria spp. spores and the DNA profile of A. alternata spores between two proximate (~ 7 km apart) sites. These were examined by sampling Alternaria spp. spores using Burkard 7-day and cyclone samplers for the period 2016-2018 at Worcester and Lakeside campuses of the University of Worcester, UK. Daily Alternaria spp. spores from the Burkard traps were identified using optical microscopy whilst A. alternata from the cyclone samples was detected and quantified using quantitative polymerase chain reaction (qPCR). The results showed that either A. alternata or other Alternaria species spores dominate the airborne Alternaria spore concentrations, generally depending on weather conditions. Furthermore, although Alternaria spp. spore concentrations were similar for the two proximate sites, A. alternata spore concentrations significantly varied for those sites and it is highly likely that the airborne samples contained large amounts of small fragments of A. alternata. Overall, the study shows that there is a higher abundance of airborne Alternaria allergen than reported by aerobiological networks and the majority is likely to be from spore and hyphal fragments.

Near-ground effect of height on pollen exposure.

The effect of height on pollen concentration is not well documented and little is known about the near-ground vertical profile of airborne pollen. This is important as most measuring stations are on roofs, but patient exposure is at ground level. Our study used a big data approach to estimate the near-ground vertical profile of pollen concentrations based on a global study of paired stations located at different heights. We analyzed paired sampling stations located at different heights between 1.5 and 50 m above ground level (AGL). This provided pollen data from 59 Hirst-type volumetric traps from 25 different areas, mainly in Europe, but also covering North America and Australia, resulting in about 2,000,000 daily pollen concentrations analyzed. The daily ratio of the amounts of pollen from different heights per location was used, and the values of the lower station were divided by the higher station. The lower station of paired traps recorded more pollen than the higher trap. However, while the effect of height on pollen concentration was clear, it was also limited (average ratio 1.3, range 0.7-2.2). The standard deviation of the pollen ratio was highly variable when the lower station was located close to the ground level (below 10 m AGL). We show that pollen concentrations measured at >10 m are representative for background near-ground levels.

Isolating the species element in grass pollen allergy: A review.

Grass pollen is a leading cause of allergy in many countries, particularly Europe. Although many elements of grass pollen production and dispersal are quite well researched, gaps still remain around the grass species that are predominant in the air and which of those are most likely to trigger allergy. In this comprehensive review we isolate the species aspect in grass pollen allergy by exploring the interdisciplinary interdependencies between plant ecology, public health, aerobiology, reproductive phenology and molecular ecology. We further identify current research gaps and provide open ended questions and recommendations for future research in an effort to focus the research community to develop novel strategies to combat grass pollen allergy. We emphasise the role of separating temperate and subtropical grasses, identified through divergence in evolutionary history, climate adaptations and flowering times. However, allergen cross-reactivity and the degree of IgE connectivity in sufferers between the two groups remains an area of active research. The importance of future research to identify allergen homology through biomolecular similarity and the connection to species taxonomy and practical implications of this to allergenicity is further emphasised. We also discuss the relevance of eDNA and molecular ecological techniques (DNA metabarcoding, qPCR and ELISA) as important tools in quantifying the connection between the biosphere with the atmosphere. By gaining more understanding of the connection between species-specific atmospheric eDNA and flowering phenology we will further elucidate the importance of species in releasing grass pollen and allergens to the atmosphere and their individual role in grass pollen allergy.

Microscale pollen release and dispersal patterns in flowering grass populations.

Characterizing pollen release and dispersion processes is fundamental for knowledge advancement in ecological, agricultural and public health disciplines. Understanding pollen dispersion from grass communities is especially relevant due to their high species-specific allergenicity and heterogeneously distributed source areas. Here, we aimed to address questions concerning fine level heterogeneity in grass pollen release and dispersion processes, with a focus on characterizing the taxonomic composition of airborne grass pollen over the grass flowering season using eDNA and molecular ecology methods. High resolution grass pollen concentrations were compared between three microscale sites (<300 m apart) in a rural area in Worcestershire, UK. The grass pollen was modelled with local meteorology in a MANOVA (Multivariate ANOVA) approach to investigate factors relevant to pollen release and dispersion. Simultaneously, airborne pollen was sequenced using Illumina MySeq for metabarcoding, analysed against a reference database with all UK grasses using the R packages DADA2 and phyloseq to calculate Shannon's Diversity Index (α-diversity). The flowering phenology of a local Festuca rubra population was observed. We found that grass pollen concentrations varied on a microscale level, likely attributed to local topography and the dispersion distance of pollen from flowering grasses in local source areas. Six genera (Agrostis, Alopecurus, Arrhenatherum, Holcus, Lolium and Poa) dominated the pollen season, comprising on average 77 % of the relative abundance of grass species reads. Temperature, solar radiation, relative humidity, turbulence and wind speeds were found to be relevant for grass pollen release and dispersion processes. An isolated flowering Festuca rubra population contributed almost 40 % of the relative pollen abundance adjacent to the nearby sampler, but only contributed 1 % to samplers situated 300 m away. This suggests that most emitted grass pollen has limited dispersion distance and our results show substantial variation in airborne grass species composition over short geographical scales.

Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields.

We consider several approaches to a design of a regional-to-continent-scale automatic pollen monitoring network in Europe. Practical challenges related to the arrangement of such a network limit the range of possible solutions. A hierarchical network is discussed, highlighting the necessity of a few reference sites that follow an extended observations protocol and have corresponding capabilities. Several theoretically rigorous approaches to a network design have been developed so far. However, before starting the process, a network purpose, a criterion of its performance, and a concept of the data usage should be formalized. For atmospheric composition monitoring, developments follow one of the two concepts: a network for direct representation of concentration fields and a network for model-based data assimilation, inverse problem solution, and forecasting. The current paper demonstrates the first approach, whereas the inverse problems are considered in a follow-up paper. We discuss the approaches for the network design from theoretical and practical standpoints, formulate criteria for the network optimality, and consider practical constraints for an automatic pollen network. An application of the methodology is demonstrated for a prominent example of Germany's pollen monitoring network. The multi-step method includes (i) the network representativeness and (ii) redundancy evaluation followed by (iii) fidelity evaluation and improvement using synthetic data.

Atmospheric transport reveals grass pollen dispersion distances.

Identifying the origin of bioaerosols is of central importance in many biological disciplines, such as human health, agriculture, forestry, aerobiology and conservation. Modelling sources, transportation pathways and sinks can reveal how bioaerosols vary in the atmosphere and their environmental impact. Grass pollen are particularly important due to their widely distributed source areas, relatively high abundance in the atmosphere and high allergenicity. Currently, studies are uncertain regarding sampler representability between distance and sources for grass pollen. Using generalized linear modelling, this study aimed to analyse this relationship further by answering the question of distance-to-source area contribution. Grass pollen concentrations were compared between urban and rural locations, located 6.4 km apart, during two years in Worcestershire, UK. We isolated and refined vegetation areas at 100 m × 100 m using the 2017 CEH Crop Map and conducted atmospheric modelling using HYSPLIT to identify which source areas could contribute pollen. Pollen concentrations were then modelled with source areas and meteorology using generalized linear mixed-models with three temporal variables as random variation. We found that the Seasonal Pollen Integral for grass pollen varied between both years and location, with the urban location having higher levels. Day of year showed higher temporal variation than the diurnal or annual variables. For the urban location, grass source areas within 30 km had positive significant effects in predicting grass pollen concentrations, while source areas within 2-10 km were important for the rural one. The source area differential was likely influenced by an urban-rural gradient that caused differences in the source area contribution. Temperature had positive highly significant effects on both locations while precipitation affected only the rural location. Combining atmospheric modelling, vegetation source maps and generalized linear modelling was found to be a highly accurate tool to identify transportation pathways of bioaerosols in landscape environments.

Pollen season trends as markers of climate change impact: Betula, Quercus and Poaceae.

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.

Predicting the severity of the grass pollen season and the effect of climate change in Northwest Europe.

Allergic rhinitis is an inflammation in the nose caused by overreaction of the immune system to allergens in the air. Managing allergic rhinitis symptoms is challenging and requires timely intervention. The following are major questions often posed by those with allergic rhinitis: How should I prepare for the forthcoming season? How will the season's severity develop over the years? No country yet provides clear guidance addressing these questions. We propose two previously unexplored approaches for forecasting the severity of the grass pollen season on the basis of statistical and mechanistic models. The results suggest annual severity is largely governed by preseasonal meteorological conditions. The mechanistic model suggests climate change will increase the season severity by up to 60%, in line with experimental chamber studies. These models can be used as forecasting tools for advising individuals with hay fever and health care professionals how to prepare for the grass pollen season.

Environmental DNA reveals links between abundance and composition of airborne grass pollen and respiratory health.

Grass (Poaceae) pollen is the most important outdoor aeroallergen,1 exacerbating a range of respiratory conditions, including allergic asthma and rhinitis ("hay fever").2-5 Understanding the relationships between respiratory diseases and airborne grass pollen with a view to improving forecasting has broad public health and socioeconomic relevance. It is estimated that there are over 400 million people with allergic rhinitis6 and over 300 million with asthma, globally,7 often comorbidly.8 In the UK, allergic asthma has an annual cost of around US$ 2.8 billion (2017).9 The relative contributions of the >11,000 (worldwide) grass species (C. Osborne et al., 2011, Botany Conference, abstract) to respiratory health have been unresolved,10 as grass pollen cannot be readily discriminated using standard microscopy.11 Instead, here we used novel environmental DNA (eDNA) sampling and qPCR12-15 to measure the relative abundances of airborne pollen from common grass species during two grass pollen seasons (2016 and 2017) across the UK. We quantitatively demonstrate discrete spatiotemporal patterns in airborne grass pollen assemblages. Using a series of generalized additive models (GAMs), we explore the relationship between the incidences of airborne pollen and severe asthma exacerbations (sub-weekly) and prescribing rates of drugs for respiratory allergies (monthly). Our results indicate that a subset of grass species may have disproportionate influence on these population-scale respiratory health responses during peak grass pollen concentrations. The work demonstrates the need for sensitive and detailed biomonitoring of harmful aeroallergens in order to investigate and mitigate their impacts on human health.

Oak pollen seasonality and severity across Europe and modelling the season start using a generalized phenological model.

Oak pollen seasons are relatively unexplored in large parts of Europe despite producing allergens and being a common tree in both continental and northern parts. Many studies are concentrated only on the Iberian Peninsula. In this study, the seasonal pattern of oak pollen in Europe was analysed using 10 observation sites, ranging from Spain to Sweden. The magnitude of peaks and annual pollen integral together with season-length were studied and substantially higher pollen levels and longer seasons were found in Spain. Two northern sites in Denmark and Sweden showed high oak pollen peaks together with two sites in Spain and United Kingdom. The study also tested four common definitions of season start and applied a generalized phenological model for computing the start of the pollen season. The most accurate definition for a European-wide description of the observed oak pollen start was when the cumulative daily average pollen count reached 50 grains per cubic meter. For the modelling of the start a thermal time method based on Growing Degree Day (GDD) was implemented, utilizing daily temperatures and a generalized approach to identify model parameters applicable to all included sites. GDD values varied between sites and generally followed a decreasing gradient from south to north, with some exceptions. Modelled onsets with base temperatures below 7 °C matched well with observed onsets and 76% of the predictions differed ≤4 days compared to observed onsets when using a base temperature of 2 °C. Base temperatures above 7 °C frequently predicted onsets differing >1 week from the observed. This general approach can be extended to a larger area where pollen observations are non-existent. The presented work will increase the understanding of oak pollen variation in Europe and provide knowledge of its phenology, which is a critical aspect both for modelling purposes on large-scale and assessing the human exposure to oak allergens.

Temperate airborne grass pollen defined by spatio-temporal shifts in community composition.

Grass pollen is the world's most harmful outdoor aeroallergen. However, it is unknown how airborne pollen assemblages change across time and space. Human sensitivity varies between different species of grass that flower at different times, but it is not known whether temporal turnover in species composition match terrestrial flowering or whether species richness steadily accumulates over the grass pollen season. Here, using targeted, high-throughput sequencing, we demonstrate that all grass genera displayed discrete, temporally restricted peaks of incidence, which varied with latitude and longitude throughout Great Britain, revealing that the taxonomic composition of grass pollen exposure changes substantially across the grass pollen season.

Using DNA Metabarcoding to Identify the Floral Composition of Honey: A New Tool for Investigating Honey Bee Foraging Preferences.

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.

Changes in the pollen seasons of the early flowering trees Alnus spp. and Corylus spp. in Worcester, United Kingdom, 1996-2005.

Previous work on Betula spp. (birch) in the UK and at five sites in Europe has shown that pollen seasons for this taxon have tended to become earlier by about 5-10 days per decade in most regions investigated over the last 30 years. This pattern has been linked to the trend to warmer winters and springs in recent years. However, little work has been done to investigate the changes in the pollen seasons for the early flowering trees. Several of these, such as Alnus spp. and Corylus spp., have allergens, which cross-react with those of Betula spp., and so have a priming effect on allergic people. This paper investigates pollen seasons for Alnus spp. and Corylus spp. for the years 1996-2005 at Worcester, in the West Midlands, United Kingdom. Pollen data for daily average counts were collected using a Burkard volumetric trap sited on the exposed roof of a three-story building. The climate is western maritime. Meteorological data for daily temperatures (maximum and minimum) and rainfall were obtained from the local monitoring sites. The local area up to approximately 10 km surrounding the site is mostly level terrain with some undulating hills and valleys. The local vegetation is mixed farmland and deciduous woodland. The pollen seasons for the two taxa investigated are typically late December or early January to late March. Various ways of defining the start and end of the pollen seasons were considered for these taxa, but the most useful was the 1% method whereby the season is deemed to have started when 1% of the total catch is achieved and to have ended when 99% is reached. The cumulative catches (in grains/m(3)) for Alnus spp. varied from 698 (2001) to 3,467 (2004). For Corylus spp., they varied from 65 (2001) to 4,933 (2004). The start dates for Alnus spp. showed 39 days difference in the 10 years (earliest 2000 day 21, latest 1996 day 60). The end dates differed by 26 days and the length of season differed by 15 days. The last 4 years in the set had notably higher cumulative counts than the first 2, but there was no trend towards earlier starts. For Corylus spp. start days also differed by 39 days (earliest 1999 day 5, latest 1996 day 44). The end date differed by 35 days and length of season by 26 days. Cumulative counts and lengths of season showed a distinct pattern of alternative high (long) and low (short) years. There is some evidence of a synchronous pattern for Alnus spp.. These patterns show some significant correlations with temperature and rainfall through the autumn, winter and early spring, and some relationships with growth degree 4s and chill units, but the series is too short to discern trends. The analysis has provided insight to the variation in the seasons for these early flowering trees and will form a basis for future work on building predictive models for these taxa.