Forecasting daily total pollen concentrations on a global scale.

BACKGROUND: There is evidence that global anthropogenic climate change may be impacting floral phenology and the temporal and spatial characteristics of aero-allergenic pollen. Given the extent of current and future climate uncertainty, there is a need to strengthen predictive pollen forecasts. METHODS: The study aims to use CatBoost (CB) and deep learning (DL) models for predicting the daily total pollen concentration up to 14 days in advance for 23 cities, covering all five continents. The model includes the projected environmental parameters, recent concentrations (1, 2 and 4 weeks), and the past environmental explanatory variables, and their future values. RESULTS: The best pollen forecasts include Mexico City (R2(DL_7) ≈ .7), and Santiago (R2(DL_7) ≈ .8) for the 7th forecast day, respectively; while the weakest pollen forecasts are made for Brisbane (R2(DL_7) ≈ .4) and Seoul (R2(DL_7) ≈ .1) for the 7th forecast day. The global order of the five most important environmental variables in determining the daily total pollen concentrations is, in decreasing order: the past daily total pollen concentration, future 2 m temperature, past 2 m temperature, past soil temperature in 28-100 cm depth, and past soil temperature in 0-7 cm depth. City-related clusters of the most similar distribution of feature importance values of the environmental variables only slightly change on consecutive forecast days for Caxias do Sul, Cape Town, Brisbane, and Mexico City, while they often change for Sydney, Santiago, and Busan. CONCLUSIONS: This new knowledge of the ecological relationships of the most remarkable variables importance for pollen forecast models according to clusters, cities and forecast days is important for developing and improving the accuracy of airborne pollen forecasts.

Flower phenology as a disruptor of the fruiting dynamics in temperate oak species.

Many perennial plants display masting, that is, fruiting with strong interannual variations, irregular and synchronized between trees within the population. Here, we tested the hypothesis that the early flower phenology in temperate oak species promotes stochasticity into their fruiting dynamics, which could play a major role in tree reproductive success. From a large field monitoring network, we compared the pollen phenology between temperate and Mediterranean oak species. Then, focusing on temperate oak species, we explored the influence of the weather around the time of budburst and flowering on seed production, and simulated with a mechanistic model the consequences that an evolutionary shifting of flower phenology would have on fruiting dynamics. Temperate oak species release pollen earlier in the season than do Mediterranean oak species. Such early flowering in temperate oak species results in pollen often being released during unfavorable weather conditions and frequently results in reproductive failure. If pollen release were delayed as a result of natural selection, fruiting dynamics would exhibit much reduced stochastic variation. We propose that early flower phenology might be adaptive by making mast-seeding years rare and unpredictable, which would greatly help in controlling the dynamics of seed consumers.

Pollen limitation as a main driver of fruiting dynamics in oak populations.

In many perennial wind-pollinated plants, the dynamics of seed production is commonly known to be highly fluctuating from year to year and synchronised among individuals within populations. The proximate causes of such seeding dynamics, called masting, are still poorly understood in oak species that are widespread in the northern hemisphere, and whose fruiting dynamics dramatically impacts forest regeneration and biodiversity. Combining long-term surveys of oak airborne pollen amount and acorn production over large-scale field networks in temperate areas, and a mechanistic modelling approach, we found that the pollen dynamics is the key driver of oak masting. Mechanisms at play involved both internal resource allocation to pollen production synchronised among trees and spring weather conditions affecting the amount of airborne pollen available for reproduction. The sensitivity of airborne pollen to weather conditions might make oak masting and its ecological consequences highly sensitive to climate change.

Google Trends and pollen concentrations in allergy and airway diseases in France.

BACKGROUND: Google Trends (GTs) is a web-based surveillance tool that explores the searching trends of specific queries via Google. This tool proposes to reflect the real-life epidemiology of allergic rhinitis and asthma. However, the validation of GTs against pollen concentrations is missing at the country level. OBJECTIVES: In the present study, we used GTs (a) to compare the terms related to allergy in France, (b) to assess seasonal variations across the country for 5 years and (c) to compare GTs and pollen concentrations for 2016. METHODS: Google Trends queries were initially searched to investigate the terms reflecting pollen and allergic diseases. 13- and 5-year GTs were used in France. Then, 5-year GTs were assessed in all metropolitan French regions to assess the seasonality of GTs. Finally, GTs were compared with pollen concentrations (Réseau National de Surveillance en Aerobiology) for 2016 in seven regions (GTs) and corresponding cities (pollen concentrations). RESULTS: The combination of searches for "allergy" as a disease, "pollen" as a disease cause and "ragweed" as a plant was needed to fully assess the pollen season in France. "Asthma" did not show any seasonality. Using the 5-year GTs, an annual and clear seasonality of queries was found in all regions depending on the predicted pollen exposure for spring and a summer peak but not for winter peaks. The agreement between GT queries and pollen concentrations is usually poor except for spring trees and grasses. Moreover, cypress pollens are insufficiently reported by GTs. CONCLUSIONS: Google Trends cannot predict the pollen season in France.

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.

Co-exposure to highly allergenic airborne pollen and fungal spores in Europe.

The study is aimed at determining the potential spatiotemporal risk of the co-occurrence of airborne pollen and fungal spores high concentrations in different bio-climatic zones in Europe. Birch, grass, mugwort, ragweed, olive pollen and Alternaria and Cladosporium fungal spores were investigated at 16 sites in Europe, in 2005-2019. In Central and northern Europe, pollen and fungal spore seasons mainly overlap in June and July, while in South Europe, the highest pollen concentrations occur frequently outside of the spore seasons. In the coldest climate, no allergy thresholds were exceeded simultaneously by two spore or pollen taxa, while in the warmest climate most of the days with at least two pollen taxa exceeding threshold values were observed. The annual air temperature amplitude seems to be the main bioclimatic factor influencing the accumulation of days in which Alternaria and Cladosporium spores simultaneously exceed allergy thresholds. The phenomenon of co-occurrence of airborne allergen concentrations gets increasingly common in Europe and is proposed to be present on other continents, especially in temperate climate.

A temporally and spatially explicit, data-driven estimation of airborne ragweed pollen concentrations across Europe.

Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health problem across Europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for Europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we have developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant's reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating seasonal pollen integrals than those of the GM approach. These are the first published modelled maps using altitude correction and flowering phenology to recover missing pollen information. We created a web page (http://euragweedpollen.gmf.u-szeged.hu/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions.

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.

Temperature-related changes in airborne allergenic pollen abundance and seasonality across the northern hemisphere: a retrospective data analysis.

BACKGROUND: Ongoing climate change might, through rising temperatures, alter allergenic pollen biology across the northern hemisphere. We aimed to analyse trends in pollen seasonality and pollen load and to establish whether there are specific climate-related links to any observed changes. METHODS: For this retrospective data analysis, we did an extensive search for global datasets with 20 years or more of airborne pollen data that consistently recorded pollen season indices (eg, duration and intensity). 17 locations across three continents with long-term (approximately 26 years on average) quantitative records of seasonal concentrations of multiple pollen (aeroallergen) taxa met the selection criteria. These datasets were analysed in the context of recent annual changes in maximum temperature (Tmax) and minimum temperature (Tmin) associated with anthropogenic climate change. Seasonal regressions (slopes) of variation in pollen load and pollen season duration over time were compared to Tmax, cumulative degree day Tmax, Tmin, cumulative degree day Tmin, and frost-free days among all 17 locations to ascertain significant correlations. FINDINGS: 12 (71%) of the 17 locations showed significant increases in seasonal cumulative pollen or annual pollen load. Similarly, 11 (65%) of the 17 locations showed a significant increase in pollen season duration over time, increasing, on average, 0·9 days per year. Across the northern hemisphere locations analysed, annual cumulative increases in Tmax over time were significantly associated with percentage increases in seasonal pollen load (r=0·52, p=0·034) as were annual cumulative increases in Tmin (r=0·61, p=0·010). Similar results were observed for pollen season duration, but only for cumulative degree days (higher than the freezing point [0°C or 32°F]) for Tmax (r=0·53, p=0·030) and Tmin (r=0·48, p=0·05). Additionally, temporal increases in frost-free days per year were significantly correlated with increases in both pollen load (r=0·62, p=0·008) and pollen season duration (r=0·68, p=0·003) when averaged for all 17 locations. INTERPRETATION: Our findings reveal that the ongoing increase in temperature extremes (Tmin and Tmax) might already be contributing to extended seasonal duration and increased pollen load for multiple aeroallergenic pollen taxa in diverse locations across the northern hemisphere. This study, done across multiple continents, highlights an important link between ongoing global warming and public health-one that could be exacerbated as temperatures continue to increase. FUNDING: None.