Predicting the intensity of the birch pollen season

We present a model for the prediction of the magnitude ofBetula flowering and pollen dispersal which may be used in the management of birch pollinosis and in the planning of clinical trials. The pollen sum during the flowering season is regressed on the temperature sum from May 1st to July 20th during the initiation year, the pollen sum of the initiation year, and the temperature sum during the main pollen season in the flowering year. We suggest that the fluctuating flowering pattern inBetula alba-species is primarily determined by the availability of assimilation products during inflorescence initiation and development during the spring one year before anthesis. When inflorescences, which are initiated during the previous year, elongate in the beginning of anthesis, they act as strong sinks to stored carbohydrates, and thus compete with developing leaves and shoots. The result is an initially reduced photosynthetic capacity in years with intense flowering, and a limited potential for the initiation of new inflorescences for the following year. The ambient temperature during catkin initiation affects assimilation efficiency and is a determinant of about equal importance to flowering intensity as is the magnitude of the flowering in the initiation year. The amount of pollen dispersed is also dependent on the weather during anthesis, which is not possible to predict until about one month in advance. The two other independent variables are available during the previous summer, making it possible to give a sufficiently valid prediction to allergologists about the magnitude of the next birch pollen season, according to its botanical determinants. We suggest that the varying reproductive output inBetula alba should not be described as true masting. A more parsimonious explanation to the flowering pattern is that an individual continually maximizes reproductive effort, according to what is possible, but that reproduction is often constrained by the environment.     

Predicting the intensity of the birch pollen season

We present a model for the prediction of the magnitude ofBetula flowering and pollen dispersal which may be used in the management of birch pollinosis and in the planning of clinical trials. The pollen sum during the flowering season is regressed on the temperature sum from May 1st to July 20th during the initiation year, the pollen sum of the initiation year, and the temperature sum during the main pollen season in the flowering year. We suggest that the fluctuating flowering pattern inBetula alba-species is primarily determined by the availability of assimilation products during inflorescence initiation and development during the spring one year before anthesis. When inflorescences, which are initiated during the previous year, elongate in the beginning of anthesis, they act as strong sinks to stored carbohydrates, and thus compete with developing leaves and shoots. The result is an initially reduced photosynthetic capacity in years with intense flowering, and a limited potential for the initiation of new inflorescences for the following year. The ambient temperature during catkin initiation affects assimilation efficiency and is a determinant of about equal importance to flowering intensity as is the magnitude of the flowering in the initiation year. The amount of pollen dispersed is also dependent on the weather during anthesis, which is not possible to predict until about one month in advance. The two other independent variables are available during the previous summer, making it possible to give a sufficiently valid prediction to allergologists about the magnitude of the next birch pollen season, according to its botanical determinants. We suggest that the varying reproductive output inBetula alba should not be described as true masting. A more parsimonious explanation to the flowering pattern is that an individual continually maximizes reproductive effort, according to what is possible, but that reproduction is often constrained by the environment.     

An attempt to predict the start,peak and end of a pollen season

The different phases, start, peak and end of the pollen season were predicted using a cumulated activity method. This procedure is a development of the temperature sum method. The temperature was transformed to activity (A):

A = 2**[(T+g)/(10*h)] - k.

T = daily mean temperature over the treshold.

g,h,k = coefficients.

Other weather parameters are also to be included in the future.

The activity is cumulated day by day and the sum is used as an indicator of a specific phase. A cumulated activity model is defined by the above formula with specified values of the three coefficients g, h and k. Four conditions stating criteria for valid cumulation days and the cumulated target sum for the phase in question are to be defined. The model was based on pollen and weather data in Stockholm 1973–1988. The cumulated activity method was found to be best applicable to Ulmus, Betula and Pinus, but less useful for Alnus, Corylus and Quercus. The model was not satisfactory for Poaceae and Artemisia.     

Predicting the start of the birch pollen season at London, Derby and Cardiff, United Kingdom, using a multiple regression model, based on data from 1987 to 1997

Recent changes in weather in North-West Europehave been reflected in the start dates ofpollen seasons. It is therefore necessary toupdate previous models, such as the oneproduced by Jones (1995), so that the modelwill be weighted by current weather patterns. Birch pollen data, collected over a period ofeleven years (1987 to 1997 inclusive) fromthree pollen counting stations in the UK,London, Derby and Cardiff, were analysed todetermine the start dates using the Sum75method. The start dates of the birch pollenseasons of the eleven-year period were thentested for significance against ten-dayaggregated variables of temperature andrainfall for each site. The significantvariables were entered into multiple regressionmodels until the most valid equation for eachsite was found. The models were then tested onthree years not included in their data sets. The models showed mean differences betweenactual and predicted start dates, for theeleven years used, of 1.5, 3 and 5 days atDerby, Cardiff and London respectively. Forthe test years the mean difference was 1, 4.5and 7.5 days at Derby, Cardiff and Londonrespectively. The most powerful model was forDerby where the corresponding meteorologicalstation is at 0.5 km distance and the weakestwas for London where the correspondingmeteorological station is much further away at21 km distance. Weather variables from earlyFebruary to mid March were found to be the mostinfluential on the start dates of the birchpollen season at the three sites.     

Poaceae pollen in the air depending on the thermal conditions

The relationship between the meteorological elements, especially the thermal conditions and the Poaceae pollen appearance in the air, were analysed as a basis to construct a useful model predicting the grass season start. Poaceae pollen concentrations were monitored in 1991–2012 in Kraków using the volumetric method. Cumulative temperature and effective cumulative temperature significantly influenced the season start in this period. The strongest correlation was seen as the sum of mean daily temperature amplitudes from April 1 to April 14, with mean daily temperature >15 °C and effective cumulative temperature >3 °C during that period. The proposed model, based on multiple regression, explained 57 % of variation of the Poaceae season starts in 1991–2010. When cumulative mean daily temperature increased by 10 °C, the season start was accelerated by 1 day. The input of the interaction between these two independent variables into the factor regression model caused the increase in goodness of model fitting. In 2011 the season started 5 days earlier in comparison with the predicted value, while in 2012 the season start was observed 2 days later compared to the predicted day. Depending on the value of mean daily temperature from March 18th to the 31st and the sum of mean daily temperature amplitudes from April 1st to the 14th, the grass pollen seasons were divided into five groups referring to the time of season start occurrence, whereby the early and moderate season starts were the most frequent in the studied period and they were especially related to mean daily temperature in the second half of March.     

Predicting gene function using hierarchical multi-label decision tree ensembles

Background  

S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challenge, however, to develop methods that assign biological functions to the ORFs in these genomes automatically. Different machine learning methods have been proposed to this end, but it remains unclear which method is to be preferred in terms of predictive performance, efficiency and usability.     

Global warming and the earlier start of the Japanese-cedar (Cryptomeria japonica) pollen season in Toyama, Japan

Atmospheric pollen surveys were conducted in Toyama City, Japan over a 21-year period (1983–2003). Airborne pollen was collected by two methods, the gravimetric method and the volumetric method. The gravimetric method indicated that the start of the Cryptomeria japonica pollen season, as indicated by pollen dispersion, has advanced from day 73 (from January 1) in 1983 to day 47 in 2003. Measurements taken using the volumetric method confirmed this trend. There was a significant correlation between the start dates obtained by both methods. Meteorological data indicated that the most noticeable elevation in temperature during the experimental period occurred in February – an increase of 2.1°C. Significant correlations existed between the mean temperatures and the start dates of the pollen season. These results support the steadily increasing number of reports indicating a global warming trend. The temperature change in February in affecting the start dates of the C. japonica pollen season is particularly relevant in the context of human health. Further studies will be needed to clarify the effects of the global warming trend on the pollen season and human health in more detail.     

Regional variations in the pollen season of Betula in Burgundy: two models for predicting the start of the pollination

Today, 10% of the French people suffer frompollen allergy, a world-wide rising ailmentsince the end of the last century.To prevent the appearance of the symptoms, physicians need precise and early information on the pollination date of the main allergenic species. This wascarried out in Burgundy on birch (Betula), which is responsible for frequent pollinoses inMarch–April. Two of the tested methods were both successful and complementary: the sum oftemperatures and the multiple regression. The first one is very precise but only allows forecastingfive days in advance: this is enough for people suffering from rhinitis or conjunctivitis, who muststart a preventive treatment one or two days before pollination is effective. But for asthmaticpatients, the treatment must one or two weeks in advance; the second method, although alittle less precise, is interesting becauseforecasting can be done at least two weeks inadvance. The results, from 1995 to 1998, were used prospectively in 1999.     

Influence of season on rose pollen quality

Summary In vitro tests of pollen germination were carried out at different periods during an annual cycle in order to study environmental influence on the quality of Rosa hybrida L. pollen during its maturation process. This quality was evaluated by taking into account the rate of germination as well as the average length of emitted pollen tubes. In addition, during an annual hybridization period, a few pollinations were carried out in vivo with pollen of the same origin in order to study the evolution of the fertilization results, as attested by number of achenes per resulting hips. During the period covered by the experiments, the evolution of the pollen quality detected in vitro can be related to that of seed setting success. Of the two criteria used in vitro to evaluate pollen quality, the factor most liable to influence in vivo fertilization success seems to be the average length of emitted pollen tubes.     

Temporal and geographical variations in grass pollen seasons in areas of west0ern Europe: an analysis of season dates at sites of the European pollen information system

Geographical and temporal variations in the start dates of grass pollen seasons are described for selected sites of the European Pollen Information Service. Daily average grass pollen counts are derived from Network sites in Finland, the Netherlands, Denmark, United Kingdom, Austria, Italy and Spain, giving a broad longitudinal transect over Western Europe. The study is part of a larger project that also examines annual and regional variations in the severity, timing of the peak and duration of the grass pollen seasons. For several sites, data are available for over twenty years enabling long term trends to be discerned. The analyses show notable contrasts in the progression of the seasons annually with differing lag times occurring between southern and northern sites in various years depending on the weather conditions. The patterns identified provide some insight into geographical differences and temporal trends in the incidence of pollinosis. The paper discusses the main difficulties involved in this type of analysis and notes possibilities for using data from the European Pollen Information service to construct pan European predictive models for pollen seasons. This revised version was published online in June 2006 with corrections to the Cover Date.     

Trends in grass pollen season in southern Spain

The main characteristics of Poaceae pollen season at 8 sites in Andalusia were studied. Special attention was paid in the trends of grass pollen-season start and peak dates. Moreover, we analyse the intensity of the grass pollen season over the study period as well as potential temporal and spatial patterns in these data. Statistical analysis was performed to determine the possible influence of weather-related parameters on variations in the grass pollen season. Main results show an advance in the start and peak of grass pollen season and an increase in the annual Pollen Index and in the severity of the season (days > 25 pollen grains/m³). The future consequences of these changes in grass phenology could be related with changes in land use and also in pollinosis symptoms due to the higher concentrations recorded but also to the variations on pollen season dates.     

Predicting the limits to tree height using statistical regressions of leaf traits

Leaf morphology and physiological functioning demonstrate considerable plasticity within tree crowns, with various leaf traits often exhibiting pronounced vertical gradients in very tall trees. It has been proposed that the trajectory of these gradients, as determined by regression methods, could be used in conjunction with theoretical biophysical limits to estimate the maximum height to which trees can grow. Here, we examined this approach using published and new experimental data from tall conifer and angiosperm species. We showed that height predictions were sensitive to tree-to-tree variation in the shape of the regression and to the biophysical endpoints selected. We examined the suitability of proposed end-points and their theoretical validity. We also noted that site and environment influenced height predictions considerably. Use of leaf mass per unit area or leaf water potential coupled with vulnerability of twigs to cavitation poses a number of difficulties for predicting tree height. Photosynthetic rate and carbon isotope discrimination show more promise, but in the second case, the complex relationship between light, water availability, photosynthetic capacity and internal conductance to CO(2) must first be characterized.     

Two statistical approaches to forecasting the start and duration of the pollen season of Ambrosia in the area of Lyon (France)

The aim of the present study was to forecast the start and duration of the pollen season of Ambrosia from meteorological data, in order to provide early information to allergists and allergic people. We used the airborne pollen data from Lyon (France), sampled using a Hirst trap from 1987 to 1999, and the meteorological data for the same period: air temperature (minimal, maximal, and average), rainfall, relative humidity, sunshine duration and soil temperature. Two forecasting models were used, one summing the temperatures and the other making use of a multiple regression on 10-day or monthly meteorological parameters. The start of the pollen season was predicted with both methods, results being more accurate with the regression (the errors between the predicted and the observed SDP ranging from 0 to 3 days). The duration of the pollen season was predicted by a regression model, errors ranging from 0 to 7 days. The models were later tested with satisfactory results from 2 additional years (2000 and 2001). Such forecasting models are helpful for allergic people, who have to begin their anti-allergic treatment before the start of the pollen season and not when the symptoms have appeared, since a preventive treatment is more efficient than a curative one. The regression allows predictions to be made 3-5 weeks in advance and so it is of particular interest. The forecasts will be broadcast on the Internet.     

A calendar for tree pollen in London

Data from a pollen monitoring network in Islington, North London, are used to construct tree pollen calendars for the tree seasons 1987 to 1989 inclusive. Annual variations in the pollen abundance and length of flowering season are investigated for individual species in relation to meteorological factors and the inherent biological rhythms of trees. Results indicate clear relationships between seasonal variations in pollen abundance and the weather, both in the prevailing season and also in the preceeding year during the time of pollen formation. Annual variations evident in the pollen records for Betula and Quercus support the theory of inherent biennial cycles for these species. Patterns for other trees do not show clear trends within the period sampled. Insufficient information is available to determine the concentration thresholds of allergic response for most tree pollens, but evidence from Finland is used to identify the timing and duration of periods which exceed the response thresholds for Betula.     

A comparative study of different temperature accumulation methods for predicting the start of the Quercus pollen season in Cordoba (South West Spain)

The aim of the present paper is to study the influence of air temperature on the start of Quercus pollination in Córdoba (Andalusia, Spain). Sixteen years of pollen counts were used. The start date of the pollen season in this period varied between 26^th February and 7^th April. Chilling requirements and heat accumulation were taken into account although no significant correlation between chilling hours and the start date was observed. Five different predictive methods based on heat accumulation were compared in this paper: 1) Number of days over a threshold; 2) Heat Units (accumulated daily mean temperature after deducting a base temperature); 3) Growing Degrees Days (Snyder 1988), as a measure of physiological growing time; 4) Accumulated maximum temperatures; and 5) Mean maximum temperature. Results indicated that the optimum base temperature for heat accumulation was 11 C^o. This threshold was used in the first three methods mentioned above. Good statistical results were obtained with the five methods, yielding high levels of explanation (p～99%). Nevertheless, the most accurate method appeared to be the Growing Degree Days (GDD^o) method, which indicated that a mean of 127.3 GDD^o must be accumulated from the end of the chilling period up to the beginning of the Quercus pollen season in Córdoba (South West Spain). Results were tested for predicting start dates in 1999 and 2000. The predicted dates were only one day after the actual dates.     

Prediction of the birch pollen season characteristics in Cracow, Poland using an 18-year data series

The aim of the study was to construct the model forecasting the birch pollen season characteristics in Cracow on the basis of an 18-year data series. The study was performed using the volumetric method (Lanzoni/Burkard trap). The 98/95 % method was used to calculate the pollen season. The Spearman’s correlation test was applied to find the relationship between the meteorological parameters and pollen season characteristics. To construct the predictive model, the backward stepwise multiple regression analysis was used including the multi-collinearity of variables. The predictive models best fitted the pollen season start and end, especially models containing two independent variables. The peak concentration value was predicted with the higher prediction error. Also the accuracy of the models predicting the pollen season characteristics in 2009 was higher in comparison with 2010. Both, the multi-variable model and one-variable model for the beginning of the pollen season included air temperature during the last 10 days of February, while the multi-variable model also included humidity at the beginning of April. The models forecasting the end of the pollen season were based on temperature in March–April, while the peak day was predicted using the temperature during the last 10 days of March.