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.     

Toward optimized temperature sum parameterizations for forecasting the start of the pollen season

The start date of flowering of allergenic species is of great interest in the context of allergy. Such forecasts can help to plan the therapy and design the medical treatment. For this purpose, temperature sum models are usually employed. Designing temperature sum models requires the selection of different parameters such as the base temperature and the start date for the temperature sum. However, the optimal parameterization is often unknown and varies depending on location and species. The purpose of this study was to systematically test parameterizations of temperature sum models based on 12 Swiss pollen stations. The examined taxa include Corylus, Alnus, Fraxinus, Betula, and Poaceae. We tested the simple thermal model type (forcing-only model hereafter) which relies solely on forcing temperatures and the sequential model type that includes also chilling temperatures. The mean absolute error was used to assess the performance of the models. Our study shows that the sequential model could not achieve a discernible reduction of the (statistical) error compared to the forcing-only model for all taxa. The mean absolute error lies roughly between 2 and 4 days with the lowest values for Betula. The optimized parameterizations in combination with temperature forecast and the climatological mean were used during the 2012 pollen season to provide daily updated forecasts of the start of flowering for all five taxa. Improvements of the models could possibly be achieved by testing additional temperature parameters as well as other meteorological factors such as precipitation or irradiation. Identification of a process-oriented model with high statistical performance for all stations would facilitate the implementation in numerical pollen dispersion models.     

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.     

The influence of air temperature on the starting dates of the pollen season of alnus and populus

In this work we have studied the influence of air temperature on the starting dates of Alnus and Populus pollination in two different climatic regions in Europe: central Italy and The Netherlands. The start of the Alnus pollen season varied between 27th January and 16th February in the Italian stations while in The Netherlands it showed an average delay of about one month. For Populus the beginning of the pollen season was delayed on an average 15 days at Dutch places compared to central Italy. In the former it varied between 14th March and 21st April while in the latter between 28th February and 24th March. Significant correlations exist between the beginning of pollination for these taxa and temperature conditions in the preceding periods. The highest correlations found were with daily mean decade temperature for three decades before the average starting dates of the pollen season. These correlations were better for The Netherlands than for central Italy perhaps because the temperature in Holland is the more prominent meteorological factor (relative to precipitation) compared with central Italy, where precipitation has much influence in winter. This study indicated correlations between the pollination and temperature also during the dormant period in the preceding season.     

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.     

Pinus pollen season trend in South Spain

In Andalusia (southern Spain), Pinus species are found in mountainous areas and nature reserves, though some species are also grown as ornamentals in cities. Annual airborne pollen trends are regarded as an indicator of variations in climate prompted by overall climate change. Airborne pollen concentration also provides a useful tool for analyzing alterations in the distribution of vegetation in response to environmental factors and to changes in land use. The present study analyzed the Pinus pollen season over 22 years (1993–2014) in 4 Andalusian cities (Córdoba, Granada, Jaén, and Málaga), and examined correlations between airborne pollen concentrations and meteorological parameters (temperature and rainfall). Pinus pollen season lasted from March to June, starting first in Málaga and later in eastern Andalusia. Differences between the pollen curves for each city were attributable to differing proportions of pine species in each province. Temperatures during the months prior to flowering tended to fall, prompting delayed onset of the pollen season in most cities. No significant results were observed for rainfall patterns in most cities. Total pollen concentrations increased at most sites, suggesting that the recorded decline in pine-nut output was not influenced by flowering rates, but to the impact of a local pest.     

Long distance pollen transport cause problems for determining the timing of birch pollen season in Fennoscandia by using phenological observations

The male flowering and leaf bud burst of birch take place almost simultaneously, suggesting that the observations of leaf bud burst could be used to determine the timing of birch pollen release. However, long‐distance transport of birch pollen before the onset of local flowering may complicate the utilization of phenological observations in pollen forecasting.

We compared the timing of leaf bud burst of silver birch with the timing of the stages of birch pollen season during an eight year period (1997–2004) at five sites in Finland. The stages of the birch pollen season were defined using four different thresholds: 1) the first date of the earliest three‐day period with airborne birch pollen counts exceeding 10 grains m^?3 air; and the dates when the accumulated pollen sum reaches 2) 5%; 3) 50% and 4) 95% of the annual total. Atmospheric modelling was used to determine the source areas for the observed long‐distance transported pollen, and the exploitability of phenological observations in pollen forecasting was evaluated.

Pair‐wise comparisons of means indicate that the timing of leaf bud burst fell closest to the date when the accumulated pollen sum reached 5% of the annual total, and did not differ significantly from it at any site (p<0.05; Student‐Newman‐Keuls test). It was found that the timing of leaf bud burst of silver birch overlaps with the first half of the main birch pollen season. However, phenological observations alone do not suffice to determine the timing of the main birch pollen season because of long‐distance transport of birch pollen.     

Variation in pollen dispersal between years with different pollination conditions in a tropical emergent tree

We examined differences in pollen dispersal efficiency between 2 years in terms of both spatial dispersal range and genetic relatedness of pollen in a tropical emergent tree, Dipterocarpus tempehes. The species was pollinated by the giant honeybee (Apis dorsata) in a year of intensive community-level mass-flowering or general flowering (1996), but by several species of moths in a year of less-intensive general flowering (1998). We carried out paternity analysis based on six DNA microsatellite markers on a total of 277 mature trees forming four spatially distinct subpopulations in a 70 ha area, and 147 and 188 2-year-old seedlings originating from seeds produced in 1996 and 1998 (cohorts 96 and 98, respectively). Outcrossing rates (0.93 and 0.96 for cohorts 96 and 98, respectively) did not differ between years. Mean dispersal distances (222 and 192 m) were not significantly different between the 2 years but marginally more biased to long distance in 1996. The mean relatedness among cross-pollinated seedlings sharing the same mothers in cohort 96 was lower than that in cohort 98. This can be attributed to the two facts that the proportion of intersubpopulations pollen flow among cross-pollination events was marginally higher in cohort 96 (44%) than in cohort 98 (33%), and that mature trees within the same subpopulations are genetically more related to each other than those between different subpopulations. We conclude that D. tempehes maintained effective pollen dispersal in terms of outcrossing rate and pollen dispersal distance in spite of the large difference in foraging characteristics between two types of pollinators. In terms of pollen relatedness, however, a slight difference was suggested between years in the level of biparental inbreeding.     

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.     

Predicting ratings of perceived exertion in youth soccer using decision tree models

The purpose of this study was to determine the effectiveness of white-box decision tree models (DTM) for predicting the rating of perceived exertion (RPE). The second aim was to examine the relationship between RPE and external measures of intensity in youth soccer training at the group and individual level. Training load data from 18 youth soccer players were collected during an in-season competition period. A total of 804 training observations were undertaken, with a total of 43 ± 17 sessions per player (range 12–76). External measures of intensity were determined using a 10 Hz GPS and included total distance (TD, m/min), high-speed running distance (HSR, m/min), PlayerLoad (PL, n/min), impacts (n/min), distance in acceleration/deceleration (TD ACC/TD DEC, m/min) and the number of accelerations/decelerations (ACC/DEC, n/min). Data were analysed with decision tree models. Global and individualized models were constructed. Aggregated importance revealed HSR as the strongest predictor of RPE with relative importance of 0.61. HSR was the most important factor in predicting RPE for half of the players. The prediction error (root mean square error [RMSE] 0.755 ± 0.014) for the individualized models was lower compared to the population model (RMSE 1.621 ± 0.001). The findings demonstrate that individual models should be used for the assessment of players’ response to external load. Furthermore, the study demonstrates that DTM provide straightforward interpretation, with the possibility of visualization. This method can be used to prescribe daily training loads on the basis of predicted, desired player responses (exertion).