Abstract
The section about monitoring covers the development of phenological networks, remote sensing of the season cycle of the vegetation, the emergence of the science of aerobiology and, more specifically, aeropalynology, pollen sampling instruments, pollen counting techniques, applications of aeropalynology in agriculture and the European Pollen Information System. Three data sources are directly related with aeropalynology: phenological observations, pollen counts and remote sensing of the vegetation activity. The main future challenge is the assimilation of these data streams into numerical pollen forecast systems. Over the last decades consistent monitoring efforts of various national networks have created a wealth of pollen concentration time series. These constitute a nearly untouched treasure, which is still to be exploited to investigate questions concerning pollen emission, transport and deposition. New monitoring methods allow measuring the allergen content in pollen. Results from research on the allergen content in pollen are expected to increase the quality of the operational pollen forecasts.
In the modelling section the concepts of a variety of process-based phenological models are sketched. Process-based models appear to exhaust the noisy information contained in commonly available observational phenological and pollen data sets. Any additional parameterisations do not to improve model quality substantially. Observation-based models, like regression models, time series models and computational intelligence methods are also briefly described. Numerical pollen forecast systems are especially challenging. The question, which of the models, regression or process-based models is superior, cannot yet be answered.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-94-007-4881-1_8
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Abbreviations
- AFEDA:
-
French Association for Ragweed Study
- ANN:
-
Artificial Neural Networks
- ARIMA:
-
Autoregressive Integrated Moving Average
- AVHRR:
-
Advanced Very High Resolution Radiometer
- CART:
-
Classification and Regression Trees
- COST725:
-
COST Action 725: Establishing a European Phenological Data Platform for Climatological Applications
- CAgM:
-
Commission for Agrometeorology
- DEM:
-
Digital Elevation Model
- DWD:
-
Deutscher Wetterdienst
- EAN:
-
European Aeroallergen Network
- ELISA:
-
Enzyme-linked Immunosorbent Assay
- EUMETNET:
-
The Network of European Meteorological Services
- GIMMS:
-
Global Inventory Modeling and Mapping Studies
- IC:
-
Computational Intelligence
- IAA:
-
International Association for Aerobiology
- IBP:
-
International Biological Programme
- INERIS:
-
Industrial Environment and Risks National Institute
- IPG:
-
International Phenological Garden
- Landsat TM:
-
Landsat Thematic Mapper, Satellite
- LUT:
-
Look Up Table
- MODIS:
-
Moderate Resolution Imaging Spectroradiometer
- NDVI:
-
Normalised Difference Vegetation Index
- NHMS:
-
National Hydrometeorological Services
- NOAA:
-
National Oceanic and Atmospheric Administration
- PCR:
-
Polymerase Chain Reaction
- PEP725:
-
Pan European Phenological Database
- PM:
-
Particulate Matter
- RMSE:
-
Root Mean Square Error
- SPOT:
-
Satellite Pour l’Observation de la Terre
- SOM:
-
Self-Organising Maps
- SVMs:
-
Support Vector Machines
- TSM:
-
Temperature Sum Model
- UM:
-
Use and Management of Biological Resources
- WCDMP:
-
World Climate Data and Monitoring Programme
- WCP:
-
World Climate Programme
- WIBS:
-
Wide-Issue Bioaerosol Spectrometer
- WMO:
-
World Meteorological Organisation
References
Ahas, R., Aasa, A., Menzel, A., Fedotova, V. G., & Scheifinger, H. (2002). Changes in European spring phenology. International Journal of Climatology, 22, 1727–1738.
Aizenberg, V., Reponen, T., Grinshpun, S. A., & Willeke, K. (2000). Performance if Air-O-Cell, Burkard, and Button samplers for total enumeration of airborne spores. American Industrial Hygiene Association Journal, 61, 855–864.
Alba, F., & Díaz de la Guardia, C. (1998). The effect of air temperature on the starting dates of the Ulmus, Platanus and Olea pollen season in the SE Iberian Peninsula. Aerobiologia, 14, 191–194.
Alcalá, A. R., & Barranco, D. (1992). Prediction of flowering time in olive for the Córdoba Olive collection. HortScience, 27(11), 1205–1207.
Alcazar, P., Carinanos, P., de Castro, C., Guerra, F., Moreno, C., Dominguez Vilchez, E., & Galán, C. (2004). Airborne plane tree (Platanus hispanica) pollen distribution in the city of Cordoba, south-western Spain and possible implications on pollen allergy. Journal of Investigational Allergology and Clinical Immunology, 14(3), 238–243.
Andersen, A. A. (1958). New sampler for the collection, sizing and enumeration of viable airborne particles. Journal of Bacteriology, 76, 471–484.
Antepara, I., Fernandez, J. C., Gamboa, P., Jauregui, I., & Miguel, F. (1995). Pollen allergy in the Bilbao area (European Atlantic seaboard climate): Pollination forecasting methods. Clinical and Experimental Allergy, 25, 133–140.
Aono, Y., & Kazui, K. (2008). Phenological data series of cherry tree flowering in Kyoto, Japan, and its application to reconstruction of springtime temperatures since the 9th century. International Journal of Climatology, 28, 905–914. doi:10.1002/joc.1594.
Arizmendi, C. M., Sanchez, J. R., Ramos, N. E., & Ramos, G. I. (1993). Time-series prediction with neural nets – applications to airborne pollen forecasting. International Journal of Biometeorology, 37(3), 139–144.
Autio, J., & Hicks, S. (2004). Annual variations in pollen deposition and meteorological conditions on the fell Aakenusrunturi in northern Finland: Potential for using fossil pollen as a climate proxy. Grana, 43, 31–47.
Aznarte, J. L., Nieto Lugilde, D., Benítez, J. M., Alba Sánchez, F., & de Linares Fernández, C. (2007). Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models. Expert Systems with Applications, 32, 1218–1225.
Badeck, F. W., Bondeau, A., Böttcher, K., Doktor, D., Lucht, W., Schaber, J., & Sitch, S. (2004). Responses of spring phenology to climate change. New Phytologist, 162(2), 295–309.
BAF. (1995). Airborne pollens and spores: A guide to trapping and counting. Aylesford: The British Aerobiology Federation. 1995. ISBN 0-9525617-0-0.
Bertin Technologies (2007). Continuous cyclonic air sampler for outdoor air monitoring. http://www.coriolis-airsampler.com/resources/fichiers/coriolis/CoriolisDelta.pdf. Accessed 5 October/2010.
Bonton, P., Boucher, A., Thonnat, M., Tomczak, R., Hidalgo, P. J., Belmonte, J., & Galán, C. (2001). Colour image in 2D and 3D microscopy for the automation of pollen rate measurement. Image Analysis and Stereology, 20, 527–532.
Boucher, A., Hidalgo, P. J., Thonnat, M., Belmonte, J., Galán, C., Bonton, P., & Tomczak, R. (2002). Development of a semi-automatic system for pollen recognition. Aerobiologia, 18, 195–201.
Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1994). Time-series analysis: Forecasting and control. Upper Saddle River, NJ: Prentice-Hall International.
Bringfelt, B., Engstrom, I., & Nilsson, S. (1982). An evaluation of some models to predict airborne pollen concentration from meteorological conditions in Stockholm, Sweden. Grana, 21, 59–64.
Bryant, W. M., Jr. (1989). Yearbook of science and future (pp. 92–111). Chicago: Encyclopaedia Britannica, Inc.
Buters, J. T., Weichenmeier, I., Ochs, S., Pusch, G., Kreyling, W., & Boere, A. J. (2010). The allergen Bet v 1 in fractions of ambient air deviates from birch pollen counts. Allergy, 65, 850–858.
Carinanos, P., Emberlin, J., Galán, C., & Dominguez-Vilches, E. (2000). Comparison of two pollen counting methods of slides from a Hirst type volumetric trap. Aerobiologia, 16, 339–346.
Chen, C., Hendriks, E. A., Duin, R. P., Reiber, J. H. C., Hiemstra, P. S., de Weger, L. A., & Stoel, B. C. (2006). Feasibility study for an automatic recognition system for three relevant allergenic pollen, grass, birch and mugwort. Aerobiologia, 22, 275–284.
Chmielewski, F.-M. (2008). The international phenological gardens. In J. Nekovar, E., Koch, E., Kubin, P., Nejedlik, T., Sparks, & F. Wielgolaski (Eds.), The History and current status of plant phenology in Europe. COST Action 725 (182 p.).Brussels: COST Office.
Chuine, I. (2000). A unified model for budburst of trees. Journal of Theoretical Biology, 207, 337–347.
Chuine, I., & Belmonte, J. (2004). Improving prophylaxis for pollen allergies: Predicting the time course of the pollen load of the atmosphere of major allergenic plants in France and Spain. Grana, 43, 65–80.
Chuine, I., Cour, P., & Rousseau, D. D. (1998). Fitting models predicting dates of flowering of temperature zone trees using simulated annealing. Plan, Cell and Environment, 21, 455–466.
Chuine, I., Cour, P., & Rousseau, D. D. (1999). Selecting models to predict the timing of flowering of temperate trees: Implications for tree phenology modelling. Plant Cell and Environment, 22, 1–13.
Chuine, I., Belmonte, J., & Mignot, A. (2000). A modelling analysis of the genetic variation of phenology between tree populations. Journal of Ecology, 80, 561–570.
Chuine, I., Kramer, K., & Hänninen, H. (2003). Plant development models. In M. D. Schwartz (Ed.), Phenology: An integrative environmental science (p. 564). Dordrecht/Boston/London: Kluwer Academic Publishers.
Chytry, M., & Tichy, L. (1998). Phenological mapping in a topographically complex landscape by combining field survey with an irradiation model. Applied Vegetation Science, 1, 225–232.
Clary, J., Savé, R., Biel, C., & de Herralde, F. (2004). Water relations in competitive interactions of Mediterranean grasses and shrubs. Annals of Applied Biology, 144(2), 149–155.
Clot, B. (1998). Forecast of the Poaceae pollination in Zurich and Basel (Switzerland). Aerobiologia, 14, 267–268.
Clot, B. (2001). Airborne birch pollen in Neuchâtel (Switzerland): Onset, peak and daily patterns. Aerobiologia, 17, 25–29.
Comtois, P., Alcázar, P., & Neron, D. (1999). Pollen count statistics and its relevance to precision. Aerobiologia, 15, 19–28.
Cour, P. (1974). Nouvelles techniques de détection des flux et retombées polliniques: étude de la sédimentation des pollens et des spores à la surface du sol. Pollen et spores XVI, 1, 103–141.
Cox, C. S., & Wathes, C. M. (1995). Bioaerosol handbook (621 p.). Boca Raton, FL: Lewis Publisher.
Crepinsek, Z., Kaifez-Bogataj, L., & Bergant, K. (2006). Modelling of weather variability effect on phytophenology. Ecological Modelling, 194, 256–265.
Cristofolini, F., & Gottardini, E. (2000). Concentration of airborne pollen of Vitis vinifera L. and yield forecast: A case study at S. Michele all’Adige, Trento, Italy. Aerobiologia, 16, 125–129.
Damialis, A., Gioulekas, D., Lazopoulou, C., Balafoutis, C., & Vokou, D. (2005). Transport of airborne pollen into the city of Thessaloniki: The effects of wind direction, speed and persistence. International Journal of Biometeorology, 49, 139–145.
Damialis, A., Halley, J. M., Gioulekas, D., & Vokou, D. (2007). Long-term trends in atmospheric pollen levels in the city of Thessaloniki, Greece. Atmospheric Environment, 41, 7011–7021.
Davies, R. R., & Smith, L. P. (1973). Forecasting the start and severity of the hay fever season. Clinical Allergy, 3, 263–267.
Degaudenzi, M. E., & Arizmendi, C. M. (1998). Wavelet based fractal analysis of airborne pollen. Physical Review E, 59(2), 6569–6573.
De Linares, C., Nieto-Lugilde, D., Alba, F., Díaz de la Guardia, C., Galán, C., & Trigo, M. M. (2007). Detection of airborne allergen (Ole e 1) in relation to Olea europaea pollen in S Spain. Clinical & Experimental Allergy, 37(1), 125–132.
De Linares, C., Días de la Guardia, C., Nieto-Lugilde, D., & Alba, F. (2010). Airborne study of grass allergen (Lol p 1) in different-sized particles. International Archives of Allergy and Immunology, 152(1), 49–57.
DeLurgio, S. A. (1998). Forecasting principles and applications. New York: McGraw-Hill.
Demokritou, P., Kavouras, I. G., Ferguson, S. T., & Koutrakis, P. (2002). Development of a high volume cascade impactor for toxicological and chemical characterisation studies. Aerosol Science and Technology, 36, 925–933.
Dominguez, E., Galán, C., Villamandos, F., & Infante, F. (1991). Handling and evaluation of the data from the aerobiological sampling. Monografías REA/EAN, 1, 131–141.
Driessen, M., & Moelands, M. (1985). Estimation of the commencement of the grass pollen season and its prediction by means of the phenological method. Acta Botanica Neerlandica, 34, 131. Abstract.
Driessen, M., Van Herpen, A., Moelands, M., & Spiekma, M. (1989). Prediction of the start of the grass pollen season for the western part of the Netherlands. Grana, 28, 37–44.
Emberlin, J., & Baboonian, C. (1995). The development of a new method for sampling airborne particles for immunological analysis. Paper presented at XVI European Congress of Allergy and Clinical Immunology, ECACI 95 (pp. 39–43). Madrid: Monduzzi, Bologna.
Emberlin, J., Savage, M., & Woodman, R. (1993a). Annual variations in Betula pollen seasons in London 1961–1990. Grana, 32, 359–363.
Emberlin, J., Savage, M., & Jones, S. (1993b). Annual variations in grass pollen seasons in London 1961–1990: Trends and forecast models. Clinical and Experimental Allergy, 23, 911–918.
Emberlin, J., Jones, S., Bailey, J., Caulton, E., Corden, J., Dubbets, S., Evans, J., McDonagh, N., Millington, W., Mullins, J., Russel, R., & Spencer, T. (1994). Variation in the start of the grass pollen season at selected sites in the United Kingdom. 1987–1992. Grana, 33, 94–99.
Emberlin, J., Mullins, J., Corden, J., Jones, S., Millington, W., Brooke, M., & Savage, M. (1999). Regional variations in grass pollen seasons in the UK, long-term trends and forecast models. Clinical and Experimental Allergy, 29, 347–356.
Emberlin, J., Smith, M., Close, R., & Adams-Groom, B. (2007). Changes in the pollen seasons of the early flowering trees Alnus spp. and Corylus spp. in Worcester, United Kingdom, 1996–2005. International Journal of Biometeorology, 51, 181–191.
Erbas, B., Chang, J. H., Dharmage, S., Ong, E. K., Hyndman, R., Newbigin, E., & Abramson, M. (2007). Do levels of airborne grass pollen influence asthma hospital admissions? Clinical and Experimental Allergy, 37(11), 1641–1647.
Estrella, N., Menzel, A., Kramer, U., & Behrendt, H. (2006). Integration of flowering dates in phenology and pollen counts in aerobiology: Analysis of their spatial and temporal coherence in Germany (1992–1999). International Journal of Biometeorology, 51, 49–59.
Férnández-González, D., Valencia-Barrera, R. M., Vega, A., Díaz de la Guardia, C., Trigo, M. M., Cariñanos, P., Guardia, A., Pertiñez, C., & Rodríguez-Rajo, F. J. (1999). Analysis of grass pollen concentrations in the atmosphere of several Spanish sites. Pollen, 10, 123–132.
Fiorina, A., Scordamaglia, A., Guerra, L., & Passalacqua, G. (2003). Aerobiologic diagnosis of Brassicaceae-induced asthma. Allergy, 58, 829–830.
Fotiou, C., Damialis, A., Krigas, N., Halley, J. M., & Vokou, D. (2011). Parietaria judaica flowering phenology, pollen production, viability and atmospheric circulation, and expansive ability in the urban environment: Impacts of environmental factors. International Journal of Biometeorology, 55, 35–50.
Frei, T., & Gassner, E. (2008). Climate change and its impact on birch pollen quantities and the start of the pollen season an example form Switzerland for the period 1969–2006. International Journal of Biometeorology, 52, 667–674.
Frenguelli, G. (1998). The contribution of aerobiology to agriculture. Aerobiologia, 14, 95–100.
Frenguelli, G., & Bricchi, E. (1998). The use of the pheno-climatic model for forecasting the pollination of some arboreal taxa. Aerobiologia, 14, 39–44.
Frenguelli, G., Bricchi, E., Romano, B., Mincigrucci, G., & Spieksma, F. Th. M. (1989). A predictive study on the beginning of the pollen season for Gramineae and Olea europaea L. Aerobiologia, 5, 64–70.
Galán, C., Emberlin, J., Dominguez-Vilches, E., Bryant, R. H., & Villamandos, F. (1995). A comparative analysis of daily variations in the Gramineae pollen counts at Cordoba, Spain and London, UK. Grana, 34, 189–198.
Galán, C., Fuillerat, M. J., Comtois, P., & Dominguez-Vilches, E. (1998). A predictive study of Cupressaceae pollen season onset, severity, maximum value and maximum value date. Aerobiologia, 14, 195–199.
Galán, C., Alcazar, P., Cariñanos, P., García-Mozo, H., & Dominguez-Vilches, E. (2000). Meteorological factors affecting daily Urticaceae pollen counts in southwest Spain. International Journal of Biometeorology, 43, 191–195.
Galán, C., García-Mozo, H., Cariñanos, P., Alcázar, P., & Domínguez-Vilches, E. (2001a). The role of temperature in the onset of the Olea europaea L. pollen season in southwestern Spain. International Journal of Biometeorology, 45(1), 8–12.
Galán, C., Carinanos, P., García-Mozo, H., Alcazar, P., & Dominguez-Vilches, E. (2001b). Model for forecasting Olea europaea L. airborne pollen in South-West Andalusia, Spain. International Journal of Biometeorology, 45, 59–93.
Galán, C., Vazquez, L., García-Mozo, H., & Dominguez-Vilches, E. (2004). Forecasting olive (Olea europea) crop yield based on pollen emission. Field Crops Research, 86, 43–51.
Galán, C., García-Mozo, H., Vazquez, L., Ruiz-Valenzuela, L., Díaz de la Guardia, C., & Trigo-Perez, M. (2005). Heat requirement for the onset of the Olea europaea L. pollen season in several places of Andalusia region and the effect of the expected future climate change. International Journal of Biometeorology, 49(3), 184–188.
Galán, C., Cariñanos, P., Alcázar, P., & Dominguez-Vilches, E. (2007). Spanish Aerobiology Network (REA) management and quality manual. Cordoba: Servicio de Publicaciones Universidad de Córdoba. ISBN 978-84-690-6353-8.
Galán, C., García-Mozo, H., Vázquez, L., Ruiz, L., Díaz de la Guardia, C., & Domínguez-Vilches, E. (2008). Modelling olive (Olea europaea L.) crop yield in Andalusia Region, Spain. Agronomy Journal, 100(1), 98–104.
García-Mozo, H., Galán, C., Gomez-Casero, M. T., & Dominguez-Vilches, E. (2000). A comparative study of different temperature accumulation methods for predicting the start of the Quercus pollen season in Cordoba (South West Spain). Grana, 39, 194–199.
García-Mozo, H., Hidalgo, P. J., Galán, C., & Gomez-Casero, M. T. (2001). Catkin frost damage in Mediterranean cork-oak (Quercus suber L.). Israel Journal of Plant Sciences, 49, 41–47.
García-Mozo, H., Galán, C., Aira, M. J., Belmonte, J., Díaz de la Guardia, C., Fernández, D., Gutierrez, A. M., Rodriguez, F. J., Trigo, M. M., & Dominguez-Vilches, E. (2002). Modelling start of oak pollen season in different climatic zones in Spain. Agricultural and Forest Meteorology, 110, 247–257.
García-Mozo, H., Galán, C., Jato, V., Belmonte, J., Díaz de la Guardia, C., Fernández, D., Gutiérrez, M., Aira, M. J., Roure, J. M., Ruiz, L., Trigo, M. M., & Domínguez-Vilches, E. (2006). Quercus pollen season dynamics in the Iberian Peninsula: Response to meteorological parameters and possible consequences of climate change. Annals of Agricultural and Environmental Medicine, 13, 209–224.
García-Mozo, H., Perez-Badía, R., & Galán, C. (2007a). Aerobiological and meteorological factors influence on olive (Olea europaea L.) crop yield in Castilla-La Mancha (Central Spain). Aerobiologia, 24(1), 13–18.
García-Mozo, H., Gómez-Casero, M. T., Dominguez-Vilches, E., & Galán, C. (2007b). Influence of pollen emission and weather-related factors on variations in holm-oak (Quercus ilex subsp. ballota) acorn production. Environmental and Experimental Botany, 61, 35–40.
García-Mozo, H., Chuine, I., Aira, M. J., Belmonte, J., Bermejo, D., Díaz de la Guardia, C., Elvira, B., Gutiérrez, M., Rodríguez-Rajo, J., Ruiz, L., Trigo, M. M., Tormo, R., Valencia, R., & Galán, C. (2008). Regional phenological models for forecasting the start and peak of the Quercus pollen season in Spain. Agricultural and Forest Meteorology, 148, 372–380.
García-Mozo, H., Galán, C., Belmonte, J., Bermejo, D., Candau, P., Díaz de la Guardia, C., Elvira, B., Gutiérrez, M., Jato, V., Silva, I., Trigo, M. M., Valencia, R., & Chuine, I. (2009). Predicting the start and peak dates of the Poaceae pollen season in Spain using process-based models. Agriculture and Forest Meteorology, 149, 256–262.
Gerad-Peeters, A. (1998). Cumulative temperatures for prediction of the beginning of ash (Fraxinus excelsior L.) pollen season. Aerobiologia, 14, 375–381.
Goldberg, C., Buch, H., Moseholm, L., & Weeke, E. V. (1988). Airborne pollen records in Denmark, 1977–1986. Grana, 27, 209–217.
Govindaraju, D. R. (1988). The relationship between dispersal ability and levels of gene flow in plants. Oikos, 52, 31–35.
Graham, J. A. H., Pavlicek, P. K., Sercombe, J. K., Xavier, M. L., & Tovey, E. R. (2000). The nasal air sampler: A device for sampling inhaled aeroallergens. Annals of Allergy, Asthma, & Immunology, 84, 599–604.
Grivas, G., & Chaloulakou, A. (2006). Artificial neural network models for prediction of Pm10 hourly concentrations, in the Greater Area of Athens, Greece. Atmospheric Environment, 40(7), 1216–1230.
Guyot, G., Gugon, D., & Riom, J. (1989). Factors affecting the spectral response of forest canopies: A review. Geocarta International, 3, 43–60.
Halley, J. M., & Inchausti, P. (2004). The increasing importance of 1/f-noises as models of ecological variability. Fluctuation and Noise Letters, 4, R1–R26.
Hänninen, H. (1995). Effects of climatic change on trees from cool and temperate regions: An ecophyisological approach to modelling of budburst phenology. Canadian Journal of Botany, 73, 183–199.
Haykin, S. (1999). Neural networks, a comprehensive foundation. Upper Saddle River, NJ: Prentice Hall.
Helbig, N., Vogel, B., Vogel, H., & Fiedler, F. (2004). Numerical modelling of pollen dispersion on the regional scale. Aerobiologia, 3, 3–19.
Hidalgo, P. J., Mangin, A., Galán, C., Hembise, O., Vazquez, L. M., & Sanchez, O. (2002). An automated system for surveying and forecasting Olea pollen dispersion. Aerobiologia, 18, 23–31.
Hirst, J. M. (1952). An automatic volumetric spore trap. The Annals of Applied Biology, 39(2), 257–265.
Høgda, K. A., Karlsen, S. R., Solheim, I., Tømmervik, H., & Ramfjord, H. (2003). The start dates of birch pollen seasons in Fennoscandia studied by NOAA AVHRR NDVI data. Paper presented at geoscience and remote sensing symposium, 2002. IGARSS’02. IEEE International, 6, 3299–3301.
Holben, B. N. (1986). Characteristics of maximum-value composite images for temporal AVHRR data. International Journal of Remote Sensing, 7, 1435–1445.
Hudson, I. L., Kim, S. W., & Keatley, M. R. (2010). Modelling the flowering of four Eucalypt species using new mixture transition distribution models. In I. L. Hudson & M. R. Keatley (Eds.), Phenological research: Methods for environmental and climate change analysis. Dordrecht/Heidelberg/London/New York: Springer. 521 p.
Huynen, M., Menne, B., Behrendt, H., Bertollini, R., Bonini, S., Brandao, R., Brown-Fährlander, C., Clot, B., D’Ambrosio, C., De Nuntiis, P., Ebi, K. L., Emberlin, J., Orbanne, E. E., Galán, C., Jäger, S., Kovats, S., Mandrioli, P., Martens, P., Menzel, A., Nyenzi, B., Rantio Lehtimäki, A., Ring, J., Rybnicek, O., Traidl-Hoffmann, T., Van Vliet, A., Voigt, T., Weiland, S., & Wickman, M. (2003). Phenology and human health: Allergic disorders. Report of a WHO meeting, Rome, Italy.
Iglesias, I., Rodriguez-Rajo, F. J., & Mendez, J. (2007). Behavior of Platanus hispanica pollen, an important spring aeroallergen in northwestern Spain. Journal of Investigational Allergology and Clinical Immunology, 17(3), 145–156.
Ihne, E. (1885). Karte der Aufblühzeit von Syringa vulgaris in Europa. Botanisches Centralblatt, 21, 85–88, 116–121, 150–155.
Jato, V., Frenguelli, G., Rodríguez, F. J., & Aira, M. J. (2000). Temperature requirements of Alnus pollen in Spain. Grana, 39, 240–245.
Jeanneret, F., & Rutishauser, T. (2010). Phenology for topoclimatological surveys and large-scale mapping. In I. L. Hudson & M. R. Keatley (Eds.), Phenological research: Methods for environmental and climate change analysis. Dordrecht/Heidelberg/London/New York: Springer. 521 p.
Kapyla, M., & Penttinen, A. (1981). An evaluation of the microscopical counting methods of the tape in Hirst-Burkard pollen and spore trap. Grana, 20, 131–141.
Karatzas, K., & Kaltsatos, S. (2007). Air pollution modelling with the aid of computational intelligence methods in Thessaloniki, Greece. Simulation Modelling Practice and Theory, 15(10), 1310–1319.
Karlsen, S. R., Elvebakk, A., Høgda, K. A., & Johansen, B. (2006). Satellite based mapping of the growing season and bioclimatic zones in Fennoscandia. Global Ecology and Biogeography, 15, 416–430.
Karlsen, S. R., Solheim, I., Beck, P. S. A., Høgda, K. A., Wielgolaski, F. E., & Tømmervik, H. (2007). Variability of the start of the growing season in Fennoscandia, 1982–2002. International Journal of Biometeorology, 51, 513–524. doi:10.1007/s00484-007-0091-x.
Karlsen, S. R., Ramfjord, H., Høgda, K. A., Johansen, B., Danks, F. S., & Brobakk, T. E. (2009a). A satellite-based map of onset of birch (Betula) flowering in Norway. Aerobiologia, 25, 15–25.
Karlsen, S. R., Høgda, K. A., Ramfjord, H., Brobakk, T. E., & Johansen, B. (2009b). Use of satellite data in near real-time monitoring of the birch flowering in Norway. Paper presented at the 12th Nordic Symposium on Aerobiology, Copenhagen, Denmark, August 28–30.
Kawashima, S., & Takahashi, Y. (1995). Modelling and simulation of mesoscale dispersion processes for airborne cedar pollen. Grana, 34, 142–150.
Kawashima, S., Clot, B., Fujita, T., Takahashi, Y., & Nakamura, K. (2007). An algorithm and a device for counting airborne pollen automatically using laser optics. Atmospheric Environment, 41, 7987–7993.
Kinnear, P. R., & Gray, C. D. (1999). SPSS for Windows Made Simple. Padstow: T.J. International.
Koch, E. (2010). Global framework for data collection – data bases, data availability, future networks, online databases. In I. L. Hudson & M. R. Keatley (Eds.), Phenological research: Methods for environmental and climate change analysis. Dordrecht: Springer. 522 p.
Koch, E., Dittmann, E., Lipa, W., Menzel, A., & van Vliet, A. (2005). COST 725 Establishing a European phenological data platform for climatological purposes. Annalen der Meteorologie 41(2), 554–558. DWD.
Koch, E., Demarée, G., Lipa, W., Zach, S., & Zimmermann, K. (2008). History of international phenology networks. In J. Nekovar, E. Koch, E. Kubin, P. Nejedlik, T. Sparks, & F.-E. Wielgolaski (Eds.), The history and current status of plant phenology in Europe – COST Action 725: Establishing a European Data Platform for Climatological Purposes. Sastamala: Vammalan Kirjapaino Oy, COST Office. ISBN 978-951-40-2091-9.
Kramer, K. (1994). A modelling analysis of the effects of climatic warming on the probability of spring frost damage to tree species in The Netherlands and Germany. Plant, Cell and Environment, 17, 367–377.
Kramer, K. (1995). Phenotypic plasticity of the phenology of seven European tree species in relation to climatic warming. Plant, Cell and Environment, 18, 93–104.
Kukkonen, J., Partanen, L., Karppinen, A., Ruuskanen, J., Junninen, H., Kolehmainen, M., Niska, H., Dorling, S., Chatterton, T., Foxall, R., & Cawley, G. (2003). Extensive evaluation of neural network models for the prediction of NO2 and PM10 concentrations, compared with a deterministic modelling system and measurements in central Helsinki. Atmospheric Environment, 37(32), 4539–4550.
Laaidi, M. (2001a). Forecasting the start of the pollen season of Poaceae: Evaluation of some methods based on meteorological factors. International Journal of Biometeorology, 45(1), 1–7.
Laaidi, M. (2001b). Regional variations in the pollen season of Betula in Burgundy: Two models for predicting the start of the pollination. Aerobiologia, 17, 247–254.
Laaidi, M., Thibaudon, M., & Besancenot, J.-P. (2003). Two statistical approaches to forecasting the start and duration of the pollen season of Ambrosia in the area of Lyon (France). International Journal of Biometeorology, 48, 65–73.
Landsmeer, S. H., Hendriks, E. A., de Weger, L. A., Reiber, J. H., & Stoel, B. C. (2009). Detection of pollen grains in multifocal optical microscopy images of air samples. Microscopy Research and Technique, 72, 424–430.
Levetin, E., Rogers, C. A., & Hall, S. A. (2000). Comparison of pollen sampling with a Burkard Spore Trap and a Tauber Trap in a warm temperate climate. Grana, 39, 294–302.
Lillesand, T. M., & Kiefer, R. (1994). Remote sensing and image interpretation (3rd ed.). New York: Wiley.
Linkosalo, T. (1999). Regularities and patterns in the spring phenology of some boreal trees. Silva Fennica, 33, 237–245.
Linkosalo, T. (2000). Mutual regularity of spring phenology of some boreal tree species: Predicting with other species and phenological models. Canadian Journal of Forest Research, 30, 667–673.
Linkosalo, T., Häkkinen, R., & Hänninen, H. (2006). Models of the spring phenology of boreal and temperate trees: Is there something missing? Tree Physiology, 26, 1165–1172.
Linkosalo, T., Lappalainen, H. K., & Hari, P. (2008). A comparison of phenological models of leaf bud burst and flowering of boreal trees using independent observations. Tree Phyisology, 28, 1873–1882.
Linkosalo, T., Häkkinen, R., Terhivuo, J., Tuomenvirta, H., & Hari, P. (2009). The time series of flowering and leaf bud burst of boreal trees (1846–2005) support the direct temperature observations of climatic warming. Agricultural and Forest Meteorology, 149(3–4), 453–461.
Linkosalo, T., Ranta, H., Oksanen, A., Siljamo, P., Luomajoki, A., Kukkonen, J., & Sofiev, M. (2010). A double-threshold temperature sum model for predicting the flowering duration and relative intensity of Betula pendula and B. pubescens. Agricultural and Forest Meteorology, 150, 1579–1584.
Litschauer, R. (2003). Untersuchungen zum Reproduktionspotential im Bergwald. FBVA, 130, 79–85.
Makinen, Y. (1981). Random sampling in the study of microscopic slides. Reports from the Aerobiological Laboratory, University of Turku, 5, 27–43.
Makra, L., Juhasz, M., Borsos, E., & Beczi, R. (2004). Meteorological variables connected with airborne ragweed pollen in southern Hungary. International Journal of Biometeorology, 49, 37–47.
Mandrioli, P. (1990). The Italian Aeroallergen Network. Sampling and counting method. Aerobiologia, 6, 5–7.
Mandrioli, P., & Ariatti, A. (2001). Aerobiology: Future course of action. Aerobiologia, 17, 1–10.
Marletto, V., Puppi Branzi, G., & Sirotti, M. (1992). Forecasting flowering dates of lawn species with air temperatures: Application boundaries of the linear approach. Aerobiologia, 8, 75–83.
Mendez, J., Comptois, P., & Iglesias, I. (2005). Betula pollen: One of the most important aeroallergens in Ourense, Spain. Aerobiological studies from 1993 to 2000. Aerobiologia, 21, 115–123.
Menzel, A. (1997). Phänologie von Waldbäumen unter sich ändernden Klimabedingungen – Auswertung der Beobachtungen in den Internationalen Phänologischen Gärten und Möglichkeiten der Modellierung von Phänodaten. Forstliche Forschungsberichte 164/1997 (147 p.). Forstwissenschaftliche Fakultät der Universität München und der Bayerischen Landesanstalt für Wald und Forstwirtschaft.
Migliavacca, M., Cremonese, E., Colombo, R., Busetto, L., Galvagno, M., Ganis, L., Meroni, M., Pari, E., Rossini, M., Siniscalco, C., & Morra di Cella, U. (2008). European larch phenology in the Alps: Can we grasp the role of ecological factors by combining field observations and inverse modelling? International Journal of Biometeorology, 52(7), 587–605.
Moriondo, M., Orlandini, S., De Nuntiis, P., & Mandrioli, P. (2001). Effect of agrometeorological parameters on the phenology of pollen emission and production of olive trees (Olea europea L.). Aerobiologia, 7, 225–232.
Moseholm, L., Weeke, E. R., & Petersen, B. N. (1987). Forecast of pollen concentrations of Poaceae (grasses) in the air by time series analysis. Pollen et Spores, 19(2–3), 305–322.
Mullins, J., & Emberlin, J. (1997). Sampling pollen. Journal of Aerosol Science, 28, 365–370.
Myneni, R. B., Keeling, C. D., Tucker, C. J., Asrar, G., & Nemani, R. R. (1997). Increased plant growth in the northern high latitudes from 1981 to 1991. Nature, 386, 698–702.
Nekovar, J., Koch, E., Kubin, E., Nejedlik, P., Sparks, T., & Wielgolaski, F. (Eds., 2008). COST Action 725, The History and current status of plant phenology in Europe (182 p.). Brussels: COST Office.
Norris-Hill, J. (1995). The modelling of daily Poaceae pollen concentrations. Grana, 34, 182–188.
Norris-Hill, J. (1998). A method to forecast the start of the Betula, Platanus and Quercus pollen seasons in North London. Aerobiology, 14, 165–170.
Ocana-Peinado, F., Valderrama, M. J., & Aguilera, A. M. (2008). A dynamic regression model for air pollen concentration. Stochastic Environmental Research and Risk Assessment, 22, 59–63.
Ong, E. K., Taylor, P. E., & Knox, R. B. (1997). Forecasting the onset of the grass pollen season in Melbourne (Australia). Aerobiologia, 13, 43–48.
Orlandi, F., Garcia-Mozo, H., Vazquez Ezquerra, L., Romano, B., Dominguez, E., Galán, C., & Fornaciari, M. (2004). Phenological olive chilling requirements in Umbria (Italy) and Andalusia (Spain). Plant Biosystems, 138(2), 111–116.
Orlandi, F., Vazquez, L. M., Ruga, L., Bonofiglio, T., Fornaciari, M., Garcia-Mozo, H., Dominguez, E., Romano, B., & Galán, C. (2005). Bioclimatic requirements for olive flowering in two Mediterranean regions located at the same latitude (Andalucía, Spain, and Sicily, Italy). Annals of Agricultural and Environmental Medicine, 12, 47–52.
Orlandi, F., Lanari, D., Romano, B., & Fornaciari, M. (2006). New model to predict the timing of olive (Olea europaea) flowering: A case study in central Italy. New Zealand Journal of Crop and Horticultural Science, 34, 93–99.
Pallant, J. (2001). SPSS Survival Manual. Buckingham: Open University Press.
Pasken, R., & Pietrowicz, J. A. (2005). Using dispersion and mesoscale meteorological models to forecast pollen concentrations. Atmospheric Environment, 39, 7689–7701.
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1992). Numerical recipes: The art of scientific computing. New York: Cambridge University Press. 963 p.
Puppi, G., & Zanotti, A. L. (1989). Methods in phenological mapping. Aerobiologia, 5, 44–54.
Puppi, G., & Zanotti, A. L. (1992). Estimate and mapping of the activity of airborne pollen sources. Aerobiologia, 8(1), 69–74.
Rantio-Lehtimaki, A., Viander, M., & Koivikko, A. (1994). Airborne birch antigens in different particle sizes. Clinical and Experimental Allergy, 24, 23–28.
Ranzi, A., Lauriola, P., Marletto, V., & Zinoni, F. (2003). Forecasting airborne pollen concentrations: Development of local models. Aerobiologia, 19, 39–45.
Reaumur, R. A. F. de. (1735). Observations du thermomètre, faites a Paris pendant l´année 1735, comparée avec celles qui ont été faites sous la ligne, a lísle de France, a Alger et quelque unes de nos isles de l´Amérique. Memoire de l´Académie des Sciences de Paris.
Ribeiro, H., Cunha, M., & Abreu, I. (2006). Comparison of classical models for evaluating the heat requirements of olive (Olea europeae L.) in Portugal. Journal of Integrative Plant Biology, 48(6), 664–671. doi:10.1111/j.1744-7909.2006.00269.x.
Rodriguez Rajo, F. J., Dopazo, A., & Jato, V. (2004). Environmental factors affecting the start of the pollen season and concentrations of airborne Alnus pollen in two localities of Galicia (NW Spain). Annals of Agricultural and Environmental Medicine, 11, 35–44.
Rodriguez Rajo, F. J., Medez, J., & Jato, V. (2005). Factors affecting pollination ecology of Quercus anemophilous species in north-west Spain. Botanical Journal of the Linnean Society, 149, 283–297.
Rodriguez-Rajo, F. J., Valencia-Barrera, R. M., Vega-Maray, A. M., Suarez, F. J., Fernandez-Gonzalez, D., & Jato, V. (2006). Prediction of airborne Alnus pollen concentration by using ARIMA models. Annals of Agricultural and Environmental Medicine, 13, 25–32.
Rogers, C. (2006). Knowledge gaps and hot topics in aerobiology. Paper presented at the 8th International Congress in Aerobiology, Neuchatel Switzerland.
Ronneberger, O. (2007). 3D invariants for automated pollen recognition. Thesis. Freiburg im Breisgau: University of Freiburg.
Ronneberger, O., Schultz, E., & Burkhardt, H. (2002). Automated pollen recognition using 3D volume images from fluorescence microscopy. Aerobiologia, 18, 107–115.
Rosenzweig, C., Casassa, G., Karoly, D. J., Imeson, A., Liu, C., Menzel, A., Rawlins, S., Root, T. L., Seguin, B., & Tryjanowski, P. (2007). Assessment of observed changes and responses in natural and managed systems. In M. L. Parry, O. F. Canziani, J. P. Palutikof, P. J. van der Linden, & C. E. Hanson (Eds.), Climate Change 2007: Impacts, adaptation and vulnerability (Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, pp. 79–131). Cambridge: Cambridge University Press.
Rötzer, Th, & Chmielewski, F.-M. (2001). Phenological maps of Europe. Climate Research, 18, 249–257.
Sánchez-Mesa, J. A., Galán, C., Martínez-Heras, J. A., & Hervás-Martínez, C. (2002). The use of a neural network to forecast daily grass pollen concentration in a Mediterranean region: The southern part of the Iberian Peninsula. Clinical and Experimental Allergy, 32, 1606–1612.
Sánchez-Mesa, J. A., Smith, M., Emberlin, J., Allitt, U., Caulton, E., & Galán, C. (2003). Characteristics of grass pollen seasons in areas of southern Spain and the United Kingdom. Aerobiologia, 19, 243–250.
Schaber, J., & Badeck, F.-W. (2003). Physiology-based phenology models for forest tree species in Germany. International Journal for Biometeorology, 47, 193–201.
Scheifinger, H., Menzel, A., Koch, E., Peter, Ch, & Ahas, R. (2002). Atmospheric mechanisms governing the spatial and temporal variability of phenological observations in central Europe. International Journal of Climatology, 22, 1739–1755.
Schueler, S., Schlunzen, K. H., & Scholz, F. (2005). Viability and sunlight sensitivity of oak pollen and its implications for pollen-mediated gene flow. Trees, 19, 154–161.
Schwartz, M. D. (Ed.). (2003). Phenology: An integrative environmental science. Dordrecht/Boston/London: Kluwer Academic Publishers. 564 pp.
Siljamo, P., Sofiev, M., Ranta, H., Linkosalo, T., Kubin, E., Ahas, R., Genikhovich, E., Jatczak, K., Jato, V., Nekovar, J., Minin, A., Severova, E., & Shalaboda, V. (2008). Representativeness of point-wise phenological Betula data collected in different parts of Europe. Global Ecology and Biogeography, 17(4), 489–502.
SKC (2010). Button Aerosol Sampler. http://www.skcinc.com/prod/225-360.asp. Accessed 5 October/2010.
Slini, T., Kaprara, A., Karatzas, K., & Moussiopoulos, N. (2006). PM10 forecasting for Thessaloniki, Greece. Environmental Modelling & Software, 21, 559–565.
Smith, M., & Emberlin, J. (2005). Constructing a 7-day ahead forecast model for grass pollen at north London, United Kingdom. Clinical and Experimental Allergy, 35, 1400–1406.
Smith, M., & Emberlin, J. (2006). A 30-day-ahead forecast model for grass pollen in north London, United Kingdom. International Journal of Biometeorology, 50, 233–242.
Sodeau, J., O’Connor, D., Hellebust, S., & Healy, D. (2010). Real-time spectrocopic measurments of PBAP in field and laboratory envirnments. Paper presented at the 9th International Congress on Aerobiology, Buenos Aires.
Sofiev, M., Siljamo, P., Ranta, H., & Rantio-Lehtimäki, A. (2006). Towards numerical forecasting of long-range air transport of birch pollen: Theoretical considerations and a feasibility study. International Journal of Biometeorology, 50, 392–402.
Spieksma, F. T., & Nikkels, A. H. (1998). Airborne grass pollen in Leiden, The Netherlands: Annual variations and trends in quantities and season starts over 26 years. Aerobiologia, 14, 347–358.
Spieksma, F. T., & Nikkels, A. H. (1999). Similarity in seasonal appearance between atmospheric birch-pollen grains and allergen in paucimicronic, size-fractionated ambient aerosol. Allergy, 54(3), 235–241.
Spieksma, F. T., Kramps, J. A., Van der Linden, A. C., Nikkels, B. H., Plomp, A., Koerten, H. K., & Dijkman, J. H. (1990). Evidence of grass-pollen allergenic activity in the smaller micronic atmosphere aerosol fraction. Clinical and Experimental Allergy, 20, 273–280.
Stach, A., Smith, M., Prieto Baena, J. C., & Emberlin, J. (2008). Long-term and short-term forecast models for Poaceae (grass) pollen in Poznań, Poland, constructed using regression analysis. Environmental and Experimental Botany, 62, 232–332.
Stark, P. C., Ryan, L. M., McDonald, J. L., & Burge, H. A. (1997). Using meteorologic data to predict daily ragweed pollen levels. Aerobiologia, 13, 177–184.
Stephen, E., Raftery, A. E., & Dowding, P. (1990). Forecasting spore concentrations – a time-series approach. International Journal of Biometeorology, 34, 87–89.
Sterling, M., Rogers, C., & Levetin, E. (1999). An evaluation of two methods used for microscopic analysis of airborne fungal spore concentrations from the Burkard Spore Trap. Aerobiologia, 15, 9–18.
Stöckli, R., & Vidale, P. L. (2004). European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter data set. International Journal of Remote Sensing, 25, 3303–3330.
Stöckli, R., Rutishauser, T., Dragoni, D., O’Keefe, J., Thornton, P. E., Jolly, M., Lu, L., & Denning, A. S. (2008). Remote sensing data assimilation for a prognostic phenology model. Journal of Geophysical Research, 113, G04021. doi:10.1029/2008JG000781.
Stokstad, E. (2002). A little pollen goes a long way. Science, 296, 2314.
Suzuki, M., Tonouchi, M., & Murayama, K. (2008). Automatic measurements of Japanese cedar/cypress pollen concentration and the numerical forecasting at Tokyo metropolitan area.(Paper presented at the International Congress of Biometeorology, September 2008.
Tabachnick, B. G., & Fidell, L. S. (2001). Using Multivariate Statistics. New York: Harper Collins.
Tedeschini, E., Rodriguez-Rajo, F. J., Caramiello, R., Jato, V., & Frenguelli, G. (2006). The influence of climate changes in Platanus spp. pollination in Spain and Italy. Grana, 45, 222–229.
Thibaudon, M., & Lachasse, C. (2005). Phénologie: Intérêt et méthodes en aérobiologie – Interest of phenology in relation to aerobiology. Revue française d’allergologie et d’immunologie clinique, 45, 194–199.
Tormo, R., Munoz, A., & Silva, I. (1996). Sampling in aerobiology. Differences between traverses along the length of the slide in Hirst spore traps. Aerobiologia, 12, 161–166.
Toro, F. J., Recio, M., Trigo, M. M., & Cabezudo, B. (1998). Predictive models in aerobiology: Data transformation. Aerobiologia, 14, 179–184.
Torrigiani Malaspina, T., Cecchi, L., Morabito, M., Onorari, M., Domeneghetti, M. P., & Orlandini, S. (2007). Influence of meteorological conditions on male flower phenology of Cupressus sempervirens and correlation with pollen production in Florence. Trees, 21(5), 507–514.
Tucker, C. J., Pinzon, J. E., Brown, M. E., Slayback, D., Pak, E. W., Mahoney, R., Vermote, E., & El Saleous, N. (2005). An extended AVHRR 8-km NDVI data set compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing, 26(20), 4485–5598.
Tzima, F., Karatzas, K., Mitkas, P., & Karathanasis, S. (2007). Using data-mining techniques for PM10 forecasting in the metropolitan area of Thessaloniki, Greece, IEEE International Conference on Neural Networks – Conference Proceedings, art. no. 4371394 (pp. 2752–2757). Proceedings of the 20th International Joint Conference on Neural Networks (http://www.ijcnn2007.org. Organized by the IEEE Computational Intelligence Society and by the International Neural Network Society, Orlando, Florida, August 2007).
van Vliet, A. J. H., Overeem, A., de Groot, R. S., Jacobs, A. F. G., & Spieksma, F. T. M. (2002). The influence of temperature and climate change on the timing of pollen release in The Netherlands. International Journal of Climatology, 22, 1757–1767.
Vogel, H., Pauling, A., & Vogel, B. (2008). Numerical simulation of birch pollen dispersion with an operational weather forecast system. International Journal of Biometeorology, 52, 805–814.
Voukantsis, D., Niska, H., Karatzas, K., Riga, M., Damialis, A., & Vokou, D. (2010). Forecasting daily pollen concentrations using data-driven modelling methods in Thessaloniki, Greece. Atmospheric Environment, 44, 5101–5111. doi:10.1016/j.atmosenv.2010.09.006.
Voukantsis, D., Karatzas, D., Jaeger, S., & Berger, U. (2011). Personalized information services for quality of life: The case of airborne pollen induced symptoms. 12th International Conference, EANN 2011, and 7th IFIP WG 12.5 International Conference, AIAI 2011, Corfu, Greece, 15–18 September 2011. Proceedings, Part I (L. S. Iliadis, & C. Jayne (Eds.)) (pp. 509–515), ISBN 978-3-642-23956-4. New York: Springer.
Walker, D. A., Epstein, H. E., Jia, G. J., Balser, A., Copass, C., Edwards, E. J., Gould, W. A., Hollingsworth, J., Knudson, J., Maier, H. A., Moody, A., & Raynolds, M. K. (2003). Phytomass, LAI, and NDVI in northern Alaska: Relationship to summer warmth, soil pH, plant functional types, and extrapolation to the circumpolar Arctic. Journal of Geophysical Research, 108, 8169.
Ward, S. (2008). The earth observation handbook – Climate change special edition 2008 (esa sP-1315). ESA Communication Production Office, ESTEC, Postbus 299, 2200 AG Noordwijk, The Netherlands, 278 p.
White, M. A., Thornton, P. E., & Running, S. W. (1997). A continental phenology model for monitoring vegetation responses to interannual climatic variability. Global Biogeochemical Cycles, 11(2), 217–234.
Winkler, H., Ostrowski, R., & Wilhelm, M. (2001). Pollenbestimmungsbuch der Stiftung Deutscher Polleninformationsdienst. Takt Verlag: Paderborn.
Zhang, Z., Zhe, J., Chandra, S., & Hu, J. (2005). An electronic pollen detection method using Coulter counting principle. Atmospheric Environment, 39, 5446–5453.
Ziello, C., Böck, A., Jochner, S., Estrella, N., Buters, J., Weichenmeier, I, Behrendt, H., & Menzel, A. (2010). Bio-monitoring of the Zugspitze area: Linking phenological, meteorological and palynological data along an altitudinal gradient. Paper presented at Erste Wissenschaftliche Tagung Umweltforschungsstation Schneefernerhaus, Iffeldorf, Mai 2010.
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Scheifinger, H. et al. (2013). Monitoring, Modelling and Forecasting of the Pollen Season. In: Sofiev, M., Bergmann, KC. (eds) Allergenic Pollen. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4881-1_4
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