Reconstruction of late spring phenophases in Poland and their response to climate change, 1951–2014
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Ahas R. Long-term phyto-, ornitho- and ichthyophenological time-series analyses in Estonia. Int J Biometeorol. 1999;42:119–123. http://dx.doi.org/10.1007/s004840050094
Bradley NL, Leopold AC, Ross J, Huffaker W. Phenological changes reflect climate change in Wisconsin. Proc Natl Acad Sci USA. 1999;96(17):9701–9704. http://dx.doi.org/10.1073/pnas.96.17.9701
Ahas R, Aasa A, Menzel A, Fedotova VG, Scheifinger H, Changes in European spring phenology. Int J Climatol. 2002;22:1727–1738. http://dx.doi.org/10.1002/joc.818
Root TL, Price JT, Hall KR, Schneider KR, Rosenzweig C, Pounds JA. Fingerprints of global warming on wild animals and plants. Nature. 2003;421:57–60. http://dx.doi.org/10.1038/nature01333
Menzel A, Sparks TH, Estrella N, Koch E, Aasa A, Aha R, et al. European phenological response to climate change matches the warming, Glob Chang Biol. 2006;12:1969–1976. http://dx.doi.org/10.1111/j.1365-2486.2006.01193.x
Parmesan C. Ecological and evolutionary responses to recent climate change. Annu Rev Ecol Evol S. 2006;37:637–669. http://dx.doi.org/10.1146/annurev.ecolsys.37.091305.110100
Schleip C, Menzel A, Dose V. Bayesian methods in phenology. In: Hudson IL, Keatley MR, editors. Phenological research. Dordrecht: Springer; 2010. p. 229–254. http://dx.doi.org/10.1007/978-90-481-3335-2_11
Aono Y, Kazui K. Phenological data series of cherry tree flowering in Kyoto, Japan, and its application to reconstruction of springtime temperatures since the 9th century. Int J Climatol. 2008;28:905–914. http://dx.doi.org/10.1002/joc.1594
Schleip C, This R, Luterbacher J, Menzel A. Time series modeling and Central European temperature impact assessment of phenological records over the last 250 years. J Geophys Res. 2008;113:G04026. http://dx.doi.org/10.1029/2007JG000646
Koch E, Maurer C, Hammerl C, Hammerl T, Pokorny E. BACCHUS grape harvest days and temperature reconstruction for Vienna from the 16th to the 18th century. In: Anderssen RS, Braddock RD, Newham LTH, editors. Proceedings of the 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation; 2009 Jul 13–17; Cairns, Australia. Christchurch: Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation; 2009. p. 2632–2638.
Bradley RS. Paleoclimatology: reconstructing climates of the quaternary. 3rd ed. Amsterdam: Elsevier; 2014.
Zheng J, Hua Z, Liu Y, Hao Z. Temperature changes derived from phenological and natural evidences in South Central China from 1850 to 2008. Climate of the Past. 2015;11:4077–4095. http://dx.doi.org/10.5194/cp-11-1553-2015
Cybulski H. Średnie wypadki spostrzeżŜeń fitofenologicznych, poczynione w Ogrodzie Botanicznym w Warszawie od roku 1865 do 1885. Pamiętnik Fizjograficzny. 1886;6:65–83.
Tomaszewska T, Przedpełska W. Dzieje agrometeorologii w Państwowej Służbie Meteorologicznej [Manuscript]. Warszawa: Instytut Meteorologii i Gospodarki Wodnej; 1989.
Obrębska-Starklowa B. O badaniach fitofenologicznych w Galicji w XIX wieku (na tle rozwoju fenologii w Europie). Przeglad Geofizyczny. 1993;3–4:289–296.
Falińska K. Seasonal dynamics of forest undergrowth in Bialowieża National Park. Phytocenosis. 1973;1:3–115.
Jabłońska K, Rapiejko P. Using the results of a nationwide phenological network to examine the impact of changes in phenology of plant species on the concentration of plant pollen in the air. Acta Agrobot. 2010;63(2):69–74. http://dx.doi.org/10.5586/aa.2010.034
Schaber J, Badeck FW. Evaluation of methods for the combination of phenological time series and outlier detection. Tree Physiol. 2002;22:973–982. http://dx.doi.org/10.1093/treephys/22.14.973
Fitter A, Fitter R. Rapid changes in flowering time in British plants. Science. 2002;296:1689–1691. http://dx.doi.org/10.1126/science.1071617
Hudson IL, Keatley MR. Phenological research. Dordrecht: Springer; 2010. http://dx.doi.org/10.1007/978-90-481-3335-2
Jabłońska K, Kwiatkowska-Falińska A, Czernecki B, Walawender J. Changes in spring and summer phenology in Poland – responses of selected plant species to air temperature variations. Pol J Ecol. 2015;63:311–319. http://dx.doi.org/10.3161/15052249PJE2015.63.3.002
Meier U. Growth stages of mono- and dicotyledonous plants: BBCH monograph. Berlin: Blackwell Wissenschafts-Verlag; 1997.
Fitter AH, Fitter RS, Harris IT, Williamson MH. Relationship between first flowering date and temperature in the flora of a locality in central England. Funct Ecol. 1995;9:55–60. http://dx.doi.org/10.2307/2390090
Sparks TH, Carey PD. The responses of species to climate over two centuries: an analysis of the Marsham phenological record. J Ecol. 1995;83:321–329. http://dx.doi.org/10.2307/2261570
Rutishauser T, Luterbacher J, Jeanneret F, Pfister C, Wanner H. A phenology-based reconstruction of interannual changes in past spring seasons. J Geophys Res. 2007;112:G04016. http://dx.doi.org/10.1029/2006JG000382
Szabo B, Vincze E, Czúcz B. Flowering phenological changes in relation to climate change in Hungary. Int J Biometeorol. 2016. http://dx.doi.org/10.1007/s00484-015-1128-1
Haylock MR, Hofstra N, Klein Tank AMG, Klok EJ, Jones PD, New M. A European daily high-resolution gridded dataset of surface temperature and precipitation. J Geophys Res Atmos. 2008;113:D2011. http://dx.doi.org/10.1029/2008JD010201
Nowosad J. Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula. Int J Biometeorol. 2016;60(6):843–855. http://dx.doi.org/10.1007/s00484-015-1077-8
Ustrnul Z, Czekierda D, Application of GIS for the development of climatological air temperature maps: an example from Poland. Meteorological Applications. 2005;12:43–50. http://dx.doi.org/10.1017/S1350482705001507
Czernecki B, Miętus M. The thermal seasons variability in Poland, 1951–2010. Theor Appl Climatol. 2015. http://dx.doi.org/10.1007/s00704-015-1647-z
Szymanowski M, Kryza M. The role of auxiliary variables in deterministic and deterministic-stochastic spatial models of air temperature in Poland. Pure and Applied Geophysics. 2015. http://dx.doi.org/10.1007/s00024-015-1199-2
Kuhn M. Building predictive models in R using the caret package. J Stat Softw. 2008;28(5):1–26. http://dx.doi.org/10.18637/jss.v028.i05
Kuhn M, Johnson K. Applied predictive modeling. New York, NY: Springer; 2013. http://dx.doi.org/10.1007/978-1-4614-6849-3
Yeo IK, Johnson R. A new family of power transformations to improve normality or symmetry. Biometrika. 2000;87:954–959. http://dx.doi.org/10.1093/biomet/87.4.954
Kuhn M. caret: classification and regression training [Internet]. 2016 [cited 2016 Jun 3]. Available from: http://cran.r-project.org/package=caret
Sakamoto, Y, Ishiguro M, Kitagawa G. Akaike information criterion statistics. Tokyo: KTK Scientific Publishers; 1986.
R Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2013.
Pebesma EJ. Multivariable geostatistics in S: the gstat package. Comput Geosci. 2004;30:683–691. http://dx.doi.org/10.1016/j.cageo.2004.03.012
Taylor KE. Summarizing multiple aspects of model performance in a single diagram. J Geophys Res Atmos. 2001;106(D7):7183–7192. http://dx.doi.org/10.1029/2000JD900719
Wilks DS. Statistical methods in the atmospheric sciences. 3rd ed. Oxford: Academic Press; 2011. (International Geophysics Series; vol 100).
Mann HB. Nonparametric tests against trend. Econometrica. 1945;13:254–259. http://dx.doi.org/10.2307/1907187
Kendall MG. Rank correlation methods. 4th ed. London: Griffin; 1975.
Menzel A. Trends in phenological phases in Europe between 1951 and 1996. Int J Biometeorol. 2000;44:76–81. http://dx.doi.org/10.1007/s004840000054
Sparks T, Menzel A. Observed changes in seasons: an overview. Int J Climatol. 2002;22(14):1715–1725. http://dx.doi.org/10.1002/joc.821
Gevrey M, Dimopoulos I, Lek S. Review and comparison of methods to study the contribution of variables in artificial neural network models. Ecol Modell. 2003;160(3):249–264. http://dx.doi.org/10.1016/S0304-3800(02)00257-0
Rötzer T, Wittenzeller M, Häckel H, Nekovar J. Phenology in Central Europe – differences and trends of spring-phenophases in urban and rural areas. Int J Biometeorol. 2000;44:60–67. http://dx.doi.org/10.1007/s004840000062
Thompson R, Clark RM. Spatio-temporal modelling and assessment of within-species phenological variability using thermal time methods. Int J Biometeorol. 2006;50:312–322. http://dx.doi.org/10.1007/s00484-005-0017-4
Siljamo P, Sofiev M, Ranta H, Linkosalo T, Kubin E, Ahas R, et al. Representativeness of pointwise phenological Betula data collected in different parts of Europe. Glob Ecol Biogeogr. 2008;17(4):489–502. http://dx.doi.org/10.1111/j.1466-8238.2008.00383.x
Intergovernmental Panel on Climate Change, Working Group II. Climate change 2007: impacts, adaptation and vulnerability. Geneva: IPCC Secretariat; 2008.
Scheifinger H, Menzel A, Koch E, Peter C, Ahas R. Atmospheric mechanisms governing the spatial and temporal variability of phenological observations in central Europe. Int J Climatol. 2002;22:1739–1755. http://dx.doi.org/10.1002/joc.817
Sparks T, Tryjanowski P. The detection of climate impacts: some methodological considerations. Int J Climatol. 2005;25(2):271–277. http://dx.doi.org/10.1002/joc.1136
Chmielewski FM, Rötzer T. Annual and spatial variability of the beginning of growing season in Europe in relation to air temperature changes. Climate Research. 2002;19:257–264. http://dx.doi.org/10.3354/cr019257
DOI: https://doi.org/10.5586/aa.1671
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