Literature DB >> 28220255

Phenological patterns of flowering across biogeographical regions of Europe.

Barbara Templ1, Matthias Templ2, Peter Filzmoser3, Annamária Lehoczky4, Eugenija Bakšienè5, Stefan Fleck6, Hilppa Gregow7, Sabina Hodzic8, Gunta Kalvane9, Eero Kubin10, Vello Palm11, Danuta Romanovskaja5, Višnja Vucˇetic12, Ana Žust13, Bálint Czúcz14,15.   

Abstract

Long-term changes of plant phenological phases determined by complex interactions of environmental factors are in the focus of recent climate impact research. There is a lack of studies on the comparison of biogeographical regions in Europe in terms of plant responses to climate. We examined the flowering phenology of plant species to identify the spatio-temporal patterns in their responses to environmental variables over the period 1970-2010. Data were collected from 12 countries along a 3000-km-long, North-South transect from northern to eastern Central Europe.Biogeographical regions of Europe were covered from Finland to Macedonia. Robust statistical methods were used to determine the most influential factors driving the changes of the beginning of flowering dates. Significant species-specific advancements in plant flowering onsets within the Continental (3 to 8.3 days), Alpine (2 to 3.8 days) and by highest magnitude in the Boreal biogeographical regions (2.2 to 9.6 days per decades) were found, while less pronounced responses were detected in the Pannonian and Mediterranean regions. While most of the other studies only use mean temperature in the models, we show that also the distribution of minimum and maximum temperatures are reasonable to consider as explanatory variable. Not just local (e.g. temperature) but large scale (e.g. North Atlantic Oscillation) climate factors, as well as altitude and latitude play significant role in the timing of flowering across biogeographical regions of Europe. Our analysis gave evidences that species show a delay in the timing of flowering with an increase in latitude (between the geographical coordinates of 40.9 and 67.9), and an advance with changing climate. The woody species (black locust and small-leaved lime) showed stronger advancements in their timing of flowering than the herbaceous species (dandelion, lily of the valley). In later decades (1991-2010), more pronounced phenological change was detected than during the earlier years (1970-1990), which indicates the increased influence of human induced higher spring temperatures in the late twentieth century.

Entities:  

Keywords:  Beginning of flowering; Biogeographical regions; Climate change; Europe; Robust regression; Shifting trend

Mesh:

Year:  2017        PMID: 28220255     DOI: 10.1007/s00484-017-1312-6

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  17 in total

1.  Fingerprints of global warming on wild animals and plants.

Authors:  Terry L Root; Jeff T Price; Kimberly R Hall; Stephen H Schneider; Cynthia Rosenzweig; J Alan Pounds
Journal:  Nature       Date:  2003-01-02       Impact factor: 49.962

2.  Warming experiments underpredict plant phenological responses to climate change.

Authors:  E M Wolkovich; B I Cook; J M Allen; T M Crimmins; J L Betancourt; S E Travers; S Pau; J Regetz; T J Davies; N J B Kraft; T R Ault; K Bolmgren; S J Mazer; G J McCabe; B J McGill; C Parmesan; N Salamin; M D Schwartz; E E Cleland
Journal:  Nature       Date:  2012-05-02       Impact factor: 49.962

3.  Plant science. Phenology under global warming.

Authors:  Christian Körner; David Basler
Journal:  Science       Date:  2010-03-19       Impact factor: 47.728

4.  The unique and multifaceted importance of the timing of flowering.

Authors:  Steven J Franks
Journal:  Am J Bot       Date:  2015-08-06       Impact factor: 3.844

5.  21st century climate change in the European Alps--a review.

Authors:  Andreas Gobiet; Sven Kotlarski; Martin Beniston; Georg Heinrich; Jan Rajczak; Markus Stoffel
Journal:  Sci Total Environ       Date:  2013-08-15       Impact factor: 7.963

6.  Phenological models to predict the main flowering phases of olive (Olea europaea L.) along a latitudinal and longitudinal gradient across the Mediterranean region.

Authors:  Fátima Aguilera; Marco Fornaciari; Luis Ruiz-Valenzuela; Carmen Galán; Monji Msallem; Ali Ben Dhiab; Consuelo Díaz-de la Guardia; María Del Mar Trigo; Tommaso Bonofiglio; Fabio Orlandi
Journal:  Int J Biometeorol       Date:  2014-07-25       Impact factor: 3.787

7.  Effects of recent warm and cold spells on European plant phenology.

Authors:  Annette Menzel; Holm Seifert; Nicole Estrella
Journal:  Int J Biometeorol       Date:  2011-07-14       Impact factor: 3.787

8.  Phenological response to climate change in China: a meta-analysis.

Authors:  Quansheng Ge; Huanjiong Wang; This Rutishauser; Junhu Dai
Journal:  Glob Chang Biol       Date:  2014-06-24       Impact factor: 10.863

9.  Change of plant phenophases explained by survival modeling.

Authors:  Barbara Templ; Stefan Fleck; Matthias Templ
Journal:  Int J Biometeorol       Date:  2016-11-16       Impact factor: 3.787

10.  Flowering phenological changes in relation to climate change in Hungary.

Authors:  Barbara Szabó; Enikő Vincze; Bálint Czúcz
Journal:  Int J Biometeorol       Date:  2016-01-14       Impact factor: 3.787

View more
  4 in total

1.  A grid-based map for the Biogeographical Regions of Europe.

Authors:  Marco Cervellini; Piero Zannini; Michele Di Musciano; Simone Fattorini; Borja Jiménez-Alfaro; Duccio Rocchini; Richard Field; Ole R Vetaas; Severin D H Irl; Carl Beierkuhnlein; Samuel Hoffmann; Jan-Christopher Fischer; Laura Casella; Pierangela Angelini; Piero Genovesi; Juri Nascimbene; Alessandro Chiarucci
Journal:  Biodivers Data J       Date:  2020-06-19

2.  Phenological response to temperature variability and orography in Central Italy.

Authors:  P B Cerlini; M Saraceni; F Orlandi; L Silvestri; M Fornaciari
Journal:  Int J Biometeorol       Date:  2021-11-30       Impact factor: 3.738

3.  Behaviour of Abutilon theophrasti in Different Climatic Niches: A New Zealand Case Study.

Authors:  Hossein Ghanizadeh; Trevor K James
Journal:  Front Plant Sci       Date:  2022-04-25       Impact factor: 6.627

4.  Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset.

Authors:  Bartosz Czernecki; Jakub Nowosad; Katarzyna Jabłońska
Journal:  Int J Biometeorol       Date:  2018-04-11       Impact factor: 3.787

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.