Literature DB >> 18437430

European larch phenology in the Alps: can we grasp the role of ecological factors by combining field observations and inverse modelling?

M Migliavacca1, E Cremonese, R Colombo, L Busetto, M Galvagno, L Ganis, M Meroni, E Pari, M Rossini, C Siniscalco, U Morra di Cella.   

Abstract

Vegetation phenology is strongly influenced by climatic factors. Climate changes may cause phenological variations, especially in the Alps which are considered to be extremely vulnerable to global warming. The main goal of our study is to analyze European larch (Larix decidua Mill.) phenology in alpine environments and the role of the ecological factors involved, using an integrated approach based on accurate field observations and modelling techniques. We present 2 years of field-collected larch phenological data, obtained following a specifically designed observation protocol. We observed that both spring and autumn larch phenology is strongly influenced by altitude. We propose an approach for the optimization of a spring warming model (SW) and the growing season index model (GSI) consisting of a model inversion technique, based on simulated look-up tables (LUTs), that provides robust parameter estimates. The optimized models showed excellent agreement between modelled and observed data: the SW model predicts the beginning of the growing season (B(GS)) with a mean RMSE of 4 days, while GSI gives a prediction of the growing season length (L(GS)) with a RMSE of 5 days. Moreover, we showed that the original GSI parameters led to consistent errors, while the optimized ones significantly increased model accuracy. Finally, we used GSI to investigate interactions of ecological factors during springtime development and autumn senescence. We found that temperature is the most effective factor during spring recovery while photoperiod plays an important role during autumn senescence: photoperiod shows a contrasting effect with altitude decreasing its influence with increasing altitude.

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Year:  2008        PMID: 18437430     DOI: 10.1007/s00484-008-0152-9

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


  19 in total

1.  Spring phenology trends in Alberta, Canada: links to ocean temperature.

Authors:  E G Beaubien; H J Freeland
Journal:  Int J Biometeorol       Date:  2000-08       Impact factor: 3.787

2.  Evaluation of methods for the combination of phenological time series and outlier detection.

Authors:  Jörg Schaber; Franz-W Badeck
Journal:  Tree Physiol       Date:  2002-10       Impact factor: 4.196

3.  The utilization of old phenological time series of budburst to compare models describing annual cycles of plants.

Authors:  P Hari; R Häkkinen
Journal:  Tree Physiol       Date:  1991-04       Impact factor: 4.196

4.  Models of the spring phenology of boreal and temperate trees: Is there something missing?

Authors:  Tapio Linkosalo; Risto Häkkinen; Heikki Hänninen
Journal:  Tree Physiol       Date:  2006-09       Impact factor: 4.196

5.  Daylength and thermal time responses of budburst during dormancy release in some northern deciduous trees.

Authors:  O M Heide
Journal:  Physiol Plant       Date:  1993-08       Impact factor: 4.500

6.  Photosynthetic decline and pigment loss during autumn foliar senescence in western larch (Larix occidentalis).

Authors:  S I Rosenthal; E L Camm
Journal:  Tree Physiol       Date:  1997-12       Impact factor: 4.196

7.  Quantification of photoperiodic effects on growth of Phleum pratense.

Authors:  Zuoli Wu; A O Skjelvåg; O H Baadshaug
Journal:  Ann Bot       Date:  2004-08-11       Impact factor: 4.357

8.  High autumn temperature delays spring bud burst in boreal trees, counterbalancing the effect of climatic warming.

Authors:  O M Heide
Journal:  Tree Physiol       Date:  2003-09       Impact factor: 4.196

9.  Effects of photoperiod and temperature on the timing of bud burst in Norway spruce (Picea abies).

Authors:  Jouni Partanen; Veikko Koski; Heikki Hänninen
Journal:  Tree Physiol       Date:  1998-12       Impact factor: 4.196

10.  Effects of dormancy and environmental factors on timing of bud burst in Betula pendula.

Authors:  Risto Häkkinen; Tapio Linkosalo; Pertti Hari
Journal:  Tree Physiol       Date:  1998-10       Impact factor: 4.196

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  8 in total

1.  Environmental controls on the phenology of moths: predicting plasticity and constraint under climate change.

Authors:  Anu Valtonen; Matthew P Ayres; Heikki Roininen; Juha Pöyry; Reima Leinonen
Journal:  Oecologia       Date:  2010-09-30       Impact factor: 3.225

2.  The response of Corylus avellana L. phenology to rising temperature in north-eastern Slovenia.

Authors:  Zalika Crepinšek; Franci Stampar; Lučka Kajfež-Bogataj; Anita Solar
Journal:  Int J Biometeorol       Date:  2011-07-23       Impact factor: 3.787

3.  The rise of phenology with climate change: an evaluation of IJB publications.

Authors:  Alison Donnelly; Rong Yu
Journal:  Int J Biometeorol       Date:  2017-05-19       Impact factor: 3.787

4.  Seasonal course of photosynthetic efficiency in Larix decidua Mill. in response to temperature and change in pigment composition during senescence.

Authors:  M Galvagno; M Rossini; M Migliavacca; E Cremonese; R Colombo; U Morra di Cella
Journal:  Int J Biometeorol       Date:  2012-12-23       Impact factor: 3.787

5.  Phenological response of grassland species to manipulative snowmelt and drought along an altitudinal gradient.

Authors:  Christine Cornelius; Annette Leingärtner; Bernhard Hoiss; Jochen Krauss; Ingolf Steffan-Dewenter; Annette Menzel
Journal:  J Exp Bot       Date:  2012-11-19       Impact factor: 6.992

6.  Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

Authors:  Mirco Migliavacca; Michele Meroni; Lorenzo Busetto; Roberto Colombo; Terenzio Zenone; Giorgio Matteucci; Giovanni Manca; Guenther Seufert
Journal:  Sensors (Basel)       Date:  2009-02-13       Impact factor: 3.576

7.  A Novel Large-Scale Temperature Dominated Model for Predicting the End of the Growing Season.

Authors:  Yang Fu; Zeyu Zheng; Haibo Shi; Rui Xiao
Journal:  PLoS One       Date:  2016-11-28       Impact factor: 3.240

8.  Traits and climate are associated with first flowering day in herbaceous species along elevational gradients.

Authors:  Solveig Franziska Bucher; Patrizia König; Annette Menzel; Mirco Migliavacca; Jörg Ewald; Christine Römermann
Journal:  Ecol Evol       Date:  2017-12-20       Impact factor: 2.912

  8 in total

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