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Can we detect a nonlinear response to temperature in European plant phenology?

Overview of attention for article published in International Journal of Biometeorology, March 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 blog

Citations

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21 Mendeley
Title
Can we detect a nonlinear response to temperature in European plant phenology?
Published in
International Journal of Biometeorology, March 2016
DOI 10.1007/s00484-016-1146-7
Pubmed ID
Authors

Susanne Jochner, Tim H. Sparks, Julia Laube, Annette Menzel

Abstract

Over a large temperature range, the statistical association between spring phenology and temperature is often regarded and treated as a linear function. There are suggestions that a sigmoidal relationship with definite upper and lower limits to leaf unfolding and flowering onset dates might be more realistic. We utilised European plant phenological records provided by the European phenology database PEP725 and gridded monthly mean temperature data for 1951-2012 calculated from the ENSEMBLES data set E-OBS (version 7.0). We analysed 568,456 observations of ten spring flowering or leafing phenophases derived from 3657 stations in 22 European countries in order to detect possible nonlinear responses to temperature. Linear response rates averaged for all stations ranged between -7.7 (flowering of hazel) and -2.7 days °C(-1) (leaf unfolding of beech and oak). A lower sensitivity at the cooler end of the temperature range was detected for most phenophases. However, a similar lower sensitivity at the warmer end was not that evident. For only ∼14 % of the station time series (where a comparison between linear and nonlinear model was possible), nonlinear models described the relationship significantly better than linear models. Although in most cases simple linear models might be still sufficient to predict future changes, this linear relationship between phenology and temperature might not be appropriate when incorporating phenological data of very cold (and possibly very warm) environments. For these cases, extrapolations on the basis of linear models would introduce uncertainty in expected ecosystem changes.

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 5%
France 1 5%
Unknown 19 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 33%
Student > Ph. D. Student 7 33%
Other 3 14%
Unspecified 2 10%
Professor > Associate Professor 1 5%
Other 1 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 43%
Environmental Science 5 24%
Unspecified 4 19%
Earth and Planetary Sciences 3 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 March 2016.
All research outputs
#2,809,596
of 12,223,436 outputs
Outputs from International Journal of Biometeorology
#298
of 752 outputs
Outputs of similar age
#70,422
of 275,752 outputs
Outputs of similar age from International Journal of Biometeorology
#16
of 33 outputs
Altmetric has tracked 12,223,436 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 752 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has gotten more attention than average, scoring higher than 58% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 275,752 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.