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Modeling daily flowering probabilities: Expected impact of climate change on Japanese cherry phenology

Overview of attention for article published in Global Change Biology, January 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

blogs
2 blogs
twitter
5 tweeters
facebook
1 Facebook page

Readers on

mendeley
59 Mendeley
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Title
Modeling daily flowering probabilities: Expected impact of climate change on Japanese cherry phenology
Published in
Global Change Biology, January 2013
DOI 10.1111/gcb.12364
Pubmed ID
Authors

Jenica M Allen, Maria A Terres, Toshio Katsuki, Kojiro Iwamoto, Hiromi Kobori, Hiroyoshi Higuchi, Richard B Primack, Adam M Wilson, Alan Gelfand, John A Silander, Allen JM, Terres MA, Katsuki T, Iwamoto K, Kobori H, Higuchi H, Primack RB, Wilson AM, Gelfand A, Silander JA, Allen, Jenica M., Terres, Maria A., Katsuki, Toshio, Iwamoto, Kojiro, Kobori, Hiromi, Higuchi, Hiroyoshi, Primack, Richard B., Wilson, Adam M., Gelfand, Alan, Silander, John A.

Abstract

Understanding the drivers of phenological events is vital for forecasting species' responses to climate change. We developed flexible Bayesian survival regression models to assess a 29-year, individual-level time series of flowering phenology from four taxa of Japanese cherry trees (Prunus spachiana, Prunus × yedoensis, Prunus jamasakura, and Prunus lannesiana), from the Tama Forest Cherry Preservation Garden in Hachioji, Japan. Our modeling framework used time-varying (chill and heat units) and time-invariant (slope, aspect, and elevation) factors. We found limited differences among taxa in sensitivity to chill, but earlier flowering taxa, such as P. spachiana, were more sensitive to heat than later flowering taxa, such as P. lannesiana. Using an ensemble of three downscaled regional climate models under the A1B emissions scenario, we projected shifts in flowering timing by 2100. Projections suggest that each taxa will flower about 30 days earlier on average by 2100 with 2-6 days greater uncertainty around the species mean flowering date. Dramatic shifts in the flowering times of cherry trees may have implications for economically important cultural festivals in Japan and East Asia. The survival models used here provide a mechanistic modeling approach and are broadly applicable to any time-to-event phenological data, such as plant leafing, bird arrival time, and insect emergence. The ability to explicitly quantify uncertainty, examine phenological responses on a fine time scale, and incorporate conditions leading up to an event may provide future insight into phenologically driven changes in carbon balance and ecological mismatches of plants and pollinators in natural populations and horticultural crops.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 3%
France 1 2%
Mexico 1 2%
United States 1 2%
Hungary 1 2%
Netherlands 1 2%
Unknown 52 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 32%
Researcher 19 32%
Professor > Associate Professor 6 10%
Other 4 7%
Student > Master 3 5%
Other 8 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 56%
Environmental Science 16 27%
Mathematics 2 3%
Earth and Planetary Sciences 2 3%
Engineering 2 3%
Other 4 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 25 April 2017.
All research outputs
#508,901
of 7,757,492 outputs
Outputs from Global Change Biology
#614
of 2,421 outputs
Outputs of similar age
#9,769
of 129,836 outputs
Outputs of similar age from Global Change Biology
#2
of 9 outputs
Altmetric has tracked 7,757,492 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,421 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. This one has gotten more attention than average, scoring higher than 74% 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 129,836 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.