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Snowmelt timing, phenology, and growing season length in conifer forests of Crater Lake National Park, USA

Overview of attention for article published in International Journal of Biometeorology, September 2017
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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 (86th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

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1 blog
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5 X users
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1 Facebook page

Citations

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15 Dimensions

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mendeley
29 Mendeley
Title
Snowmelt timing, phenology, and growing season length in conifer forests of Crater Lake National Park, USA
Published in
International Journal of Biometeorology, September 2017
DOI 10.1007/s00484-017-1449-3
Pubmed ID
Authors

Donal S. O’Leary, Jherime L. Kellermann, Chris Wayne

Abstract

Anthropogenic climate change is having significant impacts on montane and high-elevation areas globally. Warmer winter temperatures are driving reduced snowpack in the western USA with broad potential impacts on ecosystem dynamics of particular concern for protected areas. Vegetation phenology is a sensitive indicator of ecological response to climate change and is associated with snowmelt timing. Human monitoring of climate impacts can be resource prohibitive for land management agencies, whereas remotely sensed phenology observations are freely available at a range of spatiotemporal scales. Little work has been done in regions dominated by evergreen conifer cover, which represents many mountain regions at temperate latitudes. We used moderate resolution imaging spectroradiometer (MODIS) data to assess the influence of snowmelt timing and elevation on five phenology metrics (green up, maximum greenness, senescence, dormancy, and growing season length) within Crater Lake National Park, Oregon, USA from 2001 to 2012. Earlier annual mean snowmelt timing was significantly correlated with earlier onset of green up at the landscape scale. Snowmelt timing and elevation have significant explanatory power for phenology, though with high variability. Elevation has a moderate control on early season indicators such as snowmelt timing and green up and less on late-season variables such as senescence and growing season length. PCA results show that early season indicators and late season indicators vary independently. These results have important implications for ecosystem dynamics, management, and conservation, particularly of species such as whitebark pine (Pinus albicaulis) in alpine and subalpine areas.

X Demographics

X Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 31%
Student > Ph. D. Student 7 24%
Student > Master 4 14%
Student > Doctoral Student 1 3%
Other 1 3%
Other 3 10%
Unknown 4 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 38%
Environmental Science 8 28%
Earth and Planetary Sciences 2 7%
Arts and Humanities 1 3%
Social Sciences 1 3%
Other 0 0%
Unknown 6 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 07 October 2017.
All research outputs
#2,195,623
of 23,003,906 outputs
Outputs from International Journal of Biometeorology
#190
of 1,299 outputs
Outputs of similar age
#44,887
of 321,749 outputs
Outputs of similar age from International Journal of Biometeorology
#9
of 34 outputs
Altmetric has tracked 23,003,906 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,299 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one has done well, scoring higher than 85% 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 321,749 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.