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Thermokarst rates intensify due to climate change and forest fragmentation in an Alaskan boreal forest lowland

Overview of attention for article published in Global Change Biology, January 2016
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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 (84th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

blogs
1 blog
twitter
5 tweeters

Citations

dimensions_citation
48 Dimensions

Readers on

mendeley
113 Mendeley
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Title
Thermokarst rates intensify due to climate change and forest fragmentation in an Alaskan boreal forest lowland
Published in
Global Change Biology, January 2016
DOI 10.1111/gcb.13124
Pubmed ID
Authors

Mark J. Lara, Hélène Genet, Anthony D. McGuire, Eugénie S. Euskirchen, Yujin Zhang, Dana R. N. Brown, Mark T. Jorgenson, Vladimir Romanovsky, Amy Breen, William R. Bolton

Abstract

Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse scar-bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5°C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998 and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30x30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950-2009 landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of lowland ice-rich permafrost ecosystems to climate changes depends on forest type. This article is protected by copyright. All rights reserved.

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 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 <1%
United States 1 <1%
Canada 1 <1%
Unknown 110 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 21%
Student > Ph. D. Student 23 20%
Student > Master 17 15%
Student > Bachelor 11 10%
Professor 9 8%
Other 11 10%
Unknown 18 16%
Readers by discipline Count As %
Environmental Science 47 42%
Agricultural and Biological Sciences 21 19%
Earth and Planetary Sciences 11 10%
Biochemistry, Genetics and Molecular Biology 2 2%
Engineering 2 2%
Other 5 4%
Unknown 25 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 28 March 2016.
All research outputs
#2,255,895
of 17,911,762 outputs
Outputs from Global Change Biology
#2,531
of 4,777 outputs
Outputs of similar age
#38,780
of 261,046 outputs
Outputs of similar age from Global Change Biology
#30
of 81 outputs
Altmetric has tracked 17,911,762 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,777 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 28.3. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
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 261,046 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 84% of its contemporaries.
We're also able to compare this research output to 81 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 62% of its contemporaries.