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Mendeley readers
Attention Score in Context
| Title |
A lake-centric geospatial database to guide research and inform management decisions in an Arctic watershed in northern Alaska experiencing climate and land-use changes
|
|---|---|
| Published in |
Ambio, March 2017
|
| DOI | 10.1007/s13280-017-0915-9 |
| Pubmed ID | |
| Authors |
Benjamin M. Jones, Christopher D. Arp, Matthew S. Whitman, Debora Nigro, Ingmar Nitze, John Beaver, Anne Gädeke, Callie Zuck, Anna Liljedahl, Ronald Daanen, Eric Torvinen, Stacey Fritz, Guido Grosse |
| Abstract |
Lakes are dominant and diverse landscape features in the Arctic, but conventional land cover classification schemes typically map them as a single uniform class. Here, we present a detailed lake-centric geospatial database for an Arctic watershed in northern Alaska. We developed a GIS dataset consisting of 4362 lakes that provides information on lake morphometry, hydrologic connectivity, surface area dynamics, surrounding terrestrial ecotypes, and other important conditions describing Arctic lakes. Analyzing the geospatial database relative to fish and bird survey data shows relations to lake depth and hydrologic connectivity, which are being used to guide research and aid in the management of aquatic resources in the National Petroleum Reserve in Alaska. Further development of similar geospatial databases is needed to better understand and plan for the impacts of ongoing climate and land-use changes occurring across lake-rich landscapes in the Arctic. |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 63 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 19% |
| Researcher | 10 | 16% |
| Student > Master | 8 | 13% |
| Student > Bachelor | 5 | 8% |
| Student > Doctoral Student | 4 | 6% |
| Other | 6 | 10% |
| Unknown | 18 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 15 | 24% |
| Earth and Planetary Sciences | 6 | 10% |
| Agricultural and Biological Sciences | 6 | 10% |
| Engineering | 5 | 8% |
| Computer Science | 3 | 5% |
| Other | 7 | 11% |
| Unknown | 21 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 June 2020.
All research outputs
#7,801,448
of 23,680,154 outputs
Outputs from Ambio
#1,049
of 1,678 outputs
Outputs of similar age
#122,028
of 310,350 outputs
Outputs of similar age from Ambio
#22
of 28 outputs
Altmetric has tracked 23,680,154 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,678 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 20th percentile – i.e., 20% 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 310,350 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 52% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.