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Mapping Large-Area Landscape Suitability for Honey Bees to Assess the Influence of Land-Use Change on Sustainability of National Pollination Services

Overview of attention for article published in PLOS ONE, June 2014
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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 (89th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
20 tweeters

Readers on

mendeley
163 Mendeley
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Title
Mapping Large-Area Landscape Suitability for Honey Bees to Assess the Influence of Land-Use Change on Sustainability of National Pollination Services
Published in
PLOS ONE, June 2014
DOI 10.1371/journal.pone.0099268
Pubmed ID
Authors

Alisa L. Gallant, Ned H. Euliss, Zac Browning

Abstract

Pollination is a critical ecosystem service affected by various drivers of land-use change, such as policies and programs aimed at land resources, market values for crop commodities, local land-management decisions, and shifts in climate. The United States is the world's most active market for pollination services by honey bees, and the Northern Great Plains provide the majority of bee colonies used to meet the Nation's annual pollination needs. Legislation requiring increased production of biofuel crops, increasing commodity prices for crops of little nutritional value for bees in the Northern Great Plains, and reductions in government programs aimed at promoting land conservation are converging to alter the regional landscape in ways that challenge beekeepers to provide adequate numbers of hives for national pollination services. We developed a spatially explicit model that identifies sites with the potential to support large apiaries based on local-scale land-cover requirements for honey bees. We produced maps of potential apiary locations for North Dakota, a leading producer of honey, based on land-cover maps representing (1) an annual time series compiled from existing operational products and (2) a realistic scenario of land change. We found that existing land-cover products lack sufficient local accuracy to monitor actual changes in landscape suitability for honey bees, but our model proved informative for evaluating effects on suitability under scenarios of land change. The scenario we implemented was aligned with current drivers of land-use change in the Northern Great Plains and highlighted the importance of conservation lands in landscapes intensively and extensively managed for crops.

Twitter Demographics

The data shown below were collected from the profiles of 20 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 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Mexico 1 <1%
Malta 1 <1%
New Zealand 1 <1%
Spain 1 <1%
Chile 1 <1%
Serbia 1 <1%
Unknown 155 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 18%
Student > Master 27 17%
Researcher 26 16%
Student > Bachelor 21 13%
Student > Doctoral Student 9 6%
Other 28 17%
Unknown 23 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 72 44%
Environmental Science 34 21%
Earth and Planetary Sciences 10 6%
Social Sciences 3 2%
Engineering 3 2%
Other 12 7%
Unknown 29 18%

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 21 June 2019.
All research outputs
#1,872,120
of 20,032,353 outputs
Outputs from PLOS ONE
#24,658
of 175,118 outputs
Outputs of similar age
#21,114
of 203,161 outputs
Outputs of similar age from PLOS ONE
#491
of 3,032 outputs
Altmetric has tracked 20,032,353 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 175,118 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.1. 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 203,161 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 89% of its contemporaries.
We're also able to compare this research output to 3,032 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.