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Applications of step-selection functions in ecology and conservation

Overview of attention for article published in Movement Ecology, February 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)

Mentioned by

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5 tweeters

Citations

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194 Dimensions

Readers on

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716 Mendeley
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Title
Applications of step-selection functions in ecology and conservation
Published in
Movement Ecology, February 2014
DOI 10.1186/2051-3933-2-4
Pubmed ID
Authors

Henrik Thurfjell, Simone Ciuti, Mark S Boyce

Abstract

Recent progress in positioning technology facilitates the collection of massive amounts of sequential spatial data on animals. This has led to new opportunities and challenges when investigating animal movement behaviour and habitat selection. Tools like Step Selection Functions (SSFs) are relatively new powerful models for studying resource selection by animals moving through the landscape. SSFs compare environmental attributes of observed steps (the linear segment between two consecutive observations of position) with alternative random steps taken from the same starting point. SSFs have been used to study habitat selection, human-wildlife interactions, movement corridors, and dispersal behaviours in animals. SSFs also have the potential to depict resource selection at multiple spatial and temporal scales. There are several aspects of SSFs where consensus has not yet been reached such as how to analyse the data, when to consider habitat covariates along linear paths between observations rather than at their endpoints, how many random steps should be considered to measure availability, and how to account for individual variation. In this review we aim to address all these issues, as well as to highlight weak features of this modelling approach that should be developed by further research. Finally, we suggest that SSFs could be integrated with state-space models to classify behavioural states when estimating SSFs.

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

Geographical breakdown

Country Count As %
Brazil 8 1%
United States 6 <1%
Germany 4 <1%
France 4 <1%
Canada 3 <1%
Portugal 2 <1%
United Kingdom 2 <1%
Australia 1 <1%
India 1 <1%
Other 5 <1%
Unknown 680 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 181 25%
Student > Ph. D. Student 167 23%
Researcher 129 18%
Student > Bachelor 59 8%
Student > Doctoral Student 30 4%
Other 81 11%
Unknown 69 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 376 53%
Environmental Science 174 24%
Earth and Planetary Sciences 13 2%
Biochemistry, Genetics and Molecular Biology 9 1%
Engineering 7 <1%
Other 34 5%
Unknown 103 14%

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 19 March 2019.
All research outputs
#8,247,048
of 15,282,235 outputs
Outputs from Movement Ecology
#138
of 195 outputs
Outputs of similar age
#104,630
of 254,359 outputs
Outputs of similar age from Movement Ecology
#1
of 2 outputs
Altmetric has tracked 15,282,235 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 195 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.8. This one is in the 29th percentile – i.e., 29% 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 254,359 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 58% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them