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A general modeling framework for describing spatially structured population dynamics

Overview of attention for article published in Ecology and Evolution, November 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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18 tweeters


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A general modeling framework for describing spatially structured population dynamics
Published in
Ecology and Evolution, November 2017
DOI 10.1002/ece3.3685
Pubmed ID

Sample, Christine, Fryxell, John M., Bieri, Joanna A., Federico, Paula, Earl, Julia E., Wiederholt, Ruscena, Mattsson, Brady J., Flockhart, D. T. Tyler, Nicol, Sam, Diffendorfer, Jay E., Thogmartin, Wayne E., Erickson, Richard A., Norris, D. Ryan, Christine Sample, John M. Fryxell, Joanna A. Bieri, Paula Federico, Julia E. Earl, Ruscena Wiederholt, Brady J. Mattsson, D. T. Tyler Flockhart, Sam Nicol, Jay E. Diffendorfer, Wayne E. Thogmartin, Richard A. Erickson, D. Ryan Norris


Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles.

Twitter Demographics

The data shown below were collected from the profiles of 18 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 24%
Student > Ph. D. Student 10 20%
Student > Master 9 18%
Unspecified 7 14%
Student > Bachelor 4 8%
Other 8 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 52%
Environmental Science 11 22%
Unspecified 10 20%
Biochemistry, Genetics and Molecular Biology 1 2%
Computer Science 1 2%
Other 1 2%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 December 2017.
All research outputs
of 12,319,220 outputs
Outputs from Ecology and Evolution
of 3,325 outputs
Outputs of similar age
of 346,972 outputs
Outputs of similar age from Ecology and Evolution
of 264 outputs
Altmetric has tracked 12,319,220 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 3,325 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has done well, scoring higher than 81% 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 346,972 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 85% of its contemporaries.
We're also able to compare this research output to 264 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.