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Dispersal and spatial heterogeneity: single species

Overview of attention for article published in Journal of Mathematical Biology, April 2015
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Title
Dispersal and spatial heterogeneity: single species
Published in
Journal of Mathematical Biology, April 2015
DOI 10.1007/s00285-015-0879-y
Pubmed ID
Authors

Donald L. DeAngelis, Wei-Ming Ni, Bo Zhang

Abstract

A recent result for a reaction-diffusion equation is that a population diffusing at any rate in an environment in which resources vary spatially will reach a higher total equilibrium biomass than the population in an environment in which the same total resources are distributed homogeneously. This has so far been proven by Lou for the case in which the reaction term has only one parameter, [Formula: see text], varying with spatial location [Formula: see text], which serves as both the intrinsic growth rate coefficient and carrying capacity of the population. However, this striking result seems rather limited when applies to real populations. In order to make the model more relevant for ecologists, we consider a logistic reaction term, with two parameters, [Formula: see text] for intrinsic growth rate, and [Formula: see text] for carrying capacity. When [Formula: see text] and [Formula: see text] are proportional, the logistic equation takes a particularly simple form, and the earlier result still holds. In this paper we have established the result for the more general case of a positive correlation between [Formula: see text] and [Formula: see text] when dispersal rate is small. We review natural and laboratory systems to which these results are relevant and discuss the implications of the results to population theory and conservation ecology.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 33%
Student > Ph. D. Student 5 28%
Other 2 11%
Student > Master 1 6%
Student > Doctoral Student 1 6%
Other 1 6%
Unknown 2 11%
Readers by discipline Count As %
Environmental Science 6 33%
Agricultural and Biological Sciences 5 28%
Mathematics 3 17%
Medicine and Dentistry 1 6%
Unknown 3 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 24 August 2016.
All research outputs
#7,639,787
of 12,226,511 outputs
Outputs from Journal of Mathematical Biology
#165
of 364 outputs
Outputs of similar age
#145,927
of 263,023 outputs
Outputs of similar age from Journal of Mathematical Biology
#2
of 6 outputs
Altmetric has tracked 12,226,511 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 38th percentile – i.e., 38% 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 263,023 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.