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Persistence in a Two-Dimensional Moving-Habitat Model

Overview of attention for article published in Bulletin of Mathematical Biology, November 2015
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Title
Persistence in a Two-Dimensional Moving-Habitat Model
Published in
Bulletin of Mathematical Biology, November 2015
DOI 10.1007/s11538-015-0119-z
Pubmed ID
Authors

Austin Phillips, Mark Kot

Abstract

Environmental changes are forcing many species to track suitable conditions or face extinction. In this study, we use a two-dimensional integrodifference equation to analyze whether a population can track a habitat that is moving due to climate change. We model habitat as a simple rectangle. Our model quickly leads to an eigenvalue problem that determines whether the population persists or declines. After surveying techniques to solve the eigenvalue problem, we highlight three findings that impact conservation efforts such as reserve design and species risk assessment. First, while other models focus on habitat length (parallel to the direction of habitat movement), we show that ignoring habitat width (perpendicular to habitat movement) can lead to overestimates of persistence. Dispersal barriers and hostile landscapes that constrain habitat width greatly decrease the population's ability to track its habitat. Second, for some long-distance dispersal kernels, increasing habitat length improves persistence without limit; for other kernels, increasing length is of limited help and has diminishing returns. Third, it is not always best to orient the long side of the habitat in the direction of climate change. Evidence suggests that the kurtosis of the dispersal kernel determines whether it is best to have a long, wide, or square habitat. In particular, populations with platykurtic dispersal benefit more from a wide habitat, while those with leptokurtic dispersal benefit more from a long habitat. We apply our model to the Rocky Mountain Apollo butterfly (Parnassius smintheus).

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Geographical breakdown

Country Count As %
Australia 1 3%
Unknown 28 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 31%
Researcher 5 17%
Student > Master 4 14%
Student > Postgraduate 2 7%
Student > Bachelor 1 3%
Other 2 7%
Unknown 6 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 31%
Environmental Science 6 21%
Mathematics 3 10%
Economics, Econometrics and Finance 1 3%
Psychology 1 3%
Other 2 7%
Unknown 7 24%
Attention Score in Context

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 June 2016.
All research outputs
#20,334,427
of 22,879,161 outputs
Outputs from Bulletin of Mathematical Biology
#1,000
of 1,101 outputs
Outputs of similar age
#323,802
of 386,591 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#11
of 15 outputs
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