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Effects of rapid prey evolution on predator–prey cycles

Overview of attention for article published in Journal of Mathematical Biology, May 2007
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Title
Effects of rapid prey evolution on predator–prey cycles
Published in
Journal of Mathematical Biology, May 2007
DOI 10.1007/s00285-007-0094-6
Pubmed ID
Authors

Laura E. Jones, Stephen P. Ellner

Abstract

We study the qualitative properties of population cycles in a predator-prey system where genetic variability allows contemporary rapid evolution of the prey. Previous numerical studies have found that prey evolution in response to changing predation risk can have major quantitative and qualitative effects on predator-prey cycles, including: (1) large increases in cycle period, (2) changes in phase relations (so that predator and prey are cycling exactly out of phase, rather than the classical quarter-period phase lag), and (3) "cryptic" cycles in which total prey density remains nearly constant while predator density and prey traits cycle. Here we focus on a chemostat model motivated by our experimental system (Fussmann et al. in Science 290:1358-1360, 2000; Yoshida et al. in Proc roy Soc Lond B 424:303-306, 2003) with algae (prey) and rotifers (predators), in which the prey exhibit rapid evolution in their level of defense against predation. We show that the effects of rapid prey evolution are robust and general, and furthermore that they occur in a specific but biologically relevant region of parameter space: when traits that greatly reduce predation risk are relatively cheap (in terms of reductions in other fitness components), when there is coexistence between the two prey types and the predator, and when the interaction between predators and undefended prey alone would produce cycles. Because defense has been shown to be inexpensive, even cost-free, in a number of systems (Andersson et al. in Curr Opin Microbiol 2:489-493, 1999: Gagneux et al. in Science 312:1944-1946, 2006; Yoshida et al. in Proc Roy Soc Lond B 271:1947-1953, 2004), our discoveries may well be reproduced in other model systems, and in nature. Finally, some of our key results are extended to a general model in which functional forms for the predation rate and prey birth rate are not specified.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 3%
Brazil 2 2%
India 2 2%
France 1 <1%
Switzerland 1 <1%
South Africa 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
United States 1 <1%
Other 0 0%
Unknown 88 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 30%
Researcher 18 18%
Student > Bachelor 11 11%
Student > Master 10 10%
Professor 5 5%
Other 17 17%
Unknown 10 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 47%
Environmental Science 16 16%
Physics and Astronomy 9 9%
Mathematics 7 7%
Biochemistry, Genetics and Molecular Biology 4 4%
Other 7 7%
Unknown 11 11%
Attention Score in Context

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 09 May 2022.
All research outputs
#7,453,479
of 22,786,691 outputs
Outputs from Journal of Mathematical Biology
#155
of 655 outputs
Outputs of similar age
#25,258
of 72,037 outputs
Outputs of similar age from Journal of Mathematical Biology
#1
of 2 outputs
Altmetric has tracked 22,786,691 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 655 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 63% 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 72,037 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
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