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Alan J. McKane
Researcher at University of Manchester
Publications - 210
Citations - 8963
Alan J. McKane is an academic researcher from University of Manchester. The author has contributed to research in topics: Population & Stochastic modelling. The author has an hindex of 51, co-authored 209 publications receiving 8465 citations. Previous affiliations of Alan J. McKane include Isaac Newton Institute & University of Virginia.
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Journal ArticleDOI
Interaction strengths in food webs: issues and opportunities
Eric L. Berlow,Anje-Margiet Neutel,Joel E. Cohen,Peter C. de Ruiter,Bo Ebenman,Mark C. Emmerson,Jeremy W. Fox,Vincent A. A. Jansen,J. Iwan Jones,Giorgos D. Kokkoris,Dmitrii O. Logofet,Alan J. McKane,José M. Montoya,Owen L. Petchey +13 more
TL;DR: The various ways in which the term ‘interaction strength’ has been applied are described and the implications of loose terminology and definition for the development of this field are discussed.
Journal ArticleDOI
Predator-prey cycles from resonant amplification of demographic stochasticity.
Alan J. McKane,Timothy J. Newman +1 more
TL;DR: This work presents the simplest individual level model of predator-prey dynamics and shows, via direct calculation, that it exhibits cycling behavior, indicating that additional biological mechanisms may not be necessary to explain observed predator- prey cycles in real (finite) populations.
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The merits of neutral theory.
TL;DR: It is argued that neutral theory is also a stochastic theory, a sampling theory and a dispersal-limited theory, and these important additional features should be retained in future theoretical developments of community ecology.
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The Influence of Predator–Prey Population Dynamics on the Long-term Evolution of Food Web Structure
TL;DR: Although there are significant fluctuations in species diversity because of speciation and extinction, very large-scale extinction avalanches appear to be absent from the dynamics, and no evidence for self-organized criticality is found.
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Stochastic amplification in epidemics
TL;DR: A stochastic theory for the major dynamical transitions in epidemics from regular to irregular cycles is presented, which relies on the discrete nature of disease transmission and low spatial coupling to show how the amplification of noise varies across these transitions.