Optimizing Metapopulation Sustainability through a Checkerboard Strategy

The persistence of a spatially structured population is determined by the rate of dispersal among habitat patches. If the local dynamic at the subpopulation level is extinction-prone, the system viability is maximal at intermediate connectivity where recolonization is allowed, but full synchronization that enables correlated extinction is forbidden. Here we developed and used an algorithm for agent-based simulations in order to study the persistence of a stochastic metapopulation. The effect of noise is shown to be dramatic, and the dynamics of the spatial population differs substantially from the predictions of deterministic models. This has been validated for the stochastic versions of the logistic map, the Ricker map and the Nicholson-Bailey host-parasitoid system. To analyze the possibility of extinction, previous studies were focused on the attractiveness (Lyapunov exponent) of stable solutions and the structure of their basin of attraction (dependence on initial population size). Our results suggest that these features are of secondary importance in the presence of stochasticity. Instead, optimal sustainability is achieved when decoherence is maximal. Individual-based simulations of metapopulations of different sizes, dimensions and noise types, show that the system's lifetime peaks when it displays checkerboard spatial patterns. This conclusion is supported by the results of a recently published Drosophila experiment. The checkerboard strategy provides a technique for the manipulation of migration rates (e.g., by constructing corridors) in order to affect the persistence of a metapopulation. It may be used in order to minimize the risk of extinction of an endangered species, or to maximize the efficiency of an eradication campaign.

[1]  T. Reichenbach,et al.  Mobility promotes and jeopardizes biodiversity in rock–paper–scissors games , 2007, Nature.

[2]  B. Kerr,et al.  Local migration promotes competitive restraint in a host–pathogen 'tragedy of the commons' , 2006, Nature.

[3]  A. Nicholson,et al.  Supplement: the Balance of Animal Populations , 1933 .

[4]  H. B. Wilson,et al.  Reinterpreting space, time lags, and functional responses in ecological models. , 2000, Science.

[5]  Simon A. Levin,et al.  Stochastic Spatial Models: A User's Guide to Ecological Applications , 1994 .

[6]  D. Earn,et al.  Global asymptotic coherence in discrete dynamical systems. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Sutirth Dey,et al.  Stability via Asynchrony in Drosophila Metapopulations with Low Migration Rates , 2006, Science.

[8]  Kunihiko Kaneko,et al.  Complex Systems: Chaos and Beyond , 2001 .

[9]  B. Meerson,et al.  Spectral theory of metastability and extinction in birth-death systems. , 2006, Physical review letters.

[10]  T. Miller,et al.  Dispersal Rates Affect Species Composition in Metacommunities of Sarracenia purpurea Inquilines , 2003, The American Naturalist.

[11]  Nadav M. Shnerb,et al.  Extinction Rates for Fluctuation-Induced Metastabilities: A Real-Space WKB Approach , 2006, q-bio/0611049.

[12]  Comment on "Stability via Asynchrony in Drosophila Metapopulations with Low Migration Rates" , 2006, Science.

[13]  Jared M. Diamond,et al.  THE ISLAND DILEMMA: LESSONS OF MODERN BIOGEOGRAPHIC STUDIES FOR THE DESIGN OF NATURAL RESERVES , 1975 .

[14]  I. Hiscock Ecology of Populations , 1969, The Yale Journal of Biology and Medicine.

[15]  D. Sherrington Stochastic Processes in Physics and Chemistry , 1983 .

[16]  J. P. Barkham,et al.  Population Dynamics of the Wild Daffodil (Narcissus Pseudonarcissus): III. Implications of a Computer Model of 1000 Years of Population Change , 1982 .

[17]  Steven H. Strogatz,et al.  Nonlinear Dynamics and Chaos , 2024 .

[18]  Alan Hastings,et al.  Complex interactions between dispersal and dynamics: Lessons from coupled logistic equations , 1993 .

[19]  G. Hartvigsen Metapopulation biology: Ecology, genetics, and evolution , 1997 .

[20]  D. Earn,et al.  Coherence and conservation. , 2000, Science.

[21]  Robert M. May,et al.  Dispersal in stable habitats , 1977, Nature.

[22]  Mauro Mobilia,et al.  Fluctuations and correlations in lattice models for predator-prey interaction. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[23]  Kaneko,et al.  Globally coupled chaos violates the law of large numbers but not the central-limit theorem. , 1990, Physical review letters.

[24]  Michael D. Bordo,et al.  Have National Business Cycles Become More Synchronized? , 2003 .

[25]  N. Kampen,et al.  Stochastic processes in physics and chemistry , 1981 .

[26]  M. Holyoak,et al.  Persistence of an Extinction-Prone Predator-Prey Interaction Through Metapopulation Dynamics , 1996 .

[27]  David R. Appleton,et al.  Modelling Biological Populations in Space and Time , 1993 .

[28]  Per Lundberg,et al.  Noise colour and the risk of population extinctions , 1996, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[29]  R M Nisbet,et al.  Habitat structure and population persistence in an experimental community , 2001, Nature.

[30]  Eric Renshaw Modelling biological populations in space and time , 1990 .

[31]  A. Nicholson,et al.  The Balance of Animal Populations.—Part I. , 1935 .

[32]  Charles S. ReVelle,et al.  Spatial attributes and reserve design models: A review , 2005 .

[33]  K. Kaneko Clustering, coding, switching, hierarchical ordering, and control in a network of chaotic elements , 1990 .

[34]  Alessandro Flammini,et al.  Species lifetime distribution for simple models of ecologies. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[35]  F. Adler Migration Alone Can Produce Persistence of Host-Parasitoid Models , 1993, The American Naturalist.

[36]  Chris D. Thomas,et al.  Correlated extinctions, colonizations and population fluctuations in a highly connected ringlet butterfly metapopulation , 1997, Oecologia.

[37]  M. Feldman,et al.  Local dispersal promotes biodiversity in a real-life game of rock–paper–scissors , 2002, Nature.

[38]  Bernd Blasius,et al.  Complex dynamics and phase synchronization in spatially extended ecological systems , 1999, Nature.

[39]  J. García-Ojalvo,et al.  Effects of noise in excitable systems , 2004 .

[40]  N. Shnerb,et al.  Stabilization of metapopulation cycles: toward a classification scheme. , 2008, Theoretical population biology.

[41]  W. Ebeling Stochastic Processes in Physics and Chemistry , 1995 .

[42]  M. Gyllenberg,et al.  Does migration stabilize local population dynamics? Analysis of a discrete metapopulation model. , 1993, Mathematical biosciences.

[43]  Richard V. Solé,et al.  Self-Organization in Complex Ecosystems. , 2006 .

[44]  Nadav M Shnerb,et al.  Amplitude-dependent frequency, desynchronization, and stabilization in noisy metapopulation dynamics. , 2006, Physical review letters.

[45]  A. Kamenev,et al.  Rare event statistics in reaction-diffusion systems. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[46]  J. Molofsky,et al.  Extinction dynamics in experimental metapopulations. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[47]  R. Nisbet,et al.  Spatial structure and fluctuations in the contact process and related models , 2000, Bulletin of mathematical biology.