Abstract
We compare and contrast the long-time dynamical properties of two individual-based models of biological coevolution. Selection occurs via multispecies, stochastic population dynamics with reproduction probabilities that depend nonlinearly on the population densities of all species resident in the community. New species are introduced through mutation. Both models are amenable to exact linear stability analysis, and we compare the analytic results with large-scale kinetic Monte Carlo simulations, obtaining the population size as a function of an average interspecies interaction strength. Over time, the models self-optimize through mutation and selection to approximately maximize a community potential function, subject only to constraints internal to the particular model. If the interspecies interactions are randomly distributed on an interval including positive values, the system evolves toward self-sustaining, mutualistic communities. In contrast, for the predator–prey case the matrix of interactions is antisymmetric, and a nonzero population size must be sustained by an external resource. Time series of the diversity and population size for both models show approximate 1/f noise and power-law distributions for the lifetimes of communities and species. For the mutualistic model, these two lifetime distributions have the same exponent, while their exponents are different for the predator–prey model. The difference is probably due to greater resilience toward mass extinctions in the food-web like communities produced by the predator–prey model.
Similar content being viewed by others
References
Alonso D. and McKane A.J. (2004). Sampling Hubbell’s neutral theory of biodiversity. Ecol. Lett. 7: 901–10
Armstrong R.A. and McGehee R. (1980). Competitive exclusion. Am. Nat. 115: 151–70
Bak P. and Sneppen K. (1993). Punctuated equilibrium and criticality in a simple model of evolution. Phys. Rev. Lett. 71: 4083–086
Bascompte J., Jordano P. and Olesen J.M. (2006). Asymmetric coevolutionary networks facilitate biodiversity maintenance. Science 312: 431–33
den Boer P.J. (1986). The present status of the competitive exclusion principle. Trends Ecol. Evol. 1: 25–8
Bronstein J.L. (1994). Our current understanding of mutualism. Quart. Rev. Biol. 69: 31–1
Caldarelli G., Higgs P.G. and McKane A.J. (1998). Modelling coevolution in multispecies communities. J. Theor. Biol. 193: 345–58
Chowdhury, D., Stauffer, D.: Evolutionary ecology in-silico: does mathematical modelling help in understanding the generic trends? J. Biosci. 30, 277–87 (references therein) (2005)
Chowdhury D., Stauffer D. and Kunwar A. (2003). Unification of small and large time scales for biological evolution: Deviations from power law. Phys. Rev. Lett. 90: 068101
Christensen K., di Collobiano S.A., Hall M. and Jensen H.J. (2002). Tangled-nature: a model of evolutionary ecology. J. Theor. Biol. 216: 73–4
di Collobiano S.A., Christensen K. and Jensen H.J. (2003). The tangled nature model as an evolving quasi-species model. J. Phys. A 36: 883–91
Crawford J.D. (1991). Introduction to bifurcation theory. Rev. Mod. Phys. 63: 991–037
Crosby J.L. (1970). The evolution of genetic discontinuity: computer models of the selection of barriers to interbreeding between subspecies. Heredity 25: 253–97
Doebeli, M., Dieckmann, U.: Evolutionary branching and sympatric speciation caused by different types of ecological interactions. Am. Nat. 156, S77–S101 (references therein) (2000)
Dorogovtsev S.N., Mendes J.F.F. and Pogorelov Yu.G. (2000). Bak-Sneppen model near zero dimension. Phys. Rev. E 62: 295–98
Drossel B., Higgs P.G. and McKane A.J. (2001). The influence of predator–prey population dynamics on the long-term evolution of food web structure. J. Theor. Biol. 208: 91–07
Drossel B., McKane A. and Quince C. (2004). The impact of non-linear functional responses on the long-term evolution of food web structure. J. Theor. Biol. 229: 539–48
Dunne J., Williams R.J. and Martinez N.D. (2002). Network structure and diversity loss in food webs: robustness ineases with connectance. Ecol. Lett. 5: 558–67
Eigen M. (1971). Selforganization of matter and evolution of biological maomolecules. Naturwissenschaften 58: 465
Eigen M., McCaskill J. and Schuster P. (1988). Molecular quasi-species. J. Phys. Chem. 92: 6881–891
Garlaschelli, D.: Universality in food webs. Eur. Phys. J. B 38, 277–85 (references therein) (2004)
Gavrilets S. (1999). Dynamics of clade diversification on the morphological hypercube. Proc. R. Soc. Lond. B 266: 817–24
Gavrilets S. (2004). Fitness Landscapes and The Origin of Species. Princeton University Press, Princeton and Oxford
Gavrilets S. and Boake C.R.B. (1998). On the evolution of premating isolation after a founder event. Am. Nat. 152: 706–16
Gavrilets S., Li H. and Vose M.D. (2000). Patterns of parapatric speciation. Evolution 54: 1126–134
Gavrilets S. and Vose A. (2005). Dynamic patterns of adaptive radiation. Proc. Natl. Acad. Sci. USA 102: 18040–8045
Goldenfeld N. (1992). Lectures on Phase Transitions and the Renormalization Group. Addison–Wesley, Reading, MA
Haken H. (1977). Synergetics—An Introduction. Springer, Berlin
Hall M., Christensen K., di Collobiano S.A. and Jensen H.J. (2002). Time-dependent extinction rate and species abundance in a tangled-nature model of biological evolution. Phys. Rev. E 66: 011904
Hardin G. (1960). The competitive exclusion principle. Science 131: 1292–297
Hohenberg P.C. and Halperin B. (1977). Theory of dynamic critical phenomena. Rev. Mod. Phys. 49: 435–79
Hubbell, S.P.: The Unified Neutral Theory of Biodiversity and Biogeography. Princeton University Press, Princeton, Chap. 5 (2001)
Kauffman S.A. (1993). The Origins of Order. Self-organization and selection in evolution. Oxford University Press, Oxford
Kauffman S.A. and Johnsen S. (1991). Coevolution to the edge of chaos: coupled fitness landscapes, poised states and coevolutionary avalanches. J. Theor. Biol. 149: 467–05
Kawanabe H., Cohen J.E. and Iwasaki K. (1993). Mutualism and Community Organization. Oxford University Press, Oxford
Krebs, C.J.: Ecological Methodology. Harper & Row, New York, Chap. 10 (1989)
Krebs, C.J.: Ecology. The Experimental Analysis of Distribution and Abundance, 5th edn. Benjamin Cummings, San Francisco, Chaps. 13, 14 (2001)
Metz J.A.J., Nisbet R.M. and Geritz S.A.H. (1992). How should we define ‘fitness’for general ecological scenarios?. Trends Ecol. Evol. 7: 198–02
Murray J.D. (1989). Mathematical Biology. Springer, Berlin
Newman M.E.J. (2005). Power laws, Pareto distributions and Zipf’s law. Contemp. Phys. 46: 323–51
Newman M.E.J. and Palmer R.G. (2003). Modeling Extinction. Oxford University Press, Oxford
Newman M.E.J. and Sibani P. (1999). Extinction, diversity and survivorship of taxa in the fossil record. Proc. R. Soc. Lond. B 266: 1583–599
Paczuski M., Maslov S. and Bak P. (1996). Avalanche dynamics in evolution, growth, and depinning models. Phys. Rev. E 53: 414–43
Pathria, R.K.: Statistical Mechanics, 2nd edn. Butterworth-Heinemann, Oxford, Chaps. 11, 14 (1996)
Pigolotti S., Flammini A., Marsili M. and Maritan A. (2005). Species lifetime distribution for simple models of ecologies. Proc. Natl. Acad. Sci. USA 102: 15747–5751
Press W.H., Teukolsky S.A., Vetterling W.T. and Flannery B.P. (1992). Numerical Recipes, 2nd edn. Cambridge University Press, Cambridge
Rikvold, P.A., Sevim, V.: An individual-based predator–prey model for biological coevolution: fluctuations, stability, and community structure. Phys. Rev. E E-print arXiv:q-bio.PE/0611023 (in press)
Rikvold, P.A.: Complex behavior in simple models of biological coevolution. Int. J. Mod. Phys. C. E-print arXiv:q-bio.PE/0609013 (in press)
Rikvold, P.A.: Fluctuations in models of biological maoevolution. In: Kish, L.B., Lindenberg, K., Gingl, Z. (eds.) Noise in Complex Systems and Stochastic Dynamics III, pp. 148–55. SPIE, The International Society for Optical Engineering, Bellingham, WA (E-print arXiv:q-bio.PE/0502046) (2005)
Rikvold P.A. and Zia R.K.P. (2003). Punctuated equilibria and 1/f noise in a biological coevolution model with individual-based dynamics. Phys. Rev. E 68: 031913
Roberts A. (1974). The stability of a feasible random ecosystem. Nature (Lond) 251: 607–08
Sato K., Ito Y., Yomo T. and Kaneko K. (2003). On the relation between fluctuation and response in biological systems. Proc. Natl. Acad. Sci. USA 100: 14,086–4,090
Sevim V. and Rikvold P.A. (2005). Effects of correlated interactions in a biological coevolution model with individual-based dynamics. J. Phys. A 38: 9475–489
Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–23, 628–56 (1948)
Shannon C.E. and Weaver W. (1949). The Mathematical Theory of Communication. University of Illinois Press, Urbana
Solé R.V., Bascompte J. and Manrubia S. (1996). Extinction: bad genes or weak chaos?. Proc. R. Soc. Lond B 263: 1407–413
Strogatz S.H. (1994). Nonlinear Dynamics and Chaos. Westview Press, Boston
Thompson J.N. (1998). Rapid evolution as an ecological process. Trends Ecol. Evol. 13: 329–32
Thompson J.N. (1999). The evolution of species interactions. Science 284: 2116–118
Tokita K. and Yasutomi A. (2003). Emergence of a complex and stable network in a model ecosystem with extinction and mutation. Theor. Popul. Biol. 63: 131–46
Verhulst P.F. (1838). Notice sur la loi que la population suit dans son acoissement. Corres. Math. Physique 10: 113–21
Volkov I., Banavar J.R., He F., Hubbell S.P. and Maritan A. (2005). Density dependence explains tree species abundance and diversity in tropical forests. Nature 438: 658–61
Wills C., Harms K.E., Condit R., King D., Thompson J., He F., Muller-Landau H.C., Ashton P., Losos E., Comita L., Hubbell S., LaFrankie J., Bunyavejchevin S., Dattaraja H.S., Davies S., Esufali S., Foster R., Gunatilleke N., Gunatilleke S., Hall P., Itoh A., John R., Kiratiprayoon S., Massa M., Nath C., NurSupradi Noor M., Kassim A.R., Sukumar R., Suresh H.S., Sun I.F., Tan S., Yamakura T., Zimmerman J. and Lao S.L. (2006). Nonrandom processes maintain diversity in tropical forests. Science 311: 527–31
Yoshida T., Jones L.E., Ellner S.P., Fussmann G.F. and Hairston N.G. (2003). Rapid evolution drives ecological dynamics in a predator–prey system. Nature 424: 303–06
Zia R.K.P. and Rikvold P.A. (2004). Fluctuations and correlations in an individual-based model of biological coevolution. J. Phys. A 37: 5135–155
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Rikvold, P.A. Self-optimization, community stability, and fluctuations in two individual-based models of biological coevolution. J. Math. Biol. 55, 653–677 (2007). https://doi.org/10.1007/s00285-007-0101-y
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00285-007-0101-y


