Growth or reproduction: emergence of an evolutionary optimal strategy

Modern ecology has re-emphasized the need for a quantitative understanding of the original 'survival of the fittest theme' based on analyzis of the intricate trade-offs between competing evolutionary strategies that characterize the evolution of life. This is key to the understanding of species coexistence and ecosystem diversity under the omnipresent constraint of limited resources. In this work we propose an agent based model replicating a community of interacting individuals, e.g. plants in a forest, where all are competing for the same finite amount of resources and each competitor is characterized by a specific growth-reproduction strategy. We show that such an evolution dynamics drives the system towards a stationary state characterized by an emergent optimal strategy, which in turn depends on the amount of available resources the ecosystem can rely on. We find that the share of resources used by individuals is power-law distributed with an exponent directly related to the optimal strategy. The model can be further generalized to devise optimal strategies in social and economical interacting systems dynamics.

[1]  Flávia Freitas Coelho,et al.  Density-dependent reproductive and vegetative allocation in the aquatic plant Pistia stratiotes (Araceae). , 2014, Revista de biologia tropical.

[2]  Michael E. Fisher,et al.  Scaling Theory for Finite-Size Effects in the Critical Region , 1972 .

[3]  Eric R. Pianka,et al.  On r- and K-Selection , 1970, The American Naturalist.

[4]  Miroslaw R. Dudek,et al.  Lotka-Volterra population model of genetic evolution , 2007, q-bio/0701031.

[5]  Andrea Rinaldo,et al.  Ontogenetic growth (Communication arising): Modelling universality and scaling , 2002, Nature.

[6]  Filippo Simini,et al.  Self-similarity and scaling in forest communities , 2010, Proceedings of the National Academy of Sciences.

[7]  Enrico Bertuzzo,et al.  Spatial effects on species persistence and implications for biodiversity , 2011, Proceedings of the National Academy of Sciences.

[8]  R. Axtell.  Zipf Distribution of U.S. Firm Sizes , 2001, Science.

[9]  Peter Chesson,et al.  The interaction between predation and competition , 2008, Nature.

[10]  James H. Brown,et al.  A general model for ontogenetic growth , 2001, Nature.

[11]  R. Macarthur,et al.  The Theory of Island Biogeography , 1969 .

[12]  F J Ayala,et al.  Density-dependent natural selection and trade-offs in life history traits. , 1991, Science.

[13]  P. David,et al.  Coexistence in a metacommunity: the competition-colonization trade-off is not dead. , 2006, Ecology letters.

[14]  L. Bertalanffy.  Quantitative Laws in Metabolism and Growth , 1957 .

[15]  Richard E. Lenski,et al.  Experimental Tests for an Evolutionary Trade‐Off between Growth Rate and Yield in E. coli , 2006, The American Naturalist.

[16]  James P. Collins,et al.  Environmental Certainty, Trophic Level, and Resource Availability in Life History Evolution , 1974, The American Naturalist.

[17]  H. Godfray,et al.  Basis of the trade–off between parasitoid resistance and larval competitive ability in Drosophila melanogaster , 2001, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[18]  H. Takayasu,et al.  Zipf's law in income distribution of companies , 1999 .

[19]  Stephen P Ellner,et al.  Energy storage and the evolution of population dynamics. , 2002, Journal of theoretical biology.

[20]  S. Levin,et al.  Comparing Classical Community Models: Theoretical Consequences for Patterns of Diversity , 2002, The American Naturalist.

[21]  Sebastian Bernhardsson,et al.  Zipf's law unzipped , 2011, ArXiv.

[22]  Eric R. Ziegel,et al.  Statistical Size Distributions in Economics and Actuarial Sciences , 2004, Technometrics.

[23]  Jonathan M. Chase,et al.  Trade‐offs in community ecology: linking spatial scales and species coexistence , 2004 .