The expansion of information in ecological systems: Emergence as a quantifiable state

Abstract Although the term ‘emergence’ has received wide attention in the literature, most of this attention has been focused on epistemological discussions about the nature of what might be considered emergent behavior in self-organizing systems. For the concept of emergence to have any great utility for biologists, it must (1) be perceptible as a physical, quantitative property rather than just a philosophical one; (2) have a quantitative definition applicable to all levels of biological organization; and (3) be an essential component of biological system performance or evolution. Using an independent, cellular population model (running in the StarLogo system), we have developed a mutual information calculation to measure the information expansion when considering the interactions between a population of herbivores and an environment in comparison to the interactions between the individual herbivores and that environment. In self-organizing biological systems, the collective action of massively parallel units generates a greater potential complexity in the information processing capacity of the ‘whole’ system relative to the ‘individual’ parts, and as such, there is a demonstrable increase in mutual information content. From this perspective, we consider emergence to exist as a simple information expansion that is a default behavior of any system with multiple, component parts governed by a simple, probabilistic rule set. It is not a first principle of self-organizing biological systems, but rather a collective behavior that can be quantitatively described in practical terms for experimental biologists. With a quantitative formulation, the concept of emergence may become a useful information statistic in assessing the structure of biological systems.

[1]  Eric Klopfer,et al.  Technologies to support the creation of complex systems models--using StarLogo software with students. , 2003, Bio Systems.

[2]  Venkat Venkatasubramanian,et al.  Spontaneous emergence of complex optimal networks through evolutionary adaptation , 2004, Comput. Chem. Eng..

[3]  Mitchel Resnick,et al.  New paths on a StarLogo adventure , 2002, Comput. Graph..

[4]  John Aach,et al.  Mathematical models of diffusion-constrained polymerase chain reactions: basis of high-throughput nucleic acid assays and simple self-organizing systems. , 2004, Journal of theoretical biology.

[5]  J. Crutchfield.  The calculi of emergence: computation, dynamics and induction , 1994 .

[6]  B. Breckling,et al.  Emergent properties in individual-based ecological models—introducing case studies in an ecosystem research context , 2005 .

[7]  Piers K. Dunstan,et al.  Predicting global dynamics from local interactions: individual-based models predict complex features of marine epibenthic communities , 2005 .

[8]  Andrew Begel,et al.  StarLogo under the hood and in the classroom , 2003 .

[9]  Thomas Mitchell-Olds,et al.  Evolutionary and ecological functional genomics , 2003, Nature Reviews Genetics.

[10]  B. Luque.  An introduction to physical theory of molecular evolution , 2003 .

[11]  Brian O'Rourke,et al.  The fractal architecture of cytoplasmic organization: Scaling, kinetics and emergence in metabolic networks , 2004, Molecular and Cellular Biochemistry.

[12]  Simon Kirby,et al.  Complex Systems in Language Evolution: the Cultural Emergence of Compositional Structure , 2003, Adv. Complex Syst..

[13]  Mitchel Resnick,et al.  Turtles, termites, and traffic jams - explorations in massively parallel microworlds , 1994 .

[14]  T. D. Schneider,et al.  Anatomy of Escherichia coli ribosome binding sites. , 2001, Journal of molecular biology.

[15]  B. Breckling,et al.  The concepts of emergent and collective properties in individual-based models—Summary and outlook of the Bornhöved case studies , 2005 .

[16]  C. D. Hulsey,et al.  Many-to-One Mapping of Form to Function: A General Principle in Organismal Design?1 , 2005, Integrative and comparative biology.

[17]  Thomas S. Ray,et al.  Evolution, complexity, entropy and artificial reality , 1994 .

[18]  Broder Breckling,et al.  A spatiotemporal individual-based fish model to investigate emergent properties at the organismal and the population level , 2005 .

[19]  Paul Humphreys,et al.  Emergence, Not Supervenience , 1997, Philosophy of Science.

[20]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[21]  Mark M. Millonas,et al.  A connectionist type model of self-organized foraging and emergent behavior in ant swarms* , 1992 .

[22]  Hauke Reuter,et al.  Community processes as emergent properties: Modelling multilevel interaction in small mammals communities , 2005 .

[23]  Tapabrata Ray,et al.  Society and civilization: An optimization algorithm based on the simulation of social behavior , 2003, IEEE Trans. Evol. Comput..

[24]  Chrystopher L. Nehaniv,et al.  Evolvability of the Genotype-Phenotype Relation in Populations of Self-Replicating Digital Organisms in a Tierra-Like System , 2003, ECAL.

[25]  Ole Kniemeyer,et al.  Representation of Genotype and Phenotype in a Coherent Framework Based on Extended L-Systems , 2003, ECAL.

[26]  Toshihiro Shimizu,et al.  Information flow and emergence of the global patterns in connected neural networks , 2004 .

[27]  Edwin N. Lightfoot,et al.  Emergence (Unpredictability) and the Evolution of Novel Designs , 2004 .

[28]  J. Shapiro.  A 21st Century View of Evolution , 2002, Journal of biological physics.

[29]  S Bornholdt,et al.  Robustness as an evolutionary principle , 2000, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[30]  H. Morowitz.  The Emergence of Everything: How the World Became Complex , 2002 .

[31]  P Fleissner,et al.  Emergent information. Towards a unified information theory. , 1996, Bio Systems.

[32]  B. Corbara.  Self-organization in the division of labor in incipient societies of the ant Ectatomma ruidum (Formicidae: Ponerinae): emergence of an age polyethism. , 2000 .

[33]  Karin Klenke.  Information Technologies as Drivers of Emergent Organizational Forms: A Leadership Perspective , 1994, Transforming Organizations with Information Technology.

[34]  William C. Wimsatt,et al.  Simple Systems and Phylogenetic Diversity , 1998, Philosophy of Science.

[35]  W J Freeman,et al.  Biocomplexity: adaptive behavior in complex stochastic dynamical systems. , 2001, Bio Systems.

[36]  P. Bak,et al.  Evolution as a self-organized critical phenomenon. , 1995, Proceedings of the National Academy of Sciences of the United States of America.