|InterJournal Complex Systems, 1793
|Manuscript Number: |
Submission Date: 2006
|Biotic Population Dynamics and the Theory of Evolution|
We present a theory of evolution and empirical support from empirical studies and computer models of population dynamics. We analyzed published data (Global Population Dynamics Database, NERC Centre for Population Biology) of six animal species and found in five (lynx, muskrat, beaver, salmon, fox) that changes in population size display a pattern characterized by novelty, diversification, non-random complexity, asymmetric statistical distribution, non-uniform recurrence and wavelet plots, and partial autocorrelation. These features characterize bios, as contrasted to random, periodic, chaotic, or random walk patterns. Biotic patterns are also demonstrated in time series generated with multi-agent predator-prey simulations. Biotic patterns have also been found in heartbeat interval series, Schrodingerís wave function, temporal distribution of galaxies, economic processes, meteorological time series, sequences of bases in DNA, and other data (Sabelli, Bios, A Study of Creation, World Scientific, 2005; see also Thomas et al, this meeting), indicating that they are the expected product of generic natural processes such as those abstracted by lattice action, group opposition, and topological connection. Biotic patterns are generated mathematically with bipolar feedback models such as A(t+1) = sin(A(t)* k * t) (+ A(t) that combine action (recursion), bipolar opposition (trigonometric function) and connection with previous state (+ A(t) term). These observations suggest that population dynamics may be largely determined by bipolar feedback processes. We propose that biological evolution results from the formation and conservation of structure by connections among pre-existing units, and by the generation of novelty and diversity by bipolar (synergistic and antagonistic) feedback interactions --as contrasted to standard evolutionary theory that attributes novelty to random changes and selection to competition and conflict.
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