Abstract
Existing wave concepts are based on energy conservation (1st law) and on measurable variables like wavelength, amplitude, frequency or velocity which define the energy and the behaviour of waves in space and time. A wave concept related to the 2nd law treats living systems as self-propagating wavefronts. These wavefronts are defined by the degradation of energy per unit time and by constituent sets of lineages of information which are in the most abstract case defined by positions in one spatial dimension, relatedness along the time axis, masses, energy flux shares, mass-specific metabolic rates, and adaptability; if the adaptability of the lineages is constrained, it is necessary to define the conditions in multidimensional niche space which permit lineages to propagate. The dynamics of the wavefront is defined by the likelihood and magnitude of exchanges of energy flux shares between the lineages, the macroevolutionary drift of mass and drift of mass-specific metabolic rate, the ratio of energy flux share to metabolic rate in relation to thresholds for the dissipation and amplification of lineages, and by niche drift which can be replaced by spatial drift if adaptability is unconstrained. This concept allows to create an at its roots simple numerical physics, the difference between animate and conventional inanimate physics being a higher number of relevant dimensions and the replacement of constants by measurable variables. From the physical point of view, this concept, in which the evolutionary drift is the consequence of variable natural selection in combination with constrained adaptability and genetic drift, is not restricted to any particular form of life (i.e. mechanics of information storage or processing). Cellular automata permit to apply this concept to abstract as well as realistic settings so that the causation of patterns, which are drawn from large sets of lineages and based on the variables mentioned, can be studied in one to three spatial dimensions within multidimensional niche spaces under application of arbitrarily defined rules. In application to real systems, the strategy is to determine time-independent virtual equilibria based on measurable axioms, including the assumption of energy flux conservation, and to identify neglected facts (like time dependence, demographic or microevolutionary processes/phenomena) which explain differences between the virtual, purely macroevolutionary computer worlds and reality.