Quantitative evolutionary design.
The field of quantitative evolutionary design uses evolutionary reasoning (in terms of natural selection and ultimate causation) to understand the magnitudes of biological reserve capacities, i.e. excesses of capacities over natural loads. Ratios of capacities to loads, defined as safety factors, fall in the range 1.2-10 for most engineered and biological components, even though engineered safety factors are specified intentionally by humans while biological safety factors arise through natural selection. Familiar examples of engineered safety factors include those of buildings, bridges and elevators (lifts), while biological examples include factors of bones and other structural elements, of enzymes and transporters, and of organ metabolic performances. Safety factors serve to minimize the overlap zone (resulting in performance failure) between the low tail of capacity distributions and the high tail of load distributions. Safety factors increase with coefficients of variation of load and capacity, with capacity deterioration with time, and with cost of failure, and decrease with costs of initial construction, maintenance, operation, and opportunity. Adaptive regulation of many biological systems involves capacity increases with increasing load; several quantitative examples suggest sublinear increases, such that safety factors decrease towards 1.0. Unsolved questions include safety factors of series systems, parallel or branched pathways, elements with multiple functions, enzyme reaction chains, and equilibrium enzymes. The modest sizes of safety factors imply the existence of costs that penalize excess capacities. Those costs are likely to involve wasted energy or space for large or expensive components, but opportunity costs of wasted space at the molecular level for minor components.
Department of Physiology, University of California Medical School, Los Angeles, CA 90095-1751, USA. jdiamond@mednet.ucla.edu
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D000818:Animals; D005075:Biological Evolution; D015984:Causality; D006801:Humans; D008954:Models, Biological; D012449:Safety; D012641:Selection, Genetic