Survivability Is More Fundamental Than Evolvability

• Published in: PloS one Vol. 7; no. 6; p. e38025
• Main Authors: Palmer, Michael E., Feldman, Marcus W.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 18.06.2012; Public Library of Science (PLoS)
• Subjects: Adaptation; Adaptation, Biological; Algorithms; Biological Evolution; Biology; Dispersal; Dispersion; E coli; Emigration and Immigration; Environment; Escherichia coli; Evolution; Experiments; Extinction; Genetic Fitness; Genomes; Genotype; Heritability; Models, Genetic; Mutation; Mutation rates; Phenotype; Population; Population Density; Quantitative genetics; Quantitative research; Reproduction (biology); Sexual reproduction; Species extinction; Success; Survivability; Variation; United States > US; California
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0038025

For a lineage to survive over long time periods, it must sometimes change. This has given rise to the term evolvability, meaning the tendency to produce adaptive variation. One lineage may be superior to another in terms of its current standing variation, or it may tend to produce more adaptive variation. However, evolutionary outcomes depend on more than standing variation and produced adaptive variation: deleterious variation also matters. Evolvability, as most commonly interpreted, is not predictive of evolutionary outcomes. Here, we define a predictive measure of the evolutionary success of a lineage that we call the k-survivability, defined as the probability that the lineage avoids extinction for k generations. We estimate the k-survivability using multiple experimental replicates. Because we measure evolutionary outcomes, the initial standing variation, the full spectrum of generated variation, and the heritability of that variation are all incorporated. Survivability also accounts for the decreased joint likelihood of extinction of sub-lineages when they 1) disperse in space, or 2) diversify in lifestyle. We illustrate measurement of survivability with in silico models, and suggest that it may also be measured in vivo using multiple longitudinal replicates. The k-survivability is a metric that enables the quantitative study of, for example, the evolution of 1) mutation rates, 2) dispersal mechanisms, 3) the genotype-phenotype map, and 4) sexual reproduction, in temporally and spatially fluctuating environments. Although these disparate phenomena evolve by well-understood microevolutionary rules, they are also subject to the macroevolutionary constraint of long-term survivability.