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Survivorship in the Bivalvia: comparing living and extinct genera and families
Published online by Cambridge University Press: 08 February 2016
Abstract
George Gaylord Simpson was one of the first paleontologists to apply survivorship analysis to the study of fossil taxa. His finding that the survivorship curve for extant bivalve genera plotted above that for extinct genera led him to conclude that bivalve genera are drawn from at least two distinct distributions of longevities, and formed the fundamental basis for his influential concepts of horotelic and bradytelic evolutionary rates. Survivorship curves presented in this paper show the same pattern of disjunct survivorship in genera from the Treatise on Invertebrate Paleontology and in families from Sepkoski's compendium.
Some of the observed differences between survivorship curves are artificial, occurring because long-lived genera and families are more likely to survive to the Recent than short-lived genera and families. The living fauna thus contains a disproportionate number of long-lived genera and families, and the survivorship curve for the living fauna is expected to lie above that for the extinct fauna for this reason alone—even if all longevities are drawn from the same distribution. Recognition of this bias led Raup (1975) to question the significance of the survivorship patterns presented by Van Valen (1973), and Stanley's (1984) acceptance of Raup's argument led him to dismiss the survivorship pattern discovered by Simpson. But statistical analysis using bootstrapping shows that this bias accounts for only a small proportion of the difference between survivorship curves. Other biases considered, such as “pull of the Recent,” “asymmetrical range truncation,” and erroneous concatenation of stratigraphic ranges, do not account for the pattern either. Although still other biases, as yet unknown, cannot definitively be ruled out, it appears that the longevities of extinct and living bivalve taxa are meaningfully different, and that the fundamental causes are biological.
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