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Microscaling: Why Larger Anemones Have Longer Cnidae

Shannon Point Marine Center, Western Washington University, 1700 Shannon Point Rd., Anacortes, Washington 98221-4042

Scaling analysis provides a quantitative method for describing and comparing how qualities of organisms vary as a function of body size. However, cell level phenomena have been notoriously hard to analyze because animal cells and organelles have such irregular shapes. The intracellular cnidae make good models of scaling at the cell level because they are durable and easy to image and measure. The mean length of unfired tentacle cnidae (spirocysts) varies continuously, and reversibly, with body size for three macrophagous anemone species. Significant differences in spirocyst shape and size relative to body mass are related to differences in tissue functions and species ecologies, strongly suggesting that cnida size, shape, and scaling patterns respond to natural selection. Cnida scaling patterns can be treated as features of cnidarian life histories. Spirocyst scaling exponents (slopes of log cnida dimension vs. log body weight) are similar to each other (0.05–0.09) and to reported values for animal somatic cells (0.017–0.17), but are much smaller than reported values for anemone basal diameters (0.30–0.38). I propose, here, a general, mechanical explanation for microscaling of structural secretory cells and their secretions, including the cnidae. Larger bodies require thicker, pliant sheets of sluggishly respiring extracellular support materials such as mesoglea and basement membrane. Thicker mesoglea can support larger, taller epithelial cells, which in turn provide additional maintenance services for these progressively thicker acellular layers. Ultimately, larger, taller cells can secrete and support larger, longer cnidae.

Abbreviations: b, slope of the log-log plot • OLS, ordinary least squares regression estimate of line fit • RMA, reduced major axis estimate of line fit • 95% CI, 95% confidence intervals (for slope and intercept estimates) • %SEE, percent standard error of estimate

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